**Nanofluids**

Wei Yu, Huaqing Xie and Lifei Chen *Shanghai Second Polytechnic University P. R. China* 

## **1. Introduction**

496 Smart Nanoparticles Technology

*Nogues, J. and et al. (2006) Shell-driven magnetic stability in core-shell nanoparticles.* Physical

Nanofluids are a new class of fluids engineered by dispersing nanometer-sized materials (nanoparticles, nanofibers, nanotubes, nanorods, nanosheet, or droplets) in base fluids. In other words, nanofluids are nanoscale colloidal suspensions containing solid nanomaterials. They are two-phase systems with one phase (solid phase) in another (liquid phase). For a two-phase system, there are some important issues we have to face. One of the most important issues is the stability of nanofluids and it remains a big challenge to achieve desired stability of nanofluids. In this paper we will review the new progress in the methods for preparing stable nanofluids and summarize the stability mechanisms. In recent years, nanofluids have attracted more and more attention. The main driving force for nanofluids research lies in a wide range of applications. Although some review articles involving the progress of nanofluid investigation were published in the past several years [1-6], most of the reviews are concerned on the experimental and theoretical studies of the thermophysical properties or the convective heat transfer of nanofluids. The purpose of this paper will focuses on the new preparation methods and stability mechanisms, especially the new application trends for nanofluids in addition to the heat transfer properties of nanofluids. We will try to find some challenging issues that need to be solved for future research based on the review on these aspects of nanofluids.

## **2. Preparation methods for nanofluids**

## **2.1 Two-step method**

Two-step method is the most widely used method for preparing nanofluids. Nanoparticles, nanofibers, nanotubes or other nanomaterials used in this method are first produced as dry powders by chemical or physical methods. Then the nanosized powder will be dispersed into a fluid in the second processing step with the help of intensive magnetic force agitation, ultrasonic agitation, high-shear mixing, homogenizing and ball milling. Two-step method is the most economic method to produce nanofluids in large scale, because nanopowder synthesis techniques have already been scaled up to industrial production levels. Due to the high surface area and surface activity, nanoparticles have the tendency to aggregate. The important technique to enhance the stability of nanoparticles in fluids is the use of surfactants. However the functionality of the surfactants under high temperature is also a big concern, especially for high temperature applications.

Nanofluids 499

help of ultrasonic and microwave irradiation [14]. The precursor Cu(OH)2 is completely transformed to CuO nanoparticle in water under microwave irradiation. The ammonium citrate prevents the growth and aggregation of nanoparticles, resulting in a stable CuO aqueous nanofluid with higher thermal conductivity than those prepared by other dispersing methods. Phase-transfer method is also a facile way to obtain monodisperse noble metal colloids [15]. In a water-cyclohexane two-phase system, aqueous formaldehyde is transferred to cyclohexane phase via reaction with dodecylamine to form reductive intermediates in cyclohexane. The intermediates are capable of reducing silver or gold ions in aqueous solution to form dodecylamine protected silver and gold nanoparticles in cyclohexane solution at room temperature. Feng et al. used the aqueous-organic phasetransfer method for preparing gold, silver and platinum nanoparticles on the basis of the decrease of the PVP's solubility in water with the temperature increase [16]. Phase-transfer method is also applied for preparing stable kerosene based Fe3O4 nanofluids. Oleic acid is successfully grafted onto the surface of Fe3O4 nanoparticles by chemisorbed mode, which lets Fe3O4 nanoparticles have good compatibility with kerosene [17]. The Fe3O4 nanofluids prepared by phase-transfer method do not show the previously reported "time dependence of the thermal conductivity characteristic". The preparation of nanofluids with controllable microstructure is one of the key issues. It is well known that the properties of nanofluids strongly depend on the structure and shape of nanomaterials. The recent research shows that nanofluids synthesized by chemical solution method have both higher conductivity enhancement and better stability than those produced by the other methods [18]. This method is distinguished from the others by its controllability. The nanofluid microstructure can be varied and manipulated by adjusting synthesis parameters such as temperature, acidity, ultrasonic and microwave irradiation, types and concentrations of reactants and

additives, and the order in which the additives are added to the solution.

The agglomeration of nanoparticles results in not only the settlement and clogging of microchannels but also the decreasing of thermal conductivity of nanofluids. So the investigation on stability is also a key issue that influences the properties of nanofluids for application, and it is necessary to study and analyze influencing factors to the dispersion stability of nanofluids. This section will contain: A) the stability evaluation methods for nanofluids; B) the ways to enhance the stability of nanofluids and C) the stability

Many methods have been developed to evaluate the stability of nanofluids. The simplest method is sedimentation method [19, 20]. The sediment weight or the sediment volume of nanoparticles in a nanofluid under an external force field is an indication of the stability of the characterized nanofluid. The variation of concentration or particle size of supernatant particle with sediment time can be obtained by special apparatus [5]. The nanofluids are considered to be stable when the concentration or particle size of supernatant particles keeps constant. Sedimentation photograph of nanofluids in test tubes taken by a camera is also a usual method for observing the stability of nanofluids [5]. Zhu et al. used a sedimentation

**3. The stability of nanofluids** 

mechanisms of nanofluids.

**3.1 The stability evaluation methods for nanofluids 3.1.1 Sedimentation and centrifugation methods** 

Due to the difficulty in preparing stable nanofluids by two-step method, several advanced techniques are developed to produce nanofluids, including one-step method. In the following part, we will introduce one-step method in detail.

## **2.2 One-step method**

To reduce the agglomeration of nanoparticles, Choi et al. developed a one-step physical vapor condensation method to prepare Cu/ethylene glycol nanofluids [7]. The one-step process consists of simultaneously making and dispersing the particles in the fluid. In this method the processes of drying, storage, transportation, and dispersion of nanoparticles are avoided, so the agglomeration of nanoparticles is minimized and the stability of fluids is increased [5]. The one-step processes can prepare uniformly dispersed nanoparticles and the particles can be stably suspended in the base fluid. The vacuum-SANSS (submerged arc nanoparticle synthesis system) is another efficient method to prepare nanofluids using different dielectric liquids [8, 9]. The different morphologies are mainly influenced and determined by various thermal conductivity properties of the dielectric liquids. The nanoparticles prepared exhibit needle-like, polygonal, square and circular morphological shapes. The method avoids the undesired particle aggregation fair well.

One-step physical method cannot synthesize nanofluids in large scale and the cost is also high, so the one-step chemical method is developing rapidly. Zhu et al. presented a novel one-step chemical method for preparing copper nanofluids by reducing CuSO4. 5H2O with NaH2PO2 . H2O in ethylene glycol under microwave irradiation [10]. Well-dispersed and stably suspended copper nanofluids were obtained. Mineral oil-based nanofluids containing silver nanoparticles with a narrow size distribution were also prepared by this method [11]. The particles could be stabilized by Korantin, which coordinated to the silver particle surfaces via two oxygen atoms forming a dense layer around the particles. The silver nanoparticle suspensions were stable for about 1 month. Stable ethanol based nanofluids containing silver nanoparticles could be prepared by microwave-assisted one-step method [12]. In the method, polyvinylpyrrolidone (PVP) was employed as the stabilizer of colloidal silver and reducing agent for silver in solution. The cationic surfactant octadecylamine (ODA) is also an efficient phase-transfer agent to synthesize silver colloids [13]. The phase transfer of the silver nanoparticles arises due to coupling of the silver nanoparticles with the ODA molecules present in organic phase via either coordination bond formation or weak covalent interaction.

However there are some disadvantages for one-step method. The most important one is that the residual reactants are left in the nanofluids due to incomplete reaction or stabilization. It is difficult to elucidate the nanoparticle effect without eliminating this impurity effect.

#### **2.3 Other novel methods**

Wei et al. developed a continuous-flow microfluidic microreactor to synthesize copper nanofluids. By this method, copper nanofluids can be continuously synthesized, and their microstructure and properties can be varied by adjusting parameters such as reactant concentration, flow rate and additive. CuO nanofluids with high solid volume fraction (up to 10 vol%) can be synthesized through a novel precursor transformation method with the

Due to the difficulty in preparing stable nanofluids by two-step method, several advanced techniques are developed to produce nanofluids, including one-step method. In the

To reduce the agglomeration of nanoparticles, Choi et al. developed a one-step physical vapor condensation method to prepare Cu/ethylene glycol nanofluids [7]. The one-step process consists of simultaneously making and dispersing the particles in the fluid. In this method the processes of drying, storage, transportation, and dispersion of nanoparticles are avoided, so the agglomeration of nanoparticles is minimized and the stability of fluids is increased [5]. The one-step processes can prepare uniformly dispersed nanoparticles and the particles can be stably suspended in the base fluid. The vacuum-SANSS (submerged arc nanoparticle synthesis system) is another efficient method to prepare nanofluids using different dielectric liquids [8, 9]. The different morphologies are mainly influenced and determined by various thermal conductivity properties of the dielectric liquids. The nanoparticles prepared exhibit needle-like, polygonal, square and circular morphological

One-step physical method cannot synthesize nanofluids in large scale and the cost is also high, so the one-step chemical method is developing rapidly. Zhu et al. presented a novel

stably suspended copper nanofluids were obtained. Mineral oil-based nanofluids containing silver nanoparticles with a narrow size distribution were also prepared by this method [11]. The particles could be stabilized by Korantin, which coordinated to the silver particle surfaces via two oxygen atoms forming a dense layer around the particles. The silver nanoparticle suspensions were stable for about 1 month. Stable ethanol based nanofluids containing silver nanoparticles could be prepared by microwave-assisted one-step method [12]. In the method, polyvinylpyrrolidone (PVP) was employed as the stabilizer of colloidal silver and reducing agent for silver in solution. The cationic surfactant octadecylamine (ODA) is also an efficient phase-transfer agent to synthesize silver colloids [13]. The phase transfer of the silver nanoparticles arises due to coupling of the silver nanoparticles with the ODA molecules present in organic phase via either coordination bond formation or weak

However there are some disadvantages for one-step method. The most important one is that the residual reactants are left in the nanofluids due to incomplete reaction or stabilization. It is difficult to elucidate the nanoparticle effect without eliminating this

Wei et al. developed a continuous-flow microfluidic microreactor to synthesize copper nanofluids. By this method, copper nanofluids can be continuously synthesized, and their microstructure and properties can be varied by adjusting parameters such as reactant concentration, flow rate and additive. CuO nanofluids with high solid volume fraction (up to 10 vol%) can be synthesized through a novel precursor transformation method with the

H2O in ethylene glycol under microwave irradiation [10]. Well-dispersed and

5H2O with

following part, we will introduce one-step method in detail.

shapes. The method avoids the undesired particle aggregation fair well.

one-step chemical method for preparing copper nanofluids by reducing CuSO4.

**2.2 One-step method** 

NaH2PO2.

covalent interaction.

impurity effect.

**2.3 Other novel methods** 

help of ultrasonic and microwave irradiation [14]. The precursor Cu(OH)2 is completely transformed to CuO nanoparticle in water under microwave irradiation. The ammonium citrate prevents the growth and aggregation of nanoparticles, resulting in a stable CuO aqueous nanofluid with higher thermal conductivity than those prepared by other dispersing methods. Phase-transfer method is also a facile way to obtain monodisperse noble metal colloids [15]. In a water-cyclohexane two-phase system, aqueous formaldehyde is transferred to cyclohexane phase via reaction with dodecylamine to form reductive intermediates in cyclohexane. The intermediates are capable of reducing silver or gold ions in aqueous solution to form dodecylamine protected silver and gold nanoparticles in cyclohexane solution at room temperature. Feng et al. used the aqueous-organic phasetransfer method for preparing gold, silver and platinum nanoparticles on the basis of the decrease of the PVP's solubility in water with the temperature increase [16]. Phase-transfer method is also applied for preparing stable kerosene based Fe3O4 nanofluids. Oleic acid is successfully grafted onto the surface of Fe3O4 nanoparticles by chemisorbed mode, which lets Fe3O4 nanoparticles have good compatibility with kerosene [17]. The Fe3O4 nanofluids prepared by phase-transfer method do not show the previously reported "time dependence of the thermal conductivity characteristic". The preparation of nanofluids with controllable microstructure is one of the key issues. It is well known that the properties of nanofluids strongly depend on the structure and shape of nanomaterials. The recent research shows that nanofluids synthesized by chemical solution method have both higher conductivity enhancement and better stability than those produced by the other methods [18]. This method is distinguished from the others by its controllability. The nanofluid microstructure can be varied and manipulated by adjusting synthesis parameters such as temperature, acidity, ultrasonic and microwave irradiation, types and concentrations of reactants and additives, and the order in which the additives are added to the solution.

## **3. The stability of nanofluids**

The agglomeration of nanoparticles results in not only the settlement and clogging of microchannels but also the decreasing of thermal conductivity of nanofluids. So the investigation on stability is also a key issue that influences the properties of nanofluids for application, and it is necessary to study and analyze influencing factors to the dispersion stability of nanofluids. This section will contain: A) the stability evaluation methods for nanofluids; B) the ways to enhance the stability of nanofluids and C) the stability mechanisms of nanofluids.

#### **3.1 The stability evaluation methods for nanofluids**

## **3.1.1 Sedimentation and centrifugation methods**

Many methods have been developed to evaluate the stability of nanofluids. The simplest method is sedimentation method [19, 20]. The sediment weight or the sediment volume of nanoparticles in a nanofluid under an external force field is an indication of the stability of the characterized nanofluid. The variation of concentration or particle size of supernatant particle with sediment time can be obtained by special apparatus [5]. The nanofluids are considered to be stable when the concentration or particle size of supernatant particles keeps constant. Sedimentation photograph of nanofluids in test tubes taken by a camera is also a usual method for observing the stability of nanofluids [5]. Zhu et al. used a sedimentation

Nanofluids 501

spectrophotometer analysis [28]. The sedimentation kinetics could also be determined by

If the nanomaterials dispersed in fluids have characteristic absorption bands in the wavelength 190-1100 nm, it is an easy and reliable method to evaluate the stability of nanofluids using UV-vis spectral analysis. The variation of supernatant particle concentration of nanofluids with sediment time can be obtained by the measurement of absorption of nanofluids because there is a linear relation between the supernatant nanoparticle concentration and the absorbance of suspended particles. The outstanding advantage comparing to other methods is that UV-vis spectral analysis can present the quantitative concentration of nanofluids. Hwang et al. [29] studied the stability of nanofluids with the UV-vis spectrophotometer. It was believed that the stability of nanofluids was strongly affected by the characteristics of the suspended particles and the base fluid such as particle morphology. Moreover, addition of a surfactant could improve the stability of the suspensions. The relative stability of MWNT nanofluids [26] could be estimated by measuring the UV-vis absorption of the MWNT nanofluids at different sediment times. From the above relation between MWNT concentration and its UV-vis absorbance value the concentration of the MWNT nanofluids at different sediment times could be obtained. The above three methods can be united to investigate the stability of nanofluids. For example, Li et al. evaluated the dispersion behavior of the aqueous copper nano-suspensions under different pH values, different dispersant type and concentration by

the method of zeta potential, absorbency and sedimentation photographs [20].

Surfactants used in nanofluids are also called dispersants. Adding dispersants in the twophase systems is an easy and economic method to enhance the stability of nanofluids. Dispersants can markedly affect the surface characteristics of a system in small quantity. Dispersants consists of a hydrophobic tail portion, usually a long-chain hydrocarbon, and a hydrophilic polar head group. Dispersants are employed to increase the contact of two materials, sometimes known as wettability. In a two-phase system, a dispersant tends to locate at the interface of the two phases, where it introduces a degree of continuity between the nanoparticles and fluids. According to the composition of the head, surfactants are divided into four classes: non-ionic surfactants without charge groups in its head (include polyethylene oxide, alcohols, and other polar groups); anionic surfactants with negatively charged head groups (anionic head groups include long-chain fatty acids, sulfosuccinates, alkyl sulfates, phosphates, and sulfonates); cationic surfactants with positively charged head groups (cationic surfactants may be protonated long-chain amines and long-chain quaternary ammonium compounds); and amphoteric surfactants with zwitterionic head groups (charge depends on pH. The class of amphoteric surfactants is represented by betaines and certain lecithins). How to select suitable dispersants is a key issue. In general, when the base fluid of nanofluids is polar solvent, we should select water soluble surfactants, otherwise we will select oil soluble. For nonionic surfactants, we can evaluate the solubility through the term hydrophilic/lipophilic balance (HLB) value. The lower the HLB number the more oil soluble the surfactants, and in turn the higher the HLB number the more water-soluble the surfactants

**3.2 The ways to enhance the stability of nanofluids** 

is. The HLB value can be obtained easily by many handbooks.

**3.2.1 Surfactants used in nanofluids** 

examining the absorbency of particle in solution [25].

balance method to measure the stability of the graphite suspension [21]. The tray of sedimentation balance immerged in the fresh graphite suspension. The weight of sediment nanoparticles during a certain period was measured. The suspension fraction of graphite nanoparticles at a certain time could be calculated. For the sedimentation method, long period for observation is the defect. Therefore centrifugation method is developed to evaluate the stability of nanofluids. Singh et al. applied the centrifugation method to observe the stability of silver nanofluids prepared by the microwave synthesis in ethanol by reduction of AgNO3 with PVP as stabilizing agent [12]. It has been found that the obtained nanofluids are stable for more than 1 month in the stationary state and more than 10 h under centrifugation at 3,000 rpm without sedimentation. Excellent stability of the obtained nanofluid is due to the protective role of PVP as it retards the growth and agglomeration of nanoparticles by steric effect. Li et al. prepared the aqueous polyaniline colloids, and used the centrifugation method to evaluate the stability of the colloids [22]. Electrostatic repulsive forces between nanofibers enabled the long-term stability of the colloids.

### **3.1.2 Zeta potential analysis**

Zeta potential is electric potential in the interfacial double layer at the location of the slipping plane versus a point in the bulk fluid away from the interface, and it shows the potential difference between the dispersion medium and the stationary layer of fluid attached to the dispersed particle. The significance of zeta potential is that its value can be related to the stability of colloidal dispersions. So, colloids with high zeta potential (negative or positive) are electrically stabilized while colloids with low zeta potentials tend to coagulate or flocculate. In general, a value of 25 mV (positive or negative) can be taken as the arbitrary value that separates low-charged surfaces from highly-charged surfaces. The colloids with zeta potential from 40 to 60 mV are believed to be good stable, and those with more than 60 mV have excellent stability. Kim et al. prepared Au nanofluids with an outstanding stability even after 1 month although no dispersants were observed [23]. The stability is due to a large negative zeta potential of Au nanoparticles in water. The influence of pH and sodium dodecylbenzene sulfonate (SDBS) on the stability of two water-based nanofluids was studied [24], and zeta potential analysis was an important technique to evaluate the stability. Zhu et al. [25] measured the zeta potential of Al2O3-H2O nanofluids under different pH values and different SDBS concentration. The Derjaguin-Laudau-Verwey-Overbeek (DLVO) theory was used to calculate attractive and repulsive potentials. Cationic gemini surfactant as stabilizer was used to prepare stable water based nanofluids containing MWNTs [26]. Zeta potential measurements were employed to study the absorption mechanisms of the surfactants on the MWNT surfaces with the help of Fourier transformation infrared spectra.

#### **3.1.3 Spectral absorbency analysis**

Spectral absorbency analysis is another efficient way to evaluate the stability of nanofluids. In general, there is a linear relationship between the absorbency intensity and the concentration of nanoparticles in fluid. Huang et al. evaluated the dispersion characteristics of alumina and copper suspensions using the conventional sedimentation method with the help of absorbency analysis by using a spectrophotometer after the suspensions deposited for 24 h [27]. The stability investigation of colloidal FePt nanoparticle systems was done via

balance method to measure the stability of the graphite suspension [21]. The tray of sedimentation balance immerged in the fresh graphite suspension. The weight of sediment nanoparticles during a certain period was measured. The suspension fraction of graphite nanoparticles at a certain time could be calculated. For the sedimentation method, long period for observation is the defect. Therefore centrifugation method is developed to evaluate the stability of nanofluids. Singh et al. applied the centrifugation method to observe the stability of silver nanofluids prepared by the microwave synthesis in ethanol by reduction of AgNO3 with PVP as stabilizing agent [12]. It has been found that the obtained nanofluids are stable for more than 1 month in the stationary state and more than 10 h under centrifugation at 3,000 rpm without sedimentation. Excellent stability of the obtained nanofluid is due to the protective role of PVP as it retards the growth and agglomeration of nanoparticles by steric effect. Li et al. prepared the aqueous polyaniline colloids, and used the centrifugation method to evaluate the stability of the colloids [22]. Electrostatic repulsive

Zeta potential is electric potential in the interfacial double layer at the location of the slipping plane versus a point in the bulk fluid away from the interface, and it shows the potential difference between the dispersion medium and the stationary layer of fluid attached to the dispersed particle. The significance of zeta potential is that its value can be related to the stability of colloidal dispersions. So, colloids with high zeta potential (negative or positive) are electrically stabilized while colloids with low zeta potentials tend to coagulate or flocculate. In general, a value of 25 mV (positive or negative) can be taken as the arbitrary value that separates low-charged surfaces from highly-charged surfaces. The colloids with zeta potential from 40 to 60 mV are believed to be good stable, and those with more than 60 mV have excellent stability. Kim et al. prepared Au nanofluids with an outstanding stability even after 1 month although no dispersants were observed [23]. The stability is due to a large negative zeta potential of Au nanoparticles in water. The influence of pH and sodium dodecylbenzene sulfonate (SDBS) on the stability of two water-based nanofluids was studied [24], and zeta potential analysis was an important technique to evaluate the stability. Zhu et al. [25] measured the zeta potential of Al2O3-H2O nanofluids under different pH values and different SDBS concentration. The Derjaguin-Laudau-Verwey-Overbeek (DLVO) theory was used to calculate attractive and repulsive potentials. Cationic gemini surfactant as stabilizer was used to prepare stable water based nanofluids containing MWNTs [26]. Zeta potential measurements were employed to study the absorption mechanisms of the surfactants on the MWNT surfaces with the help of Fourier

Spectral absorbency analysis is another efficient way to evaluate the stability of nanofluids. In general, there is a linear relationship between the absorbency intensity and the concentration of nanoparticles in fluid. Huang et al. evaluated the dispersion characteristics of alumina and copper suspensions using the conventional sedimentation method with the help of absorbency analysis by using a spectrophotometer after the suspensions deposited for 24 h [27]. The stability investigation of colloidal FePt nanoparticle systems was done via

forces between nanofibers enabled the long-term stability of the colloids.

**3.1.2 Zeta potential analysis** 

transformation infrared spectra.

**3.1.3 Spectral absorbency analysis** 

spectrophotometer analysis [28]. The sedimentation kinetics could also be determined by examining the absorbency of particle in solution [25].

If the nanomaterials dispersed in fluids have characteristic absorption bands in the wavelength 190-1100 nm, it is an easy and reliable method to evaluate the stability of nanofluids using UV-vis spectral analysis. The variation of supernatant particle concentration of nanofluids with sediment time can be obtained by the measurement of absorption of nanofluids because there is a linear relation between the supernatant nanoparticle concentration and the absorbance of suspended particles. The outstanding advantage comparing to other methods is that UV-vis spectral analysis can present the quantitative concentration of nanofluids. Hwang et al. [29] studied the stability of nanofluids with the UV-vis spectrophotometer. It was believed that the stability of nanofluids was strongly affected by the characteristics of the suspended particles and the base fluid such as particle morphology. Moreover, addition of a surfactant could improve the stability of the suspensions. The relative stability of MWNT nanofluids [26] could be estimated by measuring the UV-vis absorption of the MWNT nanofluids at different sediment times. From the above relation between MWNT concentration and its UV-vis absorbance value the concentration of the MWNT nanofluids at different sediment times could be obtained. The above three methods can be united to investigate the stability of nanofluids. For example, Li et al. evaluated the dispersion behavior of the aqueous copper nano-suspensions under different pH values, different dispersant type and concentration by the method of zeta potential, absorbency and sedimentation photographs [20].

## **3.2 The ways to enhance the stability of nanofluids**

### **3.2.1 Surfactants used in nanofluids**

Surfactants used in nanofluids are also called dispersants. Adding dispersants in the twophase systems is an easy and economic method to enhance the stability of nanofluids. Dispersants can markedly affect the surface characteristics of a system in small quantity. Dispersants consists of a hydrophobic tail portion, usually a long-chain hydrocarbon, and a hydrophilic polar head group. Dispersants are employed to increase the contact of two materials, sometimes known as wettability. In a two-phase system, a dispersant tends to locate at the interface of the two phases, where it introduces a degree of continuity between the nanoparticles and fluids. According to the composition of the head, surfactants are divided into four classes: non-ionic surfactants without charge groups in its head (include polyethylene oxide, alcohols, and other polar groups); anionic surfactants with negatively charged head groups (anionic head groups include long-chain fatty acids, sulfosuccinates, alkyl sulfates, phosphates, and sulfonates); cationic surfactants with positively charged head groups (cationic surfactants may be protonated long-chain amines and long-chain quaternary ammonium compounds); and amphoteric surfactants with zwitterionic head groups (charge depends on pH. The class of amphoteric surfactants is represented by betaines and certain lecithins). How to select suitable dispersants is a key issue. In general, when the base fluid of nanofluids is polar solvent, we should select water soluble surfactants, otherwise we will select oil soluble. For nonionic surfactants, we can evaluate the solubility through the term hydrophilic/lipophilic balance (HLB) value. The lower the HLB number the more oil soluble the surfactants, and in turn the higher the HLB number the more water-soluble the surfactants is. The HLB value can be obtained easily by many handbooks.

Nanofluids 503

suspension is not stable. If the particles have a sufficient high repulsion, the suspensions will exist in stable state. For stable nanofluids or colloids, the repulsive forces between particles must be dominant. According to the types of repulsion, the fundamental mechanisms that affect colloidal stability are divided into two kinds, one is steric repulsion, and another is electrostatic (charge) repulsion. For steric stabilization, polymers are always involved into the suspension system, and they will adsorb onto the particles surface, producing an additional steric repulsive force. For example, Zinc oxide nanoparticles modified by PMAA have good compatibility with polar solvents [35]. Silver nanofluids are very stable due to the protective role of PVP as it retards the growth and agglomeration of nanoparticles by steric effect. PVP is an efficient agent to improve the stability of graphite suspension [21]. The steric effect of polymer dispersant is determined by the concentration of the dispersant. If the PVP concentration is low, the surface of the graphite particles is gradually coated by PVP molecules with the increase of PVP. Kamiya et al. studied the effect of polymer dispersant structure on electrosteric interaction and dense alumina suspension behavior [38]. An optimum hydrophilic to hydrophobic group ratio was obtained from the maximum repulsive force and minimum viscosity. For electrostatic stabilization, surface charge will be developed through one or more of the following mechanisms: 1) preferential adsorption of ions; 2) dissociation of surface charged species; 3) isomorphic substitution of ions; 4) accumulation or depletion of electrons at the surface and 5) physical adsorption of charged

Since the origination of the nanofluid concept about a decade ago, the potentials of nanofluids in heat transfer applications have attracted more and more attention. Up to now, there are some review papers, which present overviews of various aspects of nanofluids [1, 3-6, 39-44], including preparation and characterization, techniques for the measurements of thermal conductivity, theory and model, thermophysical properties, convective heat transfer. In this part, we will summarize the applications of nanofluids in heat transfer

Due to higher density of chips, design of electronic components with more compact makes heat dissipation more difficult. Advanced electronic devices face thermal management challenges from the high level of heat generation and the reduction of available surface area for heat removal. So, the reliable thermal management system is vital for the smooth operation of the advanced electronic devices. In general, there are two approaches to improve the heat removal for electronic equipment. One is to find an optimum geometry of cooling devices; another is to increase the heat transfer capacity. Recent researches illustrated that nanofluids could increase the heat transfer coefficient by increasing the thermal conductivity of a coolant. Jang et al. designed a new cooler, combined microchannel heat sink with nanofluids [45]. Higher cooling performance was obtained when compared to the device using pure water as working medium. Nanofluids reduced both the thermal resistance and the temperature difference between the heated microchannel wall and the coolant. A combined microchannel heat sink with nanofluids had the potential as the next

species onto the surface.

enhancement.

**4. Application of nanofluids 4.1 Heat transfer Intensification** 

**4.1.1 Electronic applications** 

#### **3.2.2 Surface modification techniques-surfactant free method**

Although surfactant addition is an effective way to enhance the dispersibility of nanoparticles, surfactants might cause several problems [30]. For example, the addition of surfactants may contaminate the heat transfer media. Surfactants may produce foams when heating, while heating and cooling are routinely processes in heat exchange systems. Furthermore surfactant molecules attaching on the surfaces of nanoparticles may enlarge the thermal resistance between the nanoparticles and the base fluid, which may limit the enhancement of the effective thermal conductivity. Use of functionalized nanoparticles is a promising approach to achieve long-term stability of nanofluid. It represents the surfactant free technique. Yang et al. presented a work on the synthesis of functionalized silica (SiO2) nanoparticles by grafting silanes directly to the surface of silica nanoparticles in original nanoparticle solutions [31]. One of the unique characteristics of the nanofluids was that no deposition layer formed on the heated surface after a pool boiling process. Chen *et al*. introduced hydrophilic functional groups on the surface of the nanotubes by mechanochemical reaction [29]. The prepared nanofluids, with no contamination to medium, good fluidity, low viscosity, high stability, and high thermal conductivity, would have potential applications as coolants in advanced thermal systems. A wetmechanochemical reaction was applied to prepare surfactant-free nanofluids containing double- and single-walled CNTs. Results from the infrared spectrum and zeta potential measurements showed that the hydroxyl groups had been introduced onto the treated CNT surfaces [32]. Plasma treatment was used to modify the surface characteristics of diamond nanoparticles [33]. Through plasma treatment using gas mixtures of methane and oxygen, various polar groups were imparted on the surface of the diamond nanoparticles, improving their dispersion property in water. A stable dispersion of titania nanoparticles in an organic solvent of diethylene glycol dimethylether (diglyme) was successfully prepared using a ball milling process [34]. In order to enhance dispersion stability of the solution, surface modification of dispersed titania particles was carried out during the centrifugal bead mill process. Surface modification was utilized with silane coupling agents, (3-acryloxypropyl) trimethoxysilane and trimethoxypropylsilane. Zinc oxide nanoparticles could be modified by polymethacrylic acid (PMAA) in aqueous system [35]. The hydroxyl groups of nano-ZnO particle surface could interact with carboxyl groups of PMAA and form poly (zinc methacrylate) complex on the surface of nano-ZnO. PMAA enhanced the dispersibility of nano-ZnO particles in water. The modification did not alter the crystalline structure of the ZnO nanoparticles.

#### **3.3 Stability mechanisms of nanofluids**

Particles in dispersion may adhere together and form aggregates of increasing size which may settle out due to gravity. Stability means that the particles do not aggregate at a significant rate. The rate of aggregation is in general determined by the frequency of collisions and the probability of cohesion during collision. Derjaguin, Verway, Landau and Overbeek (DVLO) developed a theory which dealt with colloidal stability [36, 37]. DLVO theory suggests that the stability of a particle in solution is determined by the sum of van der Waals attractive and electrical double layer repulsive forces that exist between particles as they approach each other due to the Brownian motion they are undergoing. If the attractive force is larger than the repulsive force, the two particles will collide, and the

Although surfactant addition is an effective way to enhance the dispersibility of nanoparticles, surfactants might cause several problems [30]. For example, the addition of surfactants may contaminate the heat transfer media. Surfactants may produce foams when heating, while heating and cooling are routinely processes in heat exchange systems. Furthermore surfactant molecules attaching on the surfaces of nanoparticles may enlarge the thermal resistance between the nanoparticles and the base fluid, which may limit the enhancement of the effective thermal conductivity. Use of functionalized nanoparticles is a promising approach to achieve long-term stability of nanofluid. It represents the surfactant free technique. Yang et al. presented a work on the synthesis of functionalized silica (SiO2) nanoparticles by grafting silanes directly to the surface of silica nanoparticles in original nanoparticle solutions [31]. One of the unique characteristics of the nanofluids was that no deposition layer formed on the heated surface after a pool boiling process. Chen *et al*. introduced hydrophilic functional groups on the surface of the nanotubes by mechanochemical reaction [29]. The prepared nanofluids, with no contamination to medium, good fluidity, low viscosity, high stability, and high thermal conductivity, would have potential applications as coolants in advanced thermal systems. A wetmechanochemical reaction was applied to prepare surfactant-free nanofluids containing double- and single-walled CNTs. Results from the infrared spectrum and zeta potential measurements showed that the hydroxyl groups had been introduced onto the treated CNT surfaces [32]. Plasma treatment was used to modify the surface characteristics of diamond nanoparticles [33]. Through plasma treatment using gas mixtures of methane and oxygen, various polar groups were imparted on the surface of the diamond nanoparticles, improving their dispersion property in water. A stable dispersion of titania nanoparticles in an organic solvent of diethylene glycol dimethylether (diglyme) was successfully prepared using a ball milling process [34]. In order to enhance dispersion stability of the solution, surface modification of dispersed titania particles was carried out during the centrifugal bead mill process. Surface modification was utilized with silane coupling agents, (3-acryloxypropyl) trimethoxysilane and trimethoxypropylsilane. Zinc oxide nanoparticles could be modified by polymethacrylic acid (PMAA) in aqueous system [35]. The hydroxyl groups of nano-ZnO particle surface could interact with carboxyl groups of PMAA and form poly (zinc methacrylate) complex on the surface of nano-ZnO. PMAA enhanced the dispersibility of nano-ZnO particles in water. The modification did not alter the crystalline structure of the

Particles in dispersion may adhere together and form aggregates of increasing size which may settle out due to gravity. Stability means that the particles do not aggregate at a significant rate. The rate of aggregation is in general determined by the frequency of collisions and the probability of cohesion during collision. Derjaguin, Verway, Landau and Overbeek (DVLO) developed a theory which dealt with colloidal stability [36, 37]. DLVO theory suggests that the stability of a particle in solution is determined by the sum of van der Waals attractive and electrical double layer repulsive forces that exist between particles as they approach each other due to the Brownian motion they are undergoing. If the attractive force is larger than the repulsive force, the two particles will collide, and the

**3.2.2 Surface modification techniques-surfactant free method** 

ZnO nanoparticles.

**3.3 Stability mechanisms of nanofluids** 

suspension is not stable. If the particles have a sufficient high repulsion, the suspensions will exist in stable state. For stable nanofluids or colloids, the repulsive forces between particles must be dominant. According to the types of repulsion, the fundamental mechanisms that affect colloidal stability are divided into two kinds, one is steric repulsion, and another is electrostatic (charge) repulsion. For steric stabilization, polymers are always involved into the suspension system, and they will adsorb onto the particles surface, producing an additional steric repulsive force. For example, Zinc oxide nanoparticles modified by PMAA have good compatibility with polar solvents [35]. Silver nanofluids are very stable due to the protective role of PVP as it retards the growth and agglomeration of nanoparticles by steric effect. PVP is an efficient agent to improve the stability of graphite suspension [21]. The steric effect of polymer dispersant is determined by the concentration of the dispersant. If the PVP concentration is low, the surface of the graphite particles is gradually coated by PVP molecules with the increase of PVP. Kamiya et al. studied the effect of polymer dispersant structure on electrosteric interaction and dense alumina suspension behavior [38]. An optimum hydrophilic to hydrophobic group ratio was obtained from the maximum repulsive force and minimum viscosity. For electrostatic stabilization, surface charge will be developed through one or more of the following mechanisms: 1) preferential adsorption of ions; 2) dissociation of surface charged species; 3) isomorphic substitution of ions; 4) accumulation or depletion of electrons at the surface and 5) physical adsorption of charged species onto the surface.

## **4. Application of nanofluids**

#### **4.1 Heat transfer Intensification**

Since the origination of the nanofluid concept about a decade ago, the potentials of nanofluids in heat transfer applications have attracted more and more attention. Up to now, there are some review papers, which present overviews of various aspects of nanofluids [1, 3-6, 39-44], including preparation and characterization, techniques for the measurements of thermal conductivity, theory and model, thermophysical properties, convective heat transfer. In this part, we will summarize the applications of nanofluids in heat transfer enhancement.

#### **4.1.1 Electronic applications**

Due to higher density of chips, design of electronic components with more compact makes heat dissipation more difficult. Advanced electronic devices face thermal management challenges from the high level of heat generation and the reduction of available surface area for heat removal. So, the reliable thermal management system is vital for the smooth operation of the advanced electronic devices. In general, there are two approaches to improve the heat removal for electronic equipment. One is to find an optimum geometry of cooling devices; another is to increase the heat transfer capacity. Recent researches illustrated that nanofluids could increase the heat transfer coefficient by increasing the thermal conductivity of a coolant. Jang et al. designed a new cooler, combined microchannel heat sink with nanofluids [45]. Higher cooling performance was obtained when compared to the device using pure water as working medium. Nanofluids reduced both the thermal resistance and the temperature difference between the heated microchannel wall and the coolant. A combined microchannel heat sink with nanofluids had the potential as the next

Nanofluids 505

Nanofluids have great potentials to improve automotive and heavy-duty engine cooling rates by increasing the efficiency, lowering the weight and reducing the complexity of thermal management systems. The improved cooling rates for automotive and truck engines can be used to remove more heat from higher horsepower engines with the same size of cooling system. Alternatively, it is beneficial to design more compact cooling system with smaller and lighter radiators. It is in turn benefit the high performance and high fuel economy of car and truck. Ethylene glycol based nanofluids have attracted much attention in the application as engine coolant [53-55], due to the low-pressure operation compared with a 50/50 mixture of ethylene glycol and water, which is the nearly universally used automotive coolant. The nanofluids has a high boiling point, and it can be used to increase the normal coolant operating temperature and then reject more heat through the existing coolant system [56]. Kole et al. prepared car engine coolant (Al2O3 nanofluid) using a standard car engine coolant (HP KOOLGARD) as the base fluid [57], and studied the thermal conductivity and viscosity of the coolant. The prepared nanofluid, containing only 3.5% volume fraction of Al2O3 nanoparticles, displayed a fairly higher thermal conductivity than the base fluid, and a maximum enhancement of 10.41% was observed at room temperature. Tzeng et al. [58] applied nanofluids to the cooling of automatic transmissions. The experimental platform was the transmission of a four-wheel drive vehicle. The used nanofluids were prepared by dispersing CuO and Al2O3 nanoparticles into engine transmission oil. The results showed that CuO nanofluids produced the lower transmission temperatures both at high and low rotating speeds. From the thermal performance

viewpoint, the use of nanofluid in the transmission has a clear advantage.

The researchers of Argonne National Laboratory have assessed the applications of nanofluids for transportation [59]. The use of high-thermal conductive nanofluids in radiators can lead to a reduction in the frontal area of the radiator up to 10%. The fuel saving is up to 5% due to the reduction in aerodynamic drag. It opens the door for new aerodynamic automotive designs that reduce emissions by lowering drag. The application of nanofluids also contributed to a reduction of friction and wear, reducing parasitic losses, operation of components such as pumps and compressors, and subsequently leading to more than 6% fuel savings. In fact, nanofluids not only enhance the efficiency and economic performance of car engine, but also will greatly influence the structure design of automotives. For example, the engine radiator cooled by a nanofluid will be smaller and lighter. It can be placed elsewhere in the vehicle, allowing for the redesign of a far more aerodynamic chassis. By reducing the size and changing the location of the radiator, a reduction in weight and wind resistance could enable greater fuel efficiency and subsequently lower exhaust emissions. Computer simulations from the US department of energy's office of vehicle technology showed that nanofluid coolants could reduce the size

of truck radiators by 5%. This would result in a 2.5% fuel saving at highway speeds.

The practical applications are on the road. In USA, car manufacturers GM and Ford are running their own research programs on nanofluid applications. A €8.3 million FP7 project, named NanoHex (Nanofluid Heat Exchange), began to run. It involved 12 organizations from Europe and Israel ranging from Universities to SME's and major companies. NanoHex is overcoming the technological challenges faced in development and application of reliable and safe nanofluids for more sophisticated, energy efficient, and environmentally friendly

**4.1.2 Transportation** 

products and services [60].

generation cooling devices for removing ultra-high heat flux. Nguyen et al. designed a closed liquid-circuit to investigate the heat transfer enhancement of a liquid cooling system, by replacing the base fluid (distilled water) with a nanofluid composed of distilled water and Al2O3 nanoparticles at various concentrations [46]. Measured data have clearly shown that the inclusion of nanoparticles within the distilled water has produced a considerable enhancement in convective heat transfer coefficient of the cooling block. With particle loading 4.5 vol%, the enhancement is up to 23% with respect to that of the base fluid. It has also been observed that an augmentation of particle concentration has produced a clear decrease of the junction temperature between the heated component and the cooling block. Silicon microchannel heat sink performance using nanofluids containing Cu nanoparticles was analyzed [47]. It was found nanofluids could enhance the performance as compared with that using pure water as the coolant. The enhancement was due to the increase in thermal conductivity of coolant and the nanoparticle thermal dispersion effect. The other advantage was that there was no extra pressure drop since the nanoparticle was small and particle volume fraction was low.

The thermal requirements on the personal computer become much stricter with the increase in thermal dissipation of CPU. One of the solutions is the use of heat pipes. Nanofluids, employed as working medium for conventional heat pipe, have shown higher thermal performances, having the potential as a substitute for conventional water in heat pipe. At a same charge volume, there is a significant reduction in thermal resistance of heat pipe with nanofluid containing gold nanoparticles as compared with water [48]. The measured results also show that the thermal resistance of a vertical meshed heat pipe varies with the size of gold nanoparticles. The suspended nanoparticles tend to bombard the vapor bubble during the bubble formation. Therefore, it is expected that the nucleation size of vapor bubble is much smaller for fluid with suspended nanoparticles than that without them. This may be the major reason for reducing the thermal resistance of heat pipe. Chen et al. studied the effect of a nanofluid on flat heat pipe (FHP) thermal performance [49], using silver nanofluid as the working fluid. The temperature difference and the thermal resistance of the FHP with the silver nanoparticle solution were lower than those with pure water. The plausible reasons for enhancement of the thermal performance of the FHP using the nanofluid can be explained by the critical heat flux enhancement by higher wettability and the reduction of the boiling limit. Nanofluid oscillating heat pipe with ultrahighperformance was developed by Ma et al. [50]. They combined nanofluids with thermally excited oscillating motion in an oscillating heat pipe, and heat transport capability significantly increased. For example, at the input power of 80.0 W, diamond nanofluid could reduce the temperature difference between the evaporator and the condenser from 40.9 to 24.3°C. This study would accelerate the development of a highly efficient cooling device for ultrahigh-heat-flux electronic systems. The thermal performance investigation of heat pipe indicated that nanofluids containing silver or titanium nanoparticles could be used as an efficient cooling fluid for devices with high energy density. For a silver nanofluid, the temperature difference decreased 0.56-0.65℃ compared to water at an input power of 30-50 W [51]. For the heat pipe with titanium nanoparticles at a volume concentration of 0.10%, the thermal efficiency is 10.60% higher than that with the based working fluid [52]. These positive results are promoting the continued research and development of nanofluids for such applications.

generation cooling devices for removing ultra-high heat flux. Nguyen et al. designed a closed liquid-circuit to investigate the heat transfer enhancement of a liquid cooling system, by replacing the base fluid (distilled water) with a nanofluid composed of distilled water and Al2O3 nanoparticles at various concentrations [46]. Measured data have clearly shown that the inclusion of nanoparticles within the distilled water has produced a considerable enhancement in convective heat transfer coefficient of the cooling block. With particle loading 4.5 vol%, the enhancement is up to 23% with respect to that of the base fluid. It has also been observed that an augmentation of particle concentration has produced a clear decrease of the junction temperature between the heated component and the cooling block. Silicon microchannel heat sink performance using nanofluids containing Cu nanoparticles was analyzed [47]. It was found nanofluids could enhance the performance as compared with that using pure water as the coolant. The enhancement was due to the increase in thermal conductivity of coolant and the nanoparticle thermal dispersion effect. The other advantage was that there was no extra pressure drop since the nanoparticle was small and

The thermal requirements on the personal computer become much stricter with the increase in thermal dissipation of CPU. One of the solutions is the use of heat pipes. Nanofluids, employed as working medium for conventional heat pipe, have shown higher thermal performances, having the potential as a substitute for conventional water in heat pipe. At a same charge volume, there is a significant reduction in thermal resistance of heat pipe with nanofluid containing gold nanoparticles as compared with water [48]. The measured results also show that the thermal resistance of a vertical meshed heat pipe varies with the size of gold nanoparticles. The suspended nanoparticles tend to bombard the vapor bubble during the bubble formation. Therefore, it is expected that the nucleation size of vapor bubble is much smaller for fluid with suspended nanoparticles than that without them. This may be the major reason for reducing the thermal resistance of heat pipe. Chen et al. studied the effect of a nanofluid on flat heat pipe (FHP) thermal performance [49], using silver nanofluid as the working fluid. The temperature difference and the thermal resistance of the FHP with the silver nanoparticle solution were lower than those with pure water. The plausible reasons for enhancement of the thermal performance of the FHP using the nanofluid can be explained by the critical heat flux enhancement by higher wettability and the reduction of the boiling limit. Nanofluid oscillating heat pipe with ultrahighperformance was developed by Ma et al. [50]. They combined nanofluids with thermally excited oscillating motion in an oscillating heat pipe, and heat transport capability significantly increased. For example, at the input power of 80.0 W, diamond nanofluid could reduce the temperature difference between the evaporator and the condenser from 40.9 to 24.3°C. This study would accelerate the development of a highly efficient cooling device for ultrahigh-heat-flux electronic systems. The thermal performance investigation of heat pipe indicated that nanofluids containing silver or titanium nanoparticles could be used as an efficient cooling fluid for devices with high energy density. For a silver nanofluid, the temperature difference decreased 0.56-0.65℃ compared to water at an input power of 30-50 W [51]. For the heat pipe with titanium nanoparticles at a volume concentration of 0.10%, the thermal efficiency is 10.60% higher than that with the based working fluid [52]. These positive results are promoting the continued research and development of nanofluids for

particle volume fraction was low.

such applications.

## **4.1.2 Transportation**

Nanofluids 505

Nanofluids have great potentials to improve automotive and heavy-duty engine cooling rates by increasing the efficiency, lowering the weight and reducing the complexity of thermal management systems. The improved cooling rates for automotive and truck engines can be used to remove more heat from higher horsepower engines with the same size of cooling system. Alternatively, it is beneficial to design more compact cooling system with smaller and lighter radiators. It is in turn benefit the high performance and high fuel economy of car and truck. Ethylene glycol based nanofluids have attracted much attention in the application as engine coolant [53-55], due to the low-pressure operation compared with a 50/50 mixture of ethylene glycol and water, which is the nearly universally used automotive coolant. The nanofluids has a high boiling point, and it can be used to increase the normal coolant operating temperature and then reject more heat through the existing coolant system [56]. Kole et al. prepared car engine coolant (Al2O3 nanofluid) using a standard car engine coolant (HP KOOLGARD) as the base fluid [57], and studied the thermal conductivity and viscosity of the coolant. The prepared nanofluid, containing only 3.5% volume fraction of Al2O3 nanoparticles, displayed a fairly higher thermal conductivity than the base fluid, and a maximum enhancement of 10.41% was observed at room temperature. Tzeng et al. [58] applied nanofluids to the cooling of automatic transmissions. The experimental platform was the transmission of a four-wheel drive vehicle. The used nanofluids were prepared by dispersing CuO and Al2O3 nanoparticles into engine transmission oil. The results showed that CuO nanofluids produced the lower transmission temperatures both at high and low rotating speeds. From the thermal performance viewpoint, the use of nanofluid in the transmission has a clear advantage.

The researchers of Argonne National Laboratory have assessed the applications of nanofluids for transportation [59]. The use of high-thermal conductive nanofluids in radiators can lead to a reduction in the frontal area of the radiator up to 10%. The fuel saving is up to 5% due to the reduction in aerodynamic drag. It opens the door for new aerodynamic automotive designs that reduce emissions by lowering drag. The application of nanofluids also contributed to a reduction of friction and wear, reducing parasitic losses, operation of components such as pumps and compressors, and subsequently leading to more than 6% fuel savings. In fact, nanofluids not only enhance the efficiency and economic performance of car engine, but also will greatly influence the structure design of automotives. For example, the engine radiator cooled by a nanofluid will be smaller and lighter. It can be placed elsewhere in the vehicle, allowing for the redesign of a far more aerodynamic chassis. By reducing the size and changing the location of the radiator, a reduction in weight and wind resistance could enable greater fuel efficiency and subsequently lower exhaust emissions. Computer simulations from the US department of energy's office of vehicle technology showed that nanofluid coolants could reduce the size of truck radiators by 5%. This would result in a 2.5% fuel saving at highway speeds.

The practical applications are on the road. In USA, car manufacturers GM and Ford are running their own research programs on nanofluid applications. A €8.3 million FP7 project, named NanoHex (Nanofluid Heat Exchange), began to run. It involved 12 organizations from Europe and Israel ranging from Universities to SME's and major companies. NanoHex is overcoming the technological challenges faced in development and application of reliable and safe nanofluids for more sophisticated, energy efficient, and environmentally friendly products and services [60].

Nanofluids 507

reducing the margin to CHF; 2) coolant for the emergency core cooling systems (ECCSs) of both PWRs and boiling water reactors. The use of a nanofluid in the ECCS accumulators and safety injection can increase the peak-cladding-temperature margins (in the nominal-power core) or maintain them in uprated cores if the nanofluid has a higher post-CHF heat transfer rate; 3) coolant for in-vessel retention of the molten core during severe accidents in highpower-density light water reactors. It can increase the margin to vessel breach by 40% during severe accidents in high-power density systems such as Westinghouse APR1000 and the Korean APR1400. While there exist several significant gaps, including the nanofluid thermal-hydraulic performance at prototypical reactor conditions and the compatibility of the nanofluid chemistry with the reactor materials. Much work should be done to overcome

Due to the restriction of space, energy and weight in space station and aircraft, there is a strong demand for high efficient cooling system with smaller size. You et al. [67] and Vassalo et al. [68] have reported order of magnitude increases in the critical heat flux in pool boiling with nanofluids compared to the base fluid alone. Further research of nanofluids will lead to the development of next generation of cooling devices that incorporate nanofluids for ultrahigh-heat-flux electronic systems, presenting the possibility of raising chip power in electronic components or simplifying cooling requirements for space applications. A number of military devices and systems require high-heat flux cooling to the level of tens of MW/m2. At this level, the cooling of military devices and system is vital for the reliable operation. Nanofluids with high critical heat fluxes have the potential to provide the required cooling in such applications as well as in other military systems, including military vehicles, submarines, and high-power laser diodes. Therefore, nanofluids have wide application in space and defense fields where power density is very high and the

Several researches have studied the mass transfer enhancement of nanofluids. Kim et al. initially examined the effect of nanoparticles on the bubble type absorption for NH3/H2O absorption system [69]. The addition of nanoparticles enhances the absorption performance up to 3.21 times. Then they visualized the bubble behavior during the NH3/H2O absorption process and studied the effect of nanoparticles and surfactants on the absorption characteristics [70]. The results show that the addition of surfactants and nanoparticles improved the absorption performance up to 5.32 times. The addition of both surfactants and nanoparticles enhanced significantly the absorption performance during the ammonia bubble absorption process. The theoretical investigations of thermodiffusion and diffusionthermo on convective instabilities in binary nanofluids for absorption application were conducted. Mass diffusion is induced by thermal gradient. Diffusionthermo implies that heat transfer is induced by concentration gradient [71]. Ma et al. studied the mass transfer process of absorption using CNTs-ammonia nanofluids as the working medium [72, 73]. The absorption rates of the CNTs-ammonia binary nanofluids were higher than those of ammonia solution without CNTs. The effective absorption ratio of the CNTs-ammonia binary nanofluids increased with the initial concentration of ammonia and the mass fraction

these gaps before any applications can be implemented in a nuclear power plant.

**4.1.6 Space and defense** 

components should be smaller and weight less.

**4.2 Mass transfer enhancement**

## **4.1.3 Industrial cooling applications**

The application of nanofluids in industrial cooling will result in great energy savings and emissions reductions. For US industry, the replacement of cooling and heating water with nanofluids has the potential to conserve 1 trillion Btu of energy [39, 61]. For the US electric power industry, using nanofluids in closed loop cooling cycles could save about 10-30 trillion Btu per year (equivalent to the annual energy consumption of about 50,000–150,000 households). The associated emissions reductions would be approximately 5.6 million metric tons of carbon dioxide, 8,600 metric tons of nitrogen oxides, and 21,000 metric tons of sulfur dioxide.

 Experiments were performed using a flow-loop apparatus to explore the performance of polyalphaolefin nanofluids containing exfoliated graphite nanoparticle fibers in cooling [63]. It was observed that the specific heat of nanofluids was found to be 50% higher for nanofluids compared with polyalphaolefin and it increased with temperature. The thermal diffusivity was found to be 4 times higher for nanofluids. The convective heat transfer was enhanced by ~10% using nanofluids compared with using polyalphaolefin. Ma et al. proposed the concept of nano liquid-metal fluid, aiming to establish an engineering route to make the highest conductive coolant with about several dozen times larger thermal conductivity than that of water [64]. The liquid metal with low melting point is expected to be an idealistic base fluid for making super conductive solution which may lead to the ultimate coolant in a wide variety of heat transfer enhancement area. The thermal conductivity of the liquid-metal fluid can be enhanced through the addition of more conductive nanoparticles.

## **4.1.4 Heating buildings and reducing pollution**

Nanofluids can be applied in the building heating systems. Kulkarni et al. evaluated how they perform heating buildings in cold regions [65]. In cold regions, it is a common practice to use ethylene or propylene glycol mixed with water in different proportions as a heat transfer fluid. So 60:40 ethylene glcol/water (by weight) was selected as the base fluid. The results showed that using nanofluids in heat exchangers could reduce volumetric and mass flow rates, resulting in an overall pumping power savings. Nanofluids necessitate smaller heating systems, which are capable of delivering the same amount of thermal energy as larger heating systems, but are less expensive. This lowers the initial equipment cost excluding nanofluid cost. This will also reduce environmental pollutants because smaller heating units use less power, and the heat transfer unit has less liquid and material waste to discard at the end of its life cycle.

## **4.1.5 Nuclear systems cooling**

The Massachusetts Institute of Technology has established an interdisciplinary center for nanofluid technology for the nuclear energy industry. The researchers are exploring the nuclear applications of nanofluids, specifically the following three [66]: 1) main reactor coolant for pressurized water reactors (PWRs). It could enable significant power uprates in current and future PWRs, thus enhancing their economic performance. Specifically, the use of nanofluids with at least 32% higher critical heat flux (CHF) could enable a 20% power density uprate in current plants without changing the fuel assembly design and without

The application of nanofluids in industrial cooling will result in great energy savings and emissions reductions. For US industry, the replacement of cooling and heating water with nanofluids has the potential to conserve 1 trillion Btu of energy [39, 61]. For the US electric power industry, using nanofluids in closed loop cooling cycles could save about 10-30 trillion Btu per year (equivalent to the annual energy consumption of about 50,000–150,000 households). The associated emissions reductions would be approximately 5.6 million metric tons of carbon dioxide, 8,600 metric tons of nitrogen oxides, and 21,000 metric tons of

 Experiments were performed using a flow-loop apparatus to explore the performance of polyalphaolefin nanofluids containing exfoliated graphite nanoparticle fibers in cooling [63]. It was observed that the specific heat of nanofluids was found to be 50% higher for nanofluids compared with polyalphaolefin and it increased with temperature. The thermal diffusivity was found to be 4 times higher for nanofluids. The convective heat transfer was enhanced by ~10% using nanofluids compared with using polyalphaolefin. Ma et al. proposed the concept of nano liquid-metal fluid, aiming to establish an engineering route to make the highest conductive coolant with about several dozen times larger thermal conductivity than that of water [64]. The liquid metal with low melting point is expected to be an idealistic base fluid for making super conductive solution which may lead to the ultimate coolant in a wide variety of heat transfer enhancement area. The thermal conductivity of the liquid-metal fluid can be enhanced through the addition of more

Nanofluids can be applied in the building heating systems. Kulkarni et al. evaluated how they perform heating buildings in cold regions [65]. In cold regions, it is a common practice to use ethylene or propylene glycol mixed with water in different proportions as a heat transfer fluid. So 60:40 ethylene glcol/water (by weight) was selected as the base fluid. The results showed that using nanofluids in heat exchangers could reduce volumetric and mass flow rates, resulting in an overall pumping power savings. Nanofluids necessitate smaller heating systems, which are capable of delivering the same amount of thermal energy as larger heating systems, but are less expensive. This lowers the initial equipment cost excluding nanofluid cost. This will also reduce environmental pollutants because smaller heating units use less power, and the heat transfer unit has less liquid and material waste to

The Massachusetts Institute of Technology has established an interdisciplinary center for nanofluid technology for the nuclear energy industry. The researchers are exploring the nuclear applications of nanofluids, specifically the following three [66]: 1) main reactor coolant for pressurized water reactors (PWRs). It could enable significant power uprates in current and future PWRs, thus enhancing their economic performance. Specifically, the use of nanofluids with at least 32% higher critical heat flux (CHF) could enable a 20% power density uprate in current plants without changing the fuel assembly design and without

**4.1.3 Industrial cooling applications** 

sulfur dioxide.

conductive nanoparticles.

discard at the end of its life cycle.

**4.1.5 Nuclear systems cooling** 

**4.1.4 Heating buildings and reducing pollution** 

reducing the margin to CHF; 2) coolant for the emergency core cooling systems (ECCSs) of both PWRs and boiling water reactors. The use of a nanofluid in the ECCS accumulators and safety injection can increase the peak-cladding-temperature margins (in the nominal-power core) or maintain them in uprated cores if the nanofluid has a higher post-CHF heat transfer rate; 3) coolant for in-vessel retention of the molten core during severe accidents in highpower-density light water reactors. It can increase the margin to vessel breach by 40% during severe accidents in high-power density systems such as Westinghouse APR1000 and the Korean APR1400. While there exist several significant gaps, including the nanofluid thermal-hydraulic performance at prototypical reactor conditions and the compatibility of the nanofluid chemistry with the reactor materials. Much work should be done to overcome these gaps before any applications can be implemented in a nuclear power plant.

## **4.1.6 Space and defense**

Due to the restriction of space, energy and weight in space station and aircraft, there is a strong demand for high efficient cooling system with smaller size. You et al. [67] and Vassalo et al. [68] have reported order of magnitude increases in the critical heat flux in pool boiling with nanofluids compared to the base fluid alone. Further research of nanofluids will lead to the development of next generation of cooling devices that incorporate nanofluids for ultrahigh-heat-flux electronic systems, presenting the possibility of raising chip power in electronic components or simplifying cooling requirements for space applications. A number of military devices and systems require high-heat flux cooling to the level of tens of MW/m2. At this level, the cooling of military devices and system is vital for the reliable operation. Nanofluids with high critical heat fluxes have the potential to provide the required cooling in such applications as well as in other military systems, including military vehicles, submarines, and high-power laser diodes. Therefore, nanofluids have wide application in space and defense fields where power density is very high and the components should be smaller and weight less.

### **4.2 Mass transfer enhancement**

Several researches have studied the mass transfer enhancement of nanofluids. Kim et al. initially examined the effect of nanoparticles on the bubble type absorption for NH3/H2O absorption system [69]. The addition of nanoparticles enhances the absorption performance up to 3.21 times. Then they visualized the bubble behavior during the NH3/H2O absorption process and studied the effect of nanoparticles and surfactants on the absorption characteristics [70]. The results show that the addition of surfactants and nanoparticles improved the absorption performance up to 5.32 times. The addition of both surfactants and nanoparticles enhanced significantly the absorption performance during the ammonia bubble absorption process. The theoretical investigations of thermodiffusion and diffusionthermo on convective instabilities in binary nanofluids for absorption application were conducted. Mass diffusion is induced by thermal gradient. Diffusionthermo implies that heat transfer is induced by concentration gradient [71]. Ma et al. studied the mass transfer process of absorption using CNTs-ammonia nanofluids as the working medium [72, 73]. The absorption rates of the CNTs-ammonia binary nanofluids were higher than those of ammonia solution without CNTs. The effective absorption ratio of the CNTs-ammonia binary nanofluids increased with the initial concentration of ammonia and the mass fraction

Nanofluids 509

absorption nanofluids. The experimental and numerical results demonstrated an initial rapid increase in efficiency with volume fraction, followed by a leveling off in efficiency as volume fraction continues to increase. Theoretical investigation on the feasibility of using a nonconcentrating direct absorption solar collector showed that the presence of nanoparticles increased the absorption of incident radiation by more than nine times over that of pure water [80]. Under the similar operating conditions, the efficiency of an absorption solar collector using nanofluid as the working fluid was found to be up to 10% higher (on an absolute basis) than that of a flat-plate collector. Otanicar et al. evaluated the overall economic and environmental impacts of the technology in contrast with conventional solar collectors using the life cycle assessment methodology [81]. Results showed that for the current cost of nanoparticles the nanofluid based solar collector had a slightly longer payback period but at the end of its useful life has the same economic saving as a conventional solar collector. Sani et al. investigated the optical and thermal properties of nanofluids consisting in aqueous suspensions of single wall carbon nanohorns [82]. The observed nanoparticle-induced differences in optical properties appeared promising, leading to a considerably higher sunlight absorption. Both these effects, together with the possible chemical functionalization of carbon nanohorns, make this new kind of nanofluids

very interesting for increasing the overall efficiency of the sunlight exploiting device.

Advanced lubricants can improve productivity through energy saving and reliability of engineered systems. Tribological research heavily emphasizes reducing friction and wear. Nanoparticles have attracted much interest in recent years due to their excellent loadcarrying capacity, good extreme pressure and friction reducing properties. Zhou et al. evaluated the tribological behavior of Cu nanoparticles in oil on a four-ball machine. The results showed that Cu nanoparticles as an oil additive had better friction-reduction and antiwear properties than zinc dithiophosphate, especially at high applied load. Meanwhile, the nanoparticles could also strikingly improve the load-carrying capacity of the base oil [83]. Dispersion of solid particles was found to play an important role, especially when a slurry layer was formed. Water-based Al2O3 and diamond nanofluids were applied in the minimum quantity lubrication (MQL) grinding process of cast iron. During the nanofluid MQL grinding, a dense and hard slurry layer was formed on the wheel surface and could benefit the grinding performance. Nanofluids showed the benefits of reducing grinding forces, improving surface roughness, and preventing workpiece burning. Compared to dry grinding, MQL grinding could significantly reduce the grinding temperature [84]. Wear and friction properties of surface modified Cu nanoparticles as 50CC oil additive were studied. The higher the oil temperature applied, the better the tribological properties of Cu nanoparticles were. It could be inferred that a thin copper protective film with lower elastic modulus and hardness was formed on the worn surface, which resulted in the good tribological performances of Cu nanoparticles, especially when the oil temperature was higher [85]. Wang et al. studied the tribological properties of ionic liquid-based nanofluids containing functionlized MWNTs under loads in the range of 200-800 N [86], indicating that the nanofluids exhibited preferable friction-reduction properties under 800 N and remarkable antiwear properties with use of reasonable concentrations. Magnetic

**4.4 Mechanical applications** 

**4.4.1 Friction reduction** 

of CNTs. Komati et al. studied CO2 absorption into amine solutions, and the addition of ferrofluids increased the mass transfer coefficient in gas/liquid mass transfer [74], and the enhancement extent depended on the amount of ferrofluid added. The enhancement in mass transfer coefficient was 92.8% for a volume fraction of the fluid of about 50% (solid magnetite volume fraction of about 0.39%). The research about the influence of Al2O3 nanofluid on the falling film absorption with ammonia-water showed that the sorts of nanoparticles and surfactants in the nanofluid and the concentration of ammonia in the basefluid were the key parameters influencing the absorption effect of ammonia [75].

## **4.3 Energy applications**

## **4.3.1 Energy storage**

The temporal difference of energy source and energy needs made necessary the development of storage system. The storage of thermal energy in the form of sensible and latent heat has become an important aspect of energy management with the emphasis on efficient use and conservation of the waste heat and solar energy in industry and buildings [76]. Latent heat storage is one of the most efficient ways of storing thermal energy. Wu et al. evaluated the potential of Al2O3-H2O nanofluids as a new phase change material (PCM) for the thermal energy storage of cooling systems. The thermal response test showed the addition of Al2O3 nanoparticles remarkably decreased the supercooling degree of water, advanced the beginning freezing time and reduced the total freezing time. Only adding 0.2 wt% Al2O3 nanoparticles, the total freezing time of Al2O3-H2O nanofluids could be reduced by 20.5%. Liu et al. prepared a new sort of nanofluid phase change materials (PCMs) by suspending small amount of TiO2 nanoparticles in saturated BaCl2 aqueous solution [77]. The nanofluids PCMs possessed remarkably high thermal conductivities compared to the base material. The cool storage/supply rate and the cool storage/supply capacity all increased greatly than those of BaCl2 aqueous solution without added nanoparticles. The higher thermal performances of nanofluids PCMs indicate that they have a potential for substituting conventional PCMs in cool storage applications. Copper nanoparticles are efficient additives to improve the heating and cooling rates of PCMs [78]. For composites with 1 wt % copper nanoparticle, the heating and cooling times could be reduced by 30.3 and 28.2%, respectively. The latent heats and phase-change temperatures changed very little after 100 thermal cycles.

#### **4.3.2 Solar absorption**

Solar energy is one of the best sources of renewable energy with minimal environmental impact. The conventional direct absorption solar collector is a well established technology, and it has been proposed for a variety of applications such as water heating; however the efficiency of these collectors is limited by the absorption properties of the working fluid, which is very poor for typical fluids used in solar collectors. Recently this technology has been combined with the emerging technologies of nanofluids and liquid-nanoparticle suspensions to create a new class of nanofluid-based solar collectors. Otanicar et al. reported the experimental results on solar collectors based on nanofluids made from a variety of nanoparticles (CNTs, graphite, and silver) [79]. The efficiency improvement was up to 5% in solar thermal collectors by utilizing nanofluids as the absorption media. In addition they compared the experimental data with a numerical model of a solar collector with direct

of CNTs. Komati et al. studied CO2 absorption into amine solutions, and the addition of ferrofluids increased the mass transfer coefficient in gas/liquid mass transfer [74], and the enhancement extent depended on the amount of ferrofluid added. The enhancement in mass transfer coefficient was 92.8% for a volume fraction of the fluid of about 50% (solid magnetite volume fraction of about 0.39%). The research about the influence of Al2O3 nanofluid on the falling film absorption with ammonia-water showed that the sorts of nanoparticles and surfactants in the nanofluid and the concentration of ammonia in the

basefluid were the key parameters influencing the absorption effect of ammonia [75].

The temporal difference of energy source and energy needs made necessary the development of storage system. The storage of thermal energy in the form of sensible and latent heat has become an important aspect of energy management with the emphasis on efficient use and conservation of the waste heat and solar energy in industry and buildings [76]. Latent heat storage is one of the most efficient ways of storing thermal energy. Wu et al. evaluated the potential of Al2O3-H2O nanofluids as a new phase change material (PCM) for the thermal energy storage of cooling systems. The thermal response test showed the addition of Al2O3 nanoparticles remarkably decreased the supercooling degree of water, advanced the beginning freezing time and reduced the total freezing time. Only adding 0.2 wt% Al2O3 nanoparticles, the total freezing time of Al2O3-H2O nanofluids could be reduced by 20.5%. Liu et al. prepared a new sort of nanofluid phase change materials (PCMs) by suspending small amount of TiO2 nanoparticles in saturated BaCl2 aqueous solution [77]. The nanofluids PCMs possessed remarkably high thermal conductivities compared to the base material. The cool storage/supply rate and the cool storage/supply capacity all increased greatly than those of BaCl2 aqueous solution without added nanoparticles. The higher thermal performances of nanofluids PCMs indicate that they have a potential for substituting conventional PCMs in cool storage applications. Copper nanoparticles are efficient additives to improve the heating and cooling rates of PCMs [78]. For composites with 1 wt % copper nanoparticle, the heating and cooling times could be reduced by 30.3 and 28.2%, respectively. The latent heats and phase-change temperatures changed very little

Solar energy is one of the best sources of renewable energy with minimal environmental impact. The conventional direct absorption solar collector is a well established technology, and it has been proposed for a variety of applications such as water heating; however the efficiency of these collectors is limited by the absorption properties of the working fluid, which is very poor for typical fluids used in solar collectors. Recently this technology has been combined with the emerging technologies of nanofluids and liquid-nanoparticle suspensions to create a new class of nanofluid-based solar collectors. Otanicar et al. reported the experimental results on solar collectors based on nanofluids made from a variety of nanoparticles (CNTs, graphite, and silver) [79]. The efficiency improvement was up to 5% in solar thermal collectors by utilizing nanofluids as the absorption media. In addition they compared the experimental data with a numerical model of a solar collector with direct

**4.3 Energy applications 4.3.1 Energy storage** 

after 100 thermal cycles.

**4.3.2 Solar absorption** 

absorption nanofluids. The experimental and numerical results demonstrated an initial rapid increase in efficiency with volume fraction, followed by a leveling off in efficiency as volume fraction continues to increase. Theoretical investigation on the feasibility of using a nonconcentrating direct absorption solar collector showed that the presence of nanoparticles increased the absorption of incident radiation by more than nine times over that of pure water [80]. Under the similar operating conditions, the efficiency of an absorption solar collector using nanofluid as the working fluid was found to be up to 10% higher (on an absolute basis) than that of a flat-plate collector. Otanicar et al. evaluated the overall economic and environmental impacts of the technology in contrast with conventional solar collectors using the life cycle assessment methodology [81]. Results showed that for the current cost of nanoparticles the nanofluid based solar collector had a slightly longer payback period but at the end of its useful life has the same economic saving as a conventional solar collector. Sani et al. investigated the optical and thermal properties of nanofluids consisting in aqueous suspensions of single wall carbon nanohorns [82]. The observed nanoparticle-induced differences in optical properties appeared promising, leading to a considerably higher sunlight absorption. Both these effects, together with the possible chemical functionalization of carbon nanohorns, make this new kind of nanofluids very interesting for increasing the overall efficiency of the sunlight exploiting device.

#### **4.4 Mechanical applications**

#### **4.4.1 Friction reduction**

Advanced lubricants can improve productivity through energy saving and reliability of engineered systems. Tribological research heavily emphasizes reducing friction and wear. Nanoparticles have attracted much interest in recent years due to their excellent loadcarrying capacity, good extreme pressure and friction reducing properties. Zhou et al. evaluated the tribological behavior of Cu nanoparticles in oil on a four-ball machine. The results showed that Cu nanoparticles as an oil additive had better friction-reduction and antiwear properties than zinc dithiophosphate, especially at high applied load. Meanwhile, the nanoparticles could also strikingly improve the load-carrying capacity of the base oil [83]. Dispersion of solid particles was found to play an important role, especially when a slurry layer was formed. Water-based Al2O3 and diamond nanofluids were applied in the minimum quantity lubrication (MQL) grinding process of cast iron. During the nanofluid MQL grinding, a dense and hard slurry layer was formed on the wheel surface and could benefit the grinding performance. Nanofluids showed the benefits of reducing grinding forces, improving surface roughness, and preventing workpiece burning. Compared to dry grinding, MQL grinding could significantly reduce the grinding temperature [84]. Wear and friction properties of surface modified Cu nanoparticles as 50CC oil additive were studied. The higher the oil temperature applied, the better the tribological properties of Cu nanoparticles were. It could be inferred that a thin copper protective film with lower elastic modulus and hardness was formed on the worn surface, which resulted in the good tribological performances of Cu nanoparticles, especially when the oil temperature was higher [85]. Wang et al. studied the tribological properties of ionic liquid-based nanofluids containing functionlized MWNTs under loads in the range of 200-800 N [86], indicating that the nanofluids exhibited preferable friction-reduction properties under 800 N and remarkable antiwear properties with use of reasonable concentrations. Magnetic

Nanofluids 511

terminated) in blood flow [93]. Ferro-cobalt magnetic fluid was used for oil sealing, and the

Organic antibacterial materials are often less stable particularly at high temperatures or pressures. As a consequence, inorganic materials such as metal and metal oxides have attracted lots of attention over the past decade due to their ability to withstand harsh process conditions. The antibacterial behaviour of ZnO nanofluids shows that the ZnO nanofluids have bacteriostatic activity against [95]. Electrochemical measurements suggest some direct interaction between ZnO nanoparticles and the bacteria membrane at high ZnO concentrations. Jalal et al. prepared ZnO nanoparticles via a green method. The antibacterial activity of suspensions of ZnO nanoparticles against Escherichia coli (E. coli) has been evaluated by estimating the reduction ratio of the bacteria treated with ZnO. Survival ratio of bacteria decreases with increasing the concentrations of ZnO nanofluids and time [96]. Further investigations have clearly demonstrated that ZnO nanoparticles have a wide range of antibacterial effects on a number of other microorganisms. The antibacterial activity of ZnO may be dependent on the size and the presence of normal visible light [97]. Recent research showed that ZnO nanoparticles exhibited impressive antibacterial properties against an important foodborne pathogen, E. coli O157:H7, and the inhibitory effects increased as the concentrations of ZnO nanoparticles increased. ZnO nanoparticles changed the cell membrane components including lipids and proteins. ZnO nanoparticles could distort bacterial cell membrane, leading to loss of intracellular components, and ultimately the death of cells, considered as an effective antibacterial agent for protecting agricultural

The antibacterial activity research of CuO nanoparticles showed that they possessed antibacterial activity against four bacterial strains. The size of nanoparticles was less than that of the pore size in the bacteria and thus they had a unique property of crossing the cell membrane without any hindrance. It could be hypothesized that these nanoparticles formed stable complexes with vital enzymes inside cells which hampered cellular functioning resulting in their death [99]. Bulk equivalents of these products showed no inhibitory activity, indicating that particle size was determinant in activity [100]. Lee et al. reported the antibacterial efficacy of nanosized silver colloidal solution on the cellulosic and synthetic fabrics [101]. The antibacterial treatment of the textile fabrics was easily achieved by padding them with nanosized silver colloidal solution. The antibacterial efficacy of the fabrics was maintained after many times laundering. Silver colloid is an efficient antibacterial agent. The silver colloid prepared by a one-step synthesis showed high antimicrobial and bactericidal activity against Gram-positive and Gram-negative bacteria, including highly multiresistant strains such as methicillin-resistant staphylococcus aureus. The antibacterial activity of silver nanoparticles was found to be dependent on the size of silver particles. A very low concentration of silver gave antibacterial performance [102]. The aqueous suspensions of fullerenes and nano-TiO2 can produce reactive oxygen species (ROS). Bacterial (E. coli) toxicity tests suggestted that, unlike nano-TiO2 which was exclusively phototoxic, the antibacterial activity of fullerene suspensions was linked to ROS production. Nano-TiO2 may be more efficient for water treatment involving UV or solar

holding pressure is 25 times as high as that of a conventional magnetite sealing [94].

**4.5 Biomedical application 4.5.1 Antibacterial activity** 

and food safety [98].

nanoparticle Mn0.78Zn0.22Fe2O4 was also an efficient lubricant additive. When used as a lubricant additive in 46# turbine oil, it could improve the wear resistance, load-carrying capacity, and antifriction ability of base oil, and the decreasing percentage of wear scar diameter was 25.45% compared to the base oil. This was a typical self-repair phenomenon [87]. Chen et al. reported on dispersion stability enhancement and self-repair principle discussion of ultrafine-tungsten disulfide in green lubricating oil [88]. Ultrafine-tungsten disulfide particulates could fill and level up the furrows on abrasive surfaces, repairing abrasive surface well. What is more, ultrafine-tungsten disulfide particulates could form a WS2 film with low shear stress by adsorbing and depositing in the hollowness of abrasive surface, making the abrasive surface be more smooth, and the FeS film formed in tribology reaction could protect the abrasive surface further, all of which realize the self-repair to abrasive surface. The tribological properties of liquid paraffin with SiO2 nanoparticles additive made by a sol-gel method was investigated by Peng et al. [89]. The optimal concentrations of SiO2 nanoparticles in liquid paraffin was associated with better tribological properties than pure paraffin oil, and an anti-wear ability that depended on the particle size, and oleic acid surface-modified SiO2 nanoparticles with an average diameter of 58 nm provided better tribological properties in load-carrying capacity, anti-wear and friction-reduction than pure liquid paraffin. Nanoparticles can easily penetrate into the rubbing surfaces because of their nanoscale. During the frictional process, the thin physical tribofilm of the nanoparticles forms between rubbing surfaces, which cannot only bear the load but also separates the rubbing faces. The spherical SiO2 nanoparticles could roll between the rubbing faces in sliding friction, the originally pure sliding friction becomes mixed sliding and rolling friction. Therefore, the friction coefficient declines markedly and then remains constant.

#### **4.4.2 Magnetic sealing**

Magnetic fluids (Ferromagnetic fluid) are kinds of special nanofluids. They are stable colloidal suspensions of small magnetic particles such as magnetite (Fe3O4). The properties of the magnetic nanoparticles, the magnetic component of magnetic nanofluids, may be tailored by varying their size and adapting their surface coating in order to meet the requirements of colloidal stability of magnetic nanofluids with non-polar and polar carrier liquids [90]. Comparing with the mechanical sealing, magnetic sealing offers a cost-effective solution to environmental and hazardous-gas sealing in a wide variety of industrial rotation equipment with high speed capability, low friction power losses and long life and high reliability [91]. A ring magnet forms part of a magnetic circuit in which an intense magnetic field is established in the gaps between the teeth on a magnetically permeable shaft and the surface of an opposing pole block. Ferrofluid introduced into the gaps forms discrete liquid rings capable of supporting a pressure difference while maintaining zero leakage. The seals operate without wear as the shaft rotates because the mechanical moving parts do not touch. With these unique characteristics, sealing liquids with magnetic fluids can be applied in many application areas. It is reported that an iron particle dispersed magnetic fluids was utilized in the sealing of a high rotation pump. The sealing holds pressure of 618 kPa with a 1800 r/min [92]. Mitamura et al. studied the application of a magnetic fluid seal to rotary blood pumps. The developed magnetic fluid seal worked for over 286 days in a continuous flow condition, for 24 days (on-going) in a pulsatile flow condition and for 24 h (electively

nanoparticle Mn0.78Zn0.22Fe2O4 was also an efficient lubricant additive. When used as a lubricant additive in 46# turbine oil, it could improve the wear resistance, load-carrying capacity, and antifriction ability of base oil, and the decreasing percentage of wear scar diameter was 25.45% compared to the base oil. This was a typical self-repair phenomenon [87]. Chen et al. reported on dispersion stability enhancement and self-repair principle discussion of ultrafine-tungsten disulfide in green lubricating oil [88]. Ultrafine-tungsten disulfide particulates could fill and level up the furrows on abrasive surfaces, repairing abrasive surface well. What is more, ultrafine-tungsten disulfide particulates could form a WS2 film with low shear stress by adsorbing and depositing in the hollowness of abrasive surface, making the abrasive surface be more smooth, and the FeS film formed in tribology reaction could protect the abrasive surface further, all of which realize the self-repair to abrasive surface. The tribological properties of liquid paraffin with SiO2 nanoparticles additive made by a sol-gel method was investigated by Peng et al. [89]. The optimal concentrations of SiO2 nanoparticles in liquid paraffin was associated with better tribological properties than pure paraffin oil, and an anti-wear ability that depended on the particle size, and oleic acid surface-modified SiO2 nanoparticles with an average diameter of 58 nm provided better tribological properties in load-carrying capacity, anti-wear and friction-reduction than pure liquid paraffin. Nanoparticles can easily penetrate into the rubbing surfaces because of their nanoscale. During the frictional process, the thin physical tribofilm of the nanoparticles forms between rubbing surfaces, which cannot only bear the load but also separates the rubbing faces. The spherical SiO2 nanoparticles could roll between the rubbing faces in sliding friction, the originally pure sliding friction becomes mixed sliding and rolling friction. Therefore, the friction coefficient declines markedly and

Magnetic fluids (Ferromagnetic fluid) are kinds of special nanofluids. They are stable colloidal suspensions of small magnetic particles such as magnetite (Fe3O4). The properties of the magnetic nanoparticles, the magnetic component of magnetic nanofluids, may be tailored by varying their size and adapting their surface coating in order to meet the requirements of colloidal stability of magnetic nanofluids with non-polar and polar carrier liquids [90]. Comparing with the mechanical sealing, magnetic sealing offers a cost-effective solution to environmental and hazardous-gas sealing in a wide variety of industrial rotation equipment with high speed capability, low friction power losses and long life and high reliability [91]. A ring magnet forms part of a magnetic circuit in which an intense magnetic field is established in the gaps between the teeth on a magnetically permeable shaft and the surface of an opposing pole block. Ferrofluid introduced into the gaps forms discrete liquid rings capable of supporting a pressure difference while maintaining zero leakage. The seals operate without wear as the shaft rotates because the mechanical moving parts do not touch. With these unique characteristics, sealing liquids with magnetic fluids can be applied in many application areas. It is reported that an iron particle dispersed magnetic fluids was utilized in the sealing of a high rotation pump. The sealing holds pressure of 618 kPa with a 1800 r/min [92]. Mitamura et al. studied the application of a magnetic fluid seal to rotary blood pumps. The developed magnetic fluid seal worked for over 286 days in a continuous flow condition, for 24 days (on-going) in a pulsatile flow condition and for 24 h (electively

then remains constant.

**4.4.2 Magnetic sealing** 

terminated) in blood flow [93]. Ferro-cobalt magnetic fluid was used for oil sealing, and the holding pressure is 25 times as high as that of a conventional magnetite sealing [94].

## **4.5 Biomedical application**

## **4.5.1 Antibacterial activity**

Organic antibacterial materials are often less stable particularly at high temperatures or pressures. As a consequence, inorganic materials such as metal and metal oxides have attracted lots of attention over the past decade due to their ability to withstand harsh process conditions. The antibacterial behaviour of ZnO nanofluids shows that the ZnO nanofluids have bacteriostatic activity against [95]. Electrochemical measurements suggest some direct interaction between ZnO nanoparticles and the bacteria membrane at high ZnO concentrations. Jalal et al. prepared ZnO nanoparticles via a green method. The antibacterial activity of suspensions of ZnO nanoparticles against Escherichia coli (E. coli) has been evaluated by estimating the reduction ratio of the bacteria treated with ZnO. Survival ratio of bacteria decreases with increasing the concentrations of ZnO nanofluids and time [96]. Further investigations have clearly demonstrated that ZnO nanoparticles have a wide range of antibacterial effects on a number of other microorganisms. The antibacterial activity of ZnO may be dependent on the size and the presence of normal visible light [97]. Recent research showed that ZnO nanoparticles exhibited impressive antibacterial properties against an important foodborne pathogen, E. coli O157:H7, and the inhibitory effects increased as the concentrations of ZnO nanoparticles increased. ZnO nanoparticles changed the cell membrane components including lipids and proteins. ZnO nanoparticles could distort bacterial cell membrane, leading to loss of intracellular components, and ultimately the death of cells, considered as an effective antibacterial agent for protecting agricultural and food safety [98].

The antibacterial activity research of CuO nanoparticles showed that they possessed antibacterial activity against four bacterial strains. The size of nanoparticles was less than that of the pore size in the bacteria and thus they had a unique property of crossing the cell membrane without any hindrance. It could be hypothesized that these nanoparticles formed stable complexes with vital enzymes inside cells which hampered cellular functioning resulting in their death [99]. Bulk equivalents of these products showed no inhibitory activity, indicating that particle size was determinant in activity [100]. Lee et al. reported the antibacterial efficacy of nanosized silver colloidal solution on the cellulosic and synthetic fabrics [101]. The antibacterial treatment of the textile fabrics was easily achieved by padding them with nanosized silver colloidal solution. The antibacterial efficacy of the fabrics was maintained after many times laundering. Silver colloid is an efficient antibacterial agent. The silver colloid prepared by a one-step synthesis showed high antimicrobial and bactericidal activity against Gram-positive and Gram-negative bacteria, including highly multiresistant strains such as methicillin-resistant staphylococcus aureus. The antibacterial activity of silver nanoparticles was found to be dependent on the size of silver particles. A very low concentration of silver gave antibacterial performance [102]. The aqueous suspensions of fullerenes and nano-TiO2 can produce reactive oxygen species (ROS). Bacterial (E. coli) toxicity tests suggestted that, unlike nano-TiO2 which was exclusively phototoxic, the antibacterial activity of fullerene suspensions was linked to ROS production. Nano-TiO2 may be more efficient for water treatment involving UV or solar

Nanofluids 513

for the loading and targeted delivery of anticancer drugs [114]. Controlled loading of two anticancer drugs onto the folic acid-conjugated NGO via π–π stacking and hydrophobic interactions demonstrated that NGO loaded with the two anticancer drugs showed specific targeting to MCF-7 cells (human breast cancer cells with folic acid receptors), and remarkably high cytotoxicity compared to NGO loaded with either doxorubicin or camptothecin only. The PEGylated (PEG: polyethylene glycol) nanographene oxide could be used for the delivery of water-insoluble cancer drugs [115]. PEGylated NGO readily complexes with a water insoluble aromatic molecule SN38, a camptothecin analogue, via noncovalent van der Waals interaction. The NGO-PEG-SN38 complex exhibits excellent aqueous solubility and retains the high potency of free SN38 dissolved in organic solvents. Yang et al. found GO-Fe3O4 hybrid could be loaded with anti-cancer drug doxorubicin hydrochloride with a high loading capacity [116]. This GO-Fe3O4 hybrid showed superparamagnetic property and could congregate under acidic conditions and be redispersed reversibly under basic conditions. This pH-triggered controlled magnetic behavior makes this material a promising candidate for controlled targeted drug delivery.

The discovery of high enhancement of heat transfer in nanofluids can be applicable to the area of process intensification of chemical reactors through integration of the functionalities of reaction and heat transfer in compact multifunctional reactors. Fan et al. studied a nanofluid based on benign TiO2 material dispersed in ethylene glycol in an integrated reactor-heat exchanger [117]. The overall heat transfer coefficient increase was up to 35% in the steady state continuous experiments. This resulted in a closer temperature control in the reaction of selective reduction of an aromatic aldehyde by molecular hydrogen and very

A vehicle's kinetic energy is dispersed through the heat produced during the process of braking and this is transmitted throughout the brake fluid in the hydraulic braking system [39], and now there is a higher demand for the properties of brake oils. Copper-oxide and aluminum-oxide based brake nanofluids were manufactured using the arc-submerged nanoparticle synthesis system and the plasma charging arc system, respectively [118, 119]. The two kinds of nanofluids both have enhanced properties such as a higher boiling point, higher viscosity and a higher conductivity than that of traditional brake fluid. By yielding a higher boiling point, conductivity and viscosity, the nanofluid brake oil will reduce the

Microbial fuel cells (MFC) that utilize the energy found in carbohydrates, proteins and other energy rich natural products to generate electrical power have a promising future. The excellent performance of MFC depends on electrodes and electron mediator. Sharma et al. constructed a novel microbial fuel cell (MFC) using novel electron mediators and CNT based electrodes [120]. The novel mediators are nanofluids which were prepared by

rapid change in the temperature of reaction under dynamic reaction control.

occurrence of vapor-lock and offer increased safety while driving.

**4.6 Other applications** 

**4.6.1 Intensify microreactors** 

**4.6.2 Nanofluids as vehicular brake fluids** 

**4.6.3 Nanofluids based microbial fuel cell** 

energy, to enhance contaminant oxidation and perhaps for disinfection. However, fullerol and PVP/C60 may be useful as water treatment agents targeting specific pollutants or microorganisms that are more sensitive to either superoxide or singlet oxygen [103]. Lyon et al. proposed that C60 suspensions exerted ROS-independent oxidative stress in bacteria, with evidence of protein oxidation, changes in cell membrane potential, and interruption of cellular respiration. This mechanism requires direct contact between the nanoparticle and the bacterial cell and differs from previously reported nanomaterial antibacterial mechanisms that involve ROS generation (metal oxides) or leaching of toxic elements (nanosilver) [104].

### **4.5.2 Nanodrug delivery**

Over the last few decades, colloidal drug delivery systems have been developed in order to improve the efficiency and the specificity of drug action [105]. The small size, customized surface, improved solubility, and multi-functionality of nanoparticles open many doors and create new biomedical applications. The novel properties of nanoparticles offer the ability to interact with complex cellular functions in new ways [106]. Gold nanoparticles provide nontoxic carriers for drug and gene delivery applications. With these systems, the gold core imparts stability to the assembly, while the monolayer allows tuning of surface properties such as charge and hydrophobicity. Another attractive feature of gold nanoparticles is their interaction with thiols, providing an effective and selective means of controlled intracellular release [107]. Nakano et al. proposed the drug delivery system using nano-magnetic fluid [108], which targetted and concentrated drugs using a ferrofluid cluster composed of magnetic nanoparticles. The potential of magnetic nanoparticles stems from the intrinsic properties of their magnetic cores combined with their drug loading capability and the biochemical properties that can be bestowed on them by means of a suitable coating. CNT has emerged as a new alternative and efficient tool for transporting and translocating therapeutic molecules. CNT can be functionalised with bioactive peptides, proteins, nucleic acids and drugs, and used to deliver their cargos to cells and organs. Because functionalised CNT display low toxicity and are not immunogenic, such systems hold great potential in the field of nanobiotechnology and nanomedicine [109, 110]. Pastorin et al. have developed a novel strategy for the functionalisation of CNTs with two different molecules using the 1,3 dipolar cycloaddition of azomethine ylides [111]. The attachment of molecules that will target specific receptors on tumour cells will help improve the response to anticancer agents. Liu et al. have found that prefunctionalized CNTs can adsorb widely used aromatic molecules by simple mixing, forming "forest–scrub"-like assemblies on CNTs with PEG extending into water to impart solubility and aromatic molecules densely populating CNT sidewalls. The work establishes a novel, easy-to-make formulation of a SWNT-doxorubicin complex with extremely high drug loading efficiency [112].

In recent years, graphene based drug delivery systems have attracted more and more attention. In 2008, Sun et al. firstly reported the application of nano-graphene oxide (NGO) for cellular imaging and drug delivery [113]. They have developed functionalization chemistry in order to impart solubility and compatibility of NGO in biological environments. Simple physicosorption via π-stacking can be used for loading doxorubicin, a widely used cancer drug onto NGO functionalized with antibody for selective killing of cancer cells in vitro. Functional nanoscale graphene oxide is found to be a novel nanocarrier

energy, to enhance contaminant oxidation and perhaps for disinfection. However, fullerol and PVP/C60 may be useful as water treatment agents targeting specific pollutants or microorganisms that are more sensitive to either superoxide or singlet oxygen [103]. Lyon et al. proposed that C60 suspensions exerted ROS-independent oxidative stress in bacteria, with evidence of protein oxidation, changes in cell membrane potential, and interruption of cellular respiration. This mechanism requires direct contact between the nanoparticle and the bacterial cell and differs from previously reported nanomaterial antibacterial mechanisms that involve ROS generation (metal oxides) or leaching of toxic elements

Over the last few decades, colloidal drug delivery systems have been developed in order to improve the efficiency and the specificity of drug action [105]. The small size, customized surface, improved solubility, and multi-functionality of nanoparticles open many doors and create new biomedical applications. The novel properties of nanoparticles offer the ability to interact with complex cellular functions in new ways [106]. Gold nanoparticles provide nontoxic carriers for drug and gene delivery applications. With these systems, the gold core imparts stability to the assembly, while the monolayer allows tuning of surface properties such as charge and hydrophobicity. Another attractive feature of gold nanoparticles is their interaction with thiols, providing an effective and selective means of controlled intracellular release [107]. Nakano et al. proposed the drug delivery system using nano-magnetic fluid [108], which targetted and concentrated drugs using a ferrofluid cluster composed of magnetic nanoparticles. The potential of magnetic nanoparticles stems from the intrinsic properties of their magnetic cores combined with their drug loading capability and the biochemical properties that can be bestowed on them by means of a suitable coating. CNT has emerged as a new alternative and efficient tool for transporting and translocating therapeutic molecules. CNT can be functionalised with bioactive peptides, proteins, nucleic acids and drugs, and used to deliver their cargos to cells and organs. Because functionalised CNT display low toxicity and are not immunogenic, such systems hold great potential in the field of nanobiotechnology and nanomedicine [109, 110]. Pastorin et al. have developed a novel strategy for the functionalisation of CNTs with two different molecules using the 1,3 dipolar cycloaddition of azomethine ylides [111]. The attachment of molecules that will target specific receptors on tumour cells will help improve the response to anticancer agents. Liu et al. have found that prefunctionalized CNTs can adsorb widely used aromatic molecules by simple mixing, forming "forest–scrub"-like assemblies on CNTs with PEG extending into water to impart solubility and aromatic molecules densely populating CNT sidewalls. The work establishes a novel, easy-to-make formulation of a SWNT-doxorubicin

In recent years, graphene based drug delivery systems have attracted more and more attention. In 2008, Sun et al. firstly reported the application of nano-graphene oxide (NGO) for cellular imaging and drug delivery [113]. They have developed functionalization chemistry in order to impart solubility and compatibility of NGO in biological environments. Simple physicosorption via π-stacking can be used for loading doxorubicin, a widely used cancer drug onto NGO functionalized with antibody for selective killing of cancer cells in vitro. Functional nanoscale graphene oxide is found to be a novel nanocarrier

complex with extremely high drug loading efficiency [112].

(nanosilver) [104].

**4.5.2 Nanodrug delivery** 

for the loading and targeted delivery of anticancer drugs [114]. Controlled loading of two anticancer drugs onto the folic acid-conjugated NGO via π–π stacking and hydrophobic interactions demonstrated that NGO loaded with the two anticancer drugs showed specific targeting to MCF-7 cells (human breast cancer cells with folic acid receptors), and remarkably high cytotoxicity compared to NGO loaded with either doxorubicin or camptothecin only. The PEGylated (PEG: polyethylene glycol) nanographene oxide could be used for the delivery of water-insoluble cancer drugs [115]. PEGylated NGO readily complexes with a water insoluble aromatic molecule SN38, a camptothecin analogue, via noncovalent van der Waals interaction. The NGO-PEG-SN38 complex exhibits excellent aqueous solubility and retains the high potency of free SN38 dissolved in organic solvents. Yang et al. found GO-Fe3O4 hybrid could be loaded with anti-cancer drug doxorubicin hydrochloride with a high loading capacity [116]. This GO-Fe3O4 hybrid showed superparamagnetic property and could congregate under acidic conditions and be redispersed reversibly under basic conditions. This pH-triggered controlled magnetic behavior makes this material a promising candidate for controlled targeted drug delivery.

## **4.6 Other applications**

## **4.6.1 Intensify microreactors**

The discovery of high enhancement of heat transfer in nanofluids can be applicable to the area of process intensification of chemical reactors through integration of the functionalities of reaction and heat transfer in compact multifunctional reactors. Fan et al. studied a nanofluid based on benign TiO2 material dispersed in ethylene glycol in an integrated reactor-heat exchanger [117]. The overall heat transfer coefficient increase was up to 35% in the steady state continuous experiments. This resulted in a closer temperature control in the reaction of selective reduction of an aromatic aldehyde by molecular hydrogen and very rapid change in the temperature of reaction under dynamic reaction control.

### **4.6.2 Nanofluids as vehicular brake fluids**

A vehicle's kinetic energy is dispersed through the heat produced during the process of braking and this is transmitted throughout the brake fluid in the hydraulic braking system [39], and now there is a higher demand for the properties of brake oils. Copper-oxide and aluminum-oxide based brake nanofluids were manufactured using the arc-submerged nanoparticle synthesis system and the plasma charging arc system, respectively [118, 119]. The two kinds of nanofluids both have enhanced properties such as a higher boiling point, higher viscosity and a higher conductivity than that of traditional brake fluid. By yielding a higher boiling point, conductivity and viscosity, the nanofluid brake oil will reduce the occurrence of vapor-lock and offer increased safety while driving.

## **4.6.3 Nanofluids based microbial fuel cell**

Microbial fuel cells (MFC) that utilize the energy found in carbohydrates, proteins and other energy rich natural products to generate electrical power have a promising future. The excellent performance of MFC depends on electrodes and electron mediator. Sharma et al. constructed a novel microbial fuel cell (MFC) using novel electron mediators and CNT based electrodes [120]. The novel mediators are nanofluids which were prepared by

Nanofluids 515

practical applications. The stability of nanofluids, especially the long term stability, the stability in the practical conditions and the stability after thousands of thermal cycles should be paid more attention. Fifthly, there is a lack of investigation of the thermal performance of nanofluids at high temperatures, which may widen the possible application areas of nanofluids, like in high temperature solar energy absorption and high temperature energy storage. At the same time, high temperature may accelerate the degradation of the surfactants used as dispersants in nanofluids, and may produce more foams. These factors should be taken into account. Finally, the properties of nanofluids strongly depend on the shape and property of the additive. Therefore nanofluid research can be richened and extended through exploring new nanomaterials. For example, the newly discovered 2-D monatomic sheet graphene is a promising candidate material to enhance the thermal conductivity of the base fluid [123, 124]. The concept of nanofluids is extended by the use of phase change materials, which goes well beyond simply increasing the thermal conductivity of a fluid [125]. It is found that the indium/polyalphaolefin phase change nanofluid exhibits

The work was supported by New Century Excellent Talents in University (NECT-10-883), the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning, and partly by National Natural Science Foundation of China (51106093).

simultaneously enhanced thermal conductivity and specific heat.

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**6. Acknowledgment** 

768 (2005).

**7. References** 

dispersing nanocrystalline platinum anchored CNTs in water. They compared the performance of the new E. coli based MFC to the previously reported E. coli based microbial fuel cells with Neutral Red and Methylene Blue electron mediators. The performance of the MFC using CNT based nanofluids and CNT based electrodes has been compared against plain graphite electrode based MFC. CNT based electrodes showed as high as ~6 fold increase in the power density compared to graphite electrodes. The work demonstrates the potential of noble metal nanoparticles dispersed on CNT based MFC for the generation of high energies from even simple bacteria like E. coli.

## **4.6.4 Nanofluids with unique optical properties**

Optical filters are used to select different wavelengths of light. The ferrofluid based optical filter has tunable properties. The desired central wavelength region can be tuned by an external magnetic field. Philip et al. developed a ferrofluid based emulsion for selecting different bands of wavelengths in the UV, visible and IR regions [121]. The desired range of wavelengths, bandwidth and percentage of reflectivity could be easily controlled by using suitably tailored ferrofluid emulsions. Mishra et al. developed nanofluids with selective visible colors in gold nanoparticles embedded in polymer molecules of polyvinyl pyrrolidone (PVP) in water [122]. They compared the developments in the apparent visible colors in forming the Au-PVP nanofluids of 0.05, 0.10, 0.50, and 1.00 wt% Au-contents. The surface plasmon bands, which occurs over 480-700 nm, varies sensitively in its position as well as the intensity when varying the Au-content 0-1 wt%.

## **5. Conclusions**

Many interesting properties of nanofluids have been reported in the past decades. This paper presents an overview of the recent developments in the study of nanofluids, including the preparation methods, the evaluation methods for their stability, the ways to enhance their stability, the stability mechanisms, and their potential applications in heat transfer intensification, mass transfer enhancement, energy fields, mechanical fields and biomedical fields, etc.

Although nanofluids have displayed enormously exciting potential applications, some vital hinders also exist before commercialization of nanofluids. The following key issues should receive greater attention in the future. Firstly, further experimental and theoretical researches are required to find the major factors influencing the performance of nanofluids. Up to now, there is a lack of agreement between experimental results from different groups, so it is important to systematically identify these factors. The detailed and accurate structure characterizations of the suspensions may be the key to explain the discrepancy in the experimental data. Secondly, increase in viscosity by the use of nanofluids is an important drawback due to the associated increase in pumping power. The applications for nanofluids with low viscosity and high conductivity are promising. Enhancing the compatibility between nanomaterials and the base fluids through modifying the interface properties of two phases may be one of the solution routes. Thirdly, the shape of the additives in nanofluids is very important for the properties, therefore the new nanofluid synthesis approaches with controllable microscope structure will be an interesting research work. Fourthly, Stability of the suspension is a crucial issue for both scientific research and

dispersing nanocrystalline platinum anchored CNTs in water. They compared the performance of the new E. coli based MFC to the previously reported E. coli based microbial fuel cells with Neutral Red and Methylene Blue electron mediators. The performance of the MFC using CNT based nanofluids and CNT based electrodes has been compared against plain graphite electrode based MFC. CNT based electrodes showed as high as ~6 fold increase in the power density compared to graphite electrodes. The work demonstrates the potential of noble metal nanoparticles dispersed on CNT based MFC for the generation of

Optical filters are used to select different wavelengths of light. The ferrofluid based optical filter has tunable properties. The desired central wavelength region can be tuned by an external magnetic field. Philip et al. developed a ferrofluid based emulsion for selecting different bands of wavelengths in the UV, visible and IR regions [121]. The desired range of wavelengths, bandwidth and percentage of reflectivity could be easily controlled by using suitably tailored ferrofluid emulsions. Mishra et al. developed nanofluids with selective visible colors in gold nanoparticles embedded in polymer molecules of polyvinyl pyrrolidone (PVP) in water [122]. They compared the developments in the apparent visible colors in forming the Au-PVP nanofluids of 0.05, 0.10, 0.50, and 1.00 wt% Au-contents. The surface plasmon bands, which occurs over 480-700 nm, varies sensitively in its position as

Many interesting properties of nanofluids have been reported in the past decades. This paper presents an overview of the recent developments in the study of nanofluids, including the preparation methods, the evaluation methods for their stability, the ways to enhance their stability, the stability mechanisms, and their potential applications in heat transfer intensification, mass transfer enhancement, energy fields, mechanical fields and biomedical

Although nanofluids have displayed enormously exciting potential applications, some vital hinders also exist before commercialization of nanofluids. The following key issues should receive greater attention in the future. Firstly, further experimental and theoretical researches are required to find the major factors influencing the performance of nanofluids. Up to now, there is a lack of agreement between experimental results from different groups, so it is important to systematically identify these factors. The detailed and accurate structure characterizations of the suspensions may be the key to explain the discrepancy in the experimental data. Secondly, increase in viscosity by the use of nanofluids is an important drawback due to the associated increase in pumping power. The applications for nanofluids with low viscosity and high conductivity are promising. Enhancing the compatibility between nanomaterials and the base fluids through modifying the interface properties of two phases may be one of the solution routes. Thirdly, the shape of the additives in nanofluids is very important for the properties, therefore the new nanofluid synthesis approaches with controllable microscope structure will be an interesting research work. Fourthly, Stability of the suspension is a crucial issue for both scientific research and

high energies from even simple bacteria like E. coli.

**4.6.4 Nanofluids with unique optical properties** 

well as the intensity when varying the Au-content 0-1 wt%.

**5. Conclusions** 

fields, etc.

practical applications. The stability of nanofluids, especially the long term stability, the stability in the practical conditions and the stability after thousands of thermal cycles should be paid more attention. Fifthly, there is a lack of investigation of the thermal performance of nanofluids at high temperatures, which may widen the possible application areas of nanofluids, like in high temperature solar energy absorption and high temperature energy storage. At the same time, high temperature may accelerate the degradation of the surfactants used as dispersants in nanofluids, and may produce more foams. These factors should be taken into account. Finally, the properties of nanofluids strongly depend on the shape and property of the additive. Therefore nanofluid research can be richened and extended through exploring new nanomaterials. For example, the newly discovered 2-D monatomic sheet graphene is a promising candidate material to enhance the thermal conductivity of the base fluid [123, 124]. The concept of nanofluids is extended by the use of phase change materials, which goes well beyond simply increasing the thermal conductivity of a fluid [125]. It is found that the indium/polyalphaolefin phase change nanofluid exhibits simultaneously enhanced thermal conductivity and specific heat.

## **6. Acknowledgment**

The work was supported by New Century Excellent Talents in University (NECT-10-883), the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning, and partly by National Natural Science Foundation of China (51106093).

## **7. References**


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**23** 

*Iran* 

**Thermal Conductivity** 

*Shahreza Branch, Islamic Azad University* 

ୢ୶ (1)

**of Nanoparticles Filled Polymers** 

Hassan Ebadi-Dehaghani and Monireh Nazempour

Thermal conductivity of polymers is an important thermal property for both polymer applications and processing. Polymers typically have intrinsic thermal conductivity much lower than those for metals or ceramic materials, and therefore are good thermal insulators. Further enhancement of this thermal insulating quality can be achieved by foaming polymers. In other applications which require higher thermal conductivity, such as in electronic packaging and encapsulations, satellite devices, and in areas where good heat dissipation, low thermal expansion and light weight are needed, polymers reinforced with fillers, organic or inorganic, are becoming more and more common in producing advanced polymer composites for these applications (Hodgin & Estes, 1999; Tavman, 2004; Lee & Eun, 2004; Liu & Mather, 2004; Ishida & Heights, 1999; Frank & Phillip, 2002; Hermansen, 2001; Ishida, 2000). Most polymeric materials are processed and fabricated at elevated temperatures, often above their melting temperatures. This process may be long and expensive because of the low thermal conductivity of polymers. Subsequently, the cooling process or annealing may also be controlled by heat transport properties of polymers, which eventually affect the physical properties of the materials. One example is crystalline polymers, for which the structural and morphological features may be significantly changed with the speed of cooling. Careful consideration in designing polymer processing is vital to

For one-dimensional and rectilinear heat flow, the steady-state heat transfer in polymeric

ൌ െ ୢ୲

where q is the heat flux (i.e., the heat transfer rate per unit area normal to the direction of flow), x is the thickness of the material, dT/dx is the temperature gradient per unit length, and the proportionality constant k is known as the thermal conductivity. The units for thermal conductivity k are expressed as W/(m K) in SI units, Btu in./(ft2 h ᵒF) in English units, and cal/(cm s Ԩ) in cgs units. The corresponding units for heat flux are expressed as

Heat transfer involves the transport of energy from one place to another by energy carriers. In a gas phase, gas molecules carry energy either by random molecular motion (diffusion) or by

materials can be described by the Fourier's law of heat conduction:

W/(m2), Btu/(ft2 h), and cal/(cm2 s), respectively.

**1. Introduction** 

achieve desired properties.


## **Thermal Conductivity of Nanoparticles Filled Polymers**

Hassan Ebadi-Dehaghani and Monireh Nazempour *Shahreza Branch, Islamic Azad University Iran* 

## **1. Introduction**

518 Smart Nanoparticles Technology

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Chem. Phys. 121, 198 (2010).

Thermal conductivity of polymers is an important thermal property for both polymer applications and processing. Polymers typically have intrinsic thermal conductivity much lower than those for metals or ceramic materials, and therefore are good thermal insulators. Further enhancement of this thermal insulating quality can be achieved by foaming polymers. In other applications which require higher thermal conductivity, such as in electronic packaging and encapsulations, satellite devices, and in areas where good heat dissipation, low thermal expansion and light weight are needed, polymers reinforced with fillers, organic or inorganic, are becoming more and more common in producing advanced polymer composites for these applications (Hodgin & Estes, 1999; Tavman, 2004; Lee & Eun, 2004; Liu & Mather, 2004; Ishida & Heights, 1999; Frank & Phillip, 2002; Hermansen, 2001; Ishida, 2000). Most polymeric materials are processed and fabricated at elevated temperatures, often above their melting temperatures. This process may be long and expensive because of the low thermal conductivity of polymers. Subsequently, the cooling process or annealing may also be controlled by heat transport properties of polymers, which eventually affect the physical properties of the materials. One example is crystalline polymers, for which the structural and morphological features may be significantly changed with the speed of cooling. Careful consideration in designing polymer processing is vital to achieve desired properties.

For one-dimensional and rectilinear heat flow, the steady-state heat transfer in polymeric materials can be described by the Fourier's law of heat conduction:

$$\mathbf{q} = -\mathbf{k}\frac{\mathbf{d}\mathbf{t}}{\mathbf{d}\mathbf{x}}\tag{1}$$

where q is the heat flux (i.e., the heat transfer rate per unit area normal to the direction of flow), x is the thickness of the material, dT/dx is the temperature gradient per unit length, and the proportionality constant k is known as the thermal conductivity. The units for thermal conductivity k are expressed as W/(m K) in SI units, Btu in./(ft2 h ᵒF) in English units, and cal/(cm s Ԩ) in cgs units. The corresponding units for heat flux are expressed as W/(m2), Btu/(ft2 h), and cal/(cm2 s), respectively.

Heat transfer involves the transport of energy from one place to another by energy carriers. In a gas phase, gas molecules carry energy either by random molecular motion (diffusion) or by

Thermal Conductivity of Nanoparticles Filled Polymers 521

Several methods, as reviewed elsewhere (Tritt & Weston, 2004) and (Rides et al., 2009), have been proposed and used for measurement of the thermal conductivity of polymers and composites. Classical steady-state methods measure the temperature difference across the specimens in response to an applied heating power, either as an absolute value or by comparison with a reference material put in series or in parallel to the sample to be measured. However, these methods are often time consuming and require relatively bulky

Several non steady-state methods have also been developed, including hot wire and hot plate methods, temperature wave method and laser flash techniques (Nunes dos Santos, 2007). Among these, laser-flash thermal diffusivity measurement is widely used, being a relatively fast method, using small specimens (Nunes dos Santos, 2007), (Nunes dos Santos, 2005) and (Gaal et al., 2004). In this method, the sample surface is irradiated with a very short laser pulse and the temperature rise is measured on the opposite side of the specimen, permitting calculation of the thermal diffusivity of the material, after proper mathematical

 *k*=*αCpρ* (3)

Differential scanning calorimetry (DSC) methods may also be used, applying an oscillary (Marcus & Blaine, 1994) or step temperature profile (Merzlyakov & Schick, 2001) and

Significant experimental error may be involved in thermal conductivity measurements, due to difficulties in controlling the test conditions, such as the thermal contact resistance with the sample, leading to accuracy of thermal conductivity measurements typically in the range of 5–10%. In indirect methods, such as those calculating the thermal conductivity from the thermal diffusivity, experimental errors on density and heat capacity values will also

Several different models developed to predict the thermal conductivity of traditional polymer composites are reviewed elsewhere (Bigg, 1995), (Zhou et al., 2007), (Zeng et al.,

The two basic models representing the upper bound and the lower bound for thermal conductivity of composites are the rule of mixture and the so-called series model, respectively. In the rule of mixture model, also referred to as the parallel model, each phase is assumed to contribute independently to the overall conductivity, proportionally to its

kc=kpΦp+kmΦm (4)

elaboration. The thermal conductivity k is then calculated according to Eq. (3):

contribute to the experimental error in the thermal conductivity.

2009) and (Wang et al., 2008). The fundamentals are recalled in this section.

**3.2 Modeling of thermal conductivity in composites** 

where *α*, *Cp* and *ρ* are the thermal diffusivity, heat capacity and density, respectively.

**3. Thermal conductivity – measurement and modeling** 

**3.1 Methods for thermal conductivity measurements** 

specimens.

analyzing the dynamic response.

volume fraction (Eq. (4)):

an overall drift of the molecules in a certain direction (advection). In liquids, energy can be transported by diffusion and advection of molecules. In solids, phonons, electrons, or photons transport energy. Phonons, quantized modes of vibration occurring in a rigid crystal lattice, are the primary mechanism of heat conduction in most polymers since free movement of electrons is not possible (Majumdar, 1998). In view of theoretical prediction, the Debye equation is usually used to calculate the thermal conductivity of polymers (Han & Fina, 2010).

$$
\lambda = \frac{c\_p \nu l}{3} \tag{2}
$$

where *Cp* is the specific heat capacity per unit volume; *v* is the average phonon velocity; and *l* is the phonon mean free path.

For amorphous polymers, *l* is an extremely small constant (i.e. a few angstroms) due to phonon scattering from numerous defects, leading to a very low thermal conductivity of polymers (Agari et al., 1997). Table 1 displays the thermal conductivities of some polymers (T'Joen et al., 2009), (Hu et al., 2007) and (Speight, 2005).


Table 1. Thermal conductivities of some polymers (T'Joen et al., 2009), (Hu et al., 2007) and (Speight, 2005).

an overall drift of the molecules in a certain direction (advection). In liquids, energy can be transported by diffusion and advection of molecules. In solids, phonons, electrons, or photons transport energy. Phonons, quantized modes of vibration occurring in a rigid crystal lattice, are the primary mechanism of heat conduction in most polymers since free movement of electrons is not possible (Majumdar, 1998). In view of theoretical prediction, the Debye equation is usually used to calculate the thermal conductivity of polymers (Han & Fina, 2010).

ߣ ൌ ௩

where *Cp* is the specific heat capacity per unit volume; *v* is the average phonon velocity; and

For amorphous polymers, *l* is an extremely small constant (i.e. a few angstroms) due to phonon scattering from numerous defects, leading to a very low thermal conductivity of polymers (Agari et al., 1997). Table 1 displays the thermal conductivities of some polymers

Material Thermal Conductivity at 25°C

Low density polyethylene (LDPE) 0.30 High density polyethylene (HDPE) 0.44 Polypropylene (PP) 0.11 Polystyrene (PS) 0.14 Polymethylmethacrylate (PMMA) 0.21 Nylon-6 (PA6) 0.25 Nylon-6.6 (PA66) 0.26 Poly(ethylene terephthalate) (PET) 0.15 Poly(butylene terephthalate) (PBT) 0.29 Polycarbonate (PC) 0.20

copolymer (ABS) 0.33 Polyetheretherketone (PEEK) 0.25 Polyphenylene sulfide (PPS) 0.30 Polysulfone (PSU) 0.22 Polyphenylsulfone (PPSU) 0.35 Polyvinyl chloride (PVC) 0.19 Polyvinylidene difluoride (PVDF) 0.19 Polytetrafluoroethylene (PTFE) 0.27 Poly(ethylene vinyl acetate) (EVA) 0.34 Polyimide, Thermoplastic (PI) 0.11 Poly(dimethylsiloxane) (PDMS) 0.25 Epoxy resin 0.19

Table 1. Thermal conductivities of some polymers (T'Joen et al., 2009), (Hu et al., 2007) and

*l* is the phonon mean free path.

Poly(acrylonitrile-butadiene-styrene)

(Speight, 2005).

(T'Joen et al., 2009), (Hu et al., 2007) and (Speight, 2005).

ଷ (2)

(W/m K)

## **3. Thermal conductivity – measurement and modeling**

## **3.1 Methods for thermal conductivity measurements**

Several methods, as reviewed elsewhere (Tritt & Weston, 2004) and (Rides et al., 2009), have been proposed and used for measurement of the thermal conductivity of polymers and composites. Classical steady-state methods measure the temperature difference across the specimens in response to an applied heating power, either as an absolute value or by comparison with a reference material put in series or in parallel to the sample to be measured. However, these methods are often time consuming and require relatively bulky specimens.

Several non steady-state methods have also been developed, including hot wire and hot plate methods, temperature wave method and laser flash techniques (Nunes dos Santos, 2007). Among these, laser-flash thermal diffusivity measurement is widely used, being a relatively fast method, using small specimens (Nunes dos Santos, 2007), (Nunes dos Santos, 2005) and (Gaal et al., 2004). In this method, the sample surface is irradiated with a very short laser pulse and the temperature rise is measured on the opposite side of the specimen, permitting calculation of the thermal diffusivity of the material, after proper mathematical elaboration. The thermal conductivity k is then calculated according to Eq. (3):

$$k = aC\_{\mathcal{V}}\rho \tag{3}$$

where *α*, *Cp* and *ρ* are the thermal diffusivity, heat capacity and density, respectively.

Differential scanning calorimetry (DSC) methods may also be used, applying an oscillary (Marcus & Blaine, 1994) or step temperature profile (Merzlyakov & Schick, 2001) and analyzing the dynamic response.

Significant experimental error may be involved in thermal conductivity measurements, due to difficulties in controlling the test conditions, such as the thermal contact resistance with the sample, leading to accuracy of thermal conductivity measurements typically in the range of 5–10%. In indirect methods, such as those calculating the thermal conductivity from the thermal diffusivity, experimental errors on density and heat capacity values will also contribute to the experimental error in the thermal conductivity.

#### **3.2 Modeling of thermal conductivity in composites**

Several different models developed to predict the thermal conductivity of traditional polymer composites are reviewed elsewhere (Bigg, 1995), (Zhou et al., 2007), (Zeng et al., 2009) and (Wang et al., 2008). The fundamentals are recalled in this section.

The two basic models representing the upper bound and the lower bound for thermal conductivity of composites are the rule of mixture and the so-called series model, respectively. In the rule of mixture model, also referred to as the parallel model, each phase is assumed to contribute independently to the overall conductivity, proportionally to its volume fraction (Eq. (4)):

$$\mathbf{k}\_{\rm c} = \mathbf{k}\_{\rm p} \boldsymbol{\upPhi}\_{\rm p} + \mathbf{k}\_{\rm m} \boldsymbol{\upPhi}\_{\rm m} \tag{4}$$

Thermal Conductivity of Nanoparticles Filled Polymers 523

real composites may present difficulties due to particle size distribution and particle dispersion in the matrix. However, the basic assumption of separated particles in the effective medium approach is not valid in principle for highly filled composites, where contacts are

Maxwell, using potential theory, obtained an exact solution for the conductivity of randomly distributed and non-interacting homogeneous spheres in a homogeneous

Other theoretical models have attempted to explain the thermal conductivity of two-phased composites. Some of these models, such as those by Bruggeman, Botcher, De Loor, and Ce Wen Nan et al., equations 6 to 9 respectively, have been used for prediction of thermal conductivity of carbon nanotube composites (Bruggeman, 1935; Böttcher, 1952; deLoor,

൫ଵିథ൯

൫ଵିథ൯

ଷିଶథ

In order to take into account fluctuations in thermal conductivity in the composites, Zhi et al. (Zhi et al., 2009) proposed the concept of heat-transfer passages, to model the conduction in regions where interparticle distance is low, applying the series model to "packed-belt" of

Even though these macroscopic approaches may be of interest from the engineering point of view, they deliver little or no information about the physical background of the observed behavior. As an example, very limited interpretation is given to the rapidly increasing conductivity with filler content above a certain filler loading (typically above 30 vol.%), or why the experimental results are so far away from the upper bound conductivity, even for

Attempts to model thermal conductivity taking into account the interfacial thermal resistance between conductive particles and matrix have been reported by several research groups (Nan et al., 1997), (Every et al., 1992), (Dunn & Taya, 1993), (Lipton & Vernescu, 1996) and (Torquato & Rintoul, 1995) and applied particles with different geometries and topologies, including aligned continuous fibers, laminated flat plates, spheres, as well as disoriented ellipsoidal particles. In general, these models provided an improved fit with experimental data for ceramic based composites than models not accounting for interface thermal resistance. These approaches generally assume conductive particles to be isolated in the matrix and take into account the thermal resistance in heat transfer between conductive

಼ ಼൰൨

<sup>ܭ</sup> ൌ ൫ଵାథ൯ ଵିଶథ

<sup>ܭ</sup> ൌ ଷାథ൬

ൌ ܭ

ൌ ܭ

ାଶାଶథ൫ି൯

ାଶିథ൫ି൯ <sup>൨</sup> (9)

<sup>య</sup> (10)

(11)

(12)

(13)

likely to occur, possibly leading to thermally conductive paths (Tavman, 1996).

ܭ ൌ ܭ

medium:

1956; Nan et al., 2004).

conductive particles.

highly percolated systems.

where *kc*, *kp*, *km* are the thermal conductivity of the composite, particle, matrix, respectively, and *Φp*, *Φm* volume fractions of particles and matrix, respectively. The parallel model maximizes the contribution of the conductive phase and implicitly assumes perfect contact between particles in a fully percolating network. This model has some relevance to the case of continuous fiber composites in the direction parallel to fibers, but generally results in very large overestimation for other types of composites.

On the other hand, the basic series model assumes no contact between particles and thus the contribution of particles is confined to the region of matrix embedding the particle. The conductivity of composites accordingly with the series model is predicted by Eq. (5):

$$k\_{\mathcal{C}} = \frac{1}{(\phi\_m + k\_m) + (\phi\_p + k\_p)}\tag{5}$$

Most of the experimental results were found to fall in between the two models. However, the lower bound model is usually closer to the experimental data compared to the rule of mixture (Ebadi-Dehaghani et al., 2011; Bigg, 1995), which brought to a number of different models derived from the basic series model, generally introducing some more complex weighted averages on thermal conductivities and volume fractions of particles and matrix. These so-called second-order models including equations by Hashin and Shtrikman, Hamilton and Crosser, Hatta and Taya, Agari, Cheng and Vachon as well as by Nielsen (Bigg, 1995), (Zhou et al., 2007) and (Okamoto & Ishida 1999), appear to reasonably fit most of the experimental data for composites based on isotropic particles as well as short fibers and flakes with limited aspect ratio, up to loadings of about 30% in volume.

In the case of the geometric mean model, the effective thermal conductivity of the composite is given by:

$$K\_{\mathcal{C}} = K\_m^{\phi\_m} + K\_f^{\phi\_f} \tag{6}$$

Lewis and Nielsen modified the Halpin-Tsai equation (Nielsen et al., 1994) to include the effect of the shape of the particles and the orientation or type of packing for a two-phase system.

$$K\_c = K\_m \left[ \frac{1 + AB \phi\_f}{1 - B \psi \phi\_f} \right] \tag{7}$$

Where

$$B = \frac{\frac{K\_f}{K\_m} \mathbf{1}}{\frac{K\_f}{K\_m} \mathbf{A}} \boldsymbol{\psi} = \mathbf{1} + \left(\frac{\mathbf{1} - \phi\_{\max}}{\phi\_{\max}}\right) \boldsymbol{\phi}\_f \tag{8}$$

The values of A and Фmax were given for many geometric shapes and orientations (Weidenfeller et al., 2004).

This model appears to reasonably fit most of the experimental data for composites based on isotropic particles as well as short fibers and flakes with limited aspect ratio, up to loading of about 30% in volume. For higher loadings, the Nielsen's model appear to best fit the rapid increase of thermal conductivity above 30 vol.%, thanks for the introduction of the maximum packing factor into the fitting equation, despite the evaluation of maximum packing factor in

where *kc*, *kp*, *km* are the thermal conductivity of the composite, particle, matrix, respectively, and *Φp*, *Φm* volume fractions of particles and matrix, respectively. The parallel model maximizes the contribution of the conductive phase and implicitly assumes perfect contact between particles in a fully percolating network. This model has some relevance to the case of continuous fiber composites in the direction parallel to fibers, but generally results in very

On the other hand, the basic series model assumes no contact between particles and thus the contribution of particles is confined to the region of matrix embedding the particle. The

ሺథାሻା൫థା൯

Most of the experimental results were found to fall in between the two models. However, the lower bound model is usually closer to the experimental data compared to the rule of mixture (Ebadi-Dehaghani et al., 2011; Bigg, 1995), which brought to a number of different models derived from the basic series model, generally introducing some more complex weighted averages on thermal conductivities and volume fractions of particles and matrix. These so-called second-order models including equations by Hashin and Shtrikman, Hamilton and Crosser, Hatta and Taya, Agari, Cheng and Vachon as well as by Nielsen (Bigg, 1995), (Zhou et al., 2007) and (Okamoto & Ishida 1999), appear to reasonably fit most of the experimental data for composites based on isotropic particles as well as short fibers

In the case of the geometric mean model, the effective thermal conductivity of the composite

Lewis and Nielsen modified the Halpin-Tsai equation (Nielsen et al., 1994) to include the effect of the shape of the particles and the orientation or type of packing for a two-phase

ܭ థ థ

> ଵାథ ଵିటథ

߰ ൌ ͳ ቀଵିథೌೣ

The values of A and Фmax were given for many geometric shapes and orientations

This model appears to reasonably fit most of the experimental data for composites based on isotropic particles as well as short fibers and flakes with limited aspect ratio, up to loading of about 30% in volume. For higher loadings, the Nielsen's model appear to best fit the rapid increase of thermal conductivity above 30 vol.%, thanks for the introduction of the maximum packing factor into the fitting equation, despite the evaluation of maximum packing factor in

ܭ ൌ ܭ

ܭ ൌ ܭ

ൌ ܤ

಼ ಼ିଵ ಼ ಼ି (5)

(6)

൨ (7)

థೌೣ<sup>మ</sup> ቁ ߶ (8)

conductivity of composites accordingly with the series model is predicted by Eq. (5):

݇ ൌ <sup>ଵ</sup>

and flakes with limited aspect ratio, up to loadings of about 30% in volume.

large overestimation for other types of composites.

is given by:

system.

Where

(Weidenfeller et al., 2004).

real composites may present difficulties due to particle size distribution and particle dispersion in the matrix. However, the basic assumption of separated particles in the effective medium approach is not valid in principle for highly filled composites, where contacts are likely to occur, possibly leading to thermally conductive paths (Tavman, 1996).

Maxwell, using potential theory, obtained an exact solution for the conductivity of randomly distributed and non-interacting homogeneous spheres in a homogeneous medium:

$$K\_c = K\_m \left[ \frac{K\_f + 2K\_m + 2\phi\_f (K\_f - K\_m)}{K\_f + 2K\_m - \phi\_f (K\_f - K\_m)} \right] \tag{9}$$

Other theoretical models have attempted to explain the thermal conductivity of two-phased composites. Some of these models, such as those by Bruggeman, Botcher, De Loor, and Ce Wen Nan et al., equations 6 to 9 respectively, have been used for prediction of thermal conductivity of carbon nanotube composites (Bruggeman, 1935; Böttcher, 1952; deLoor, 1956; Nan et al., 2004).

$$K\_{\mathcal{C}} = \frac{\kappa\_m}{\left(1 - \phi\_f\right)^3} \tag{10}$$

$$K\_c = \frac{K\_m}{\left(1 - \phi\_f\right)}\tag{11}$$

$$K\_c = \frac{K\_m(1+\phi\_f)}{1-2\phi\_f} \tag{12}$$

$$K\_c = \frac{K\_m \left[3 + \phi\_f \left(\frac{K\_f}{K\_m}\right)\right]}{3 - 2\phi\_f} \tag{13}$$

In order to take into account fluctuations in thermal conductivity in the composites, Zhi et al. (Zhi et al., 2009) proposed the concept of heat-transfer passages, to model the conduction in regions where interparticle distance is low, applying the series model to "packed-belt" of conductive particles.

Even though these macroscopic approaches may be of interest from the engineering point of view, they deliver little or no information about the physical background of the observed behavior. As an example, very limited interpretation is given to the rapidly increasing conductivity with filler content above a certain filler loading (typically above 30 vol.%), or why the experimental results are so far away from the upper bound conductivity, even for highly percolated systems.

Attempts to model thermal conductivity taking into account the interfacial thermal resistance between conductive particles and matrix have been reported by several research groups (Nan et al., 1997), (Every et al., 1992), (Dunn & Taya, 1993), (Lipton & Vernescu, 1996) and (Torquato & Rintoul, 1995) and applied particles with different geometries and topologies, including aligned continuous fibers, laminated flat plates, spheres, as well as disoriented ellipsoidal particles. In general, these models provided an improved fit with experimental data for ceramic based composites than models not accounting for interface thermal resistance. These approaches generally assume conductive particles to be isolated in the matrix and take into account the thermal resistance in heat transfer between conductive

Thermal Conductivity of Nanoparticles Filled Polymers 525

& Yamaoka, 1995), while amorphous polymers display temperature dependence similar to that obtained for inorganic glasses with no maximum, but a significant plateau region at low temperature range (Reese, 1969). The thermal conductivity of an amorphous polymer increases with increasing temperature to the glass transition temperature (*Tg*), while it decreases above *Tg* (Zhong et al., 2001) and (Dashora & Gupta, 1996). The study of the thermal conductivity of some amorphous and partially crystalline polymers (PE, PS, PTFE and epoxy resin) as a function of temperature in a common-use range (273–373 K) indicates that the conductivity of amorphous polymers increases with temperature and that the conductivity is significantly higher in crystalline than amorphous regions (Kline, 1961).

From the general overview given in the preceding, it appears that very limited thermal conductivity is usually characteristic of polymers. On the other hand, there are many reasons to increase thermal conductivity of polymer-based materials in various industrial applications including circuit boards in power electronics, heat exchangers, electronics appliances and machinery. This justifies the recent significant research efforts on thermally

Many applications would benefit from the use of polymers with enhanced thermal conductivity. For example, when used as heat sinks in electric or electronic systems, composites with a thermal conductivity approximately from 1 to 30 W/m K are required (King et al., 1999). The thermal conductivity of polymers has been traditionally enhanced by the addition of thermally conductive fillers, including graphite, carbon black, carbon fibers, ceramic or metal particles (see Table 2) (Pierson, 1993), (Wypych, 2000), (Fischer, 2006),

**Material Thermal Conductivity at 25 °C** 

Graphite 100 400 (on plane) Carbon black 6 174 Carbon Nanotubes 2000 6000 Diamond 2000

PAN-based Carbon Fibre 8 70 (along the axis) Pitch-based Carbon Fibre 530 1100 (along the axis)

Table 2. Thermal conductivities of some thermally conductive fillers (Pierson, 1993),

(Wypych, 2000), (Fischer, 2006), (Wolff & Wang, 1993) and (Kelly, 1981).

Copper 483 Silver 450 Gold 345 Aluminum 204 Nickel 158 Boron Nitride 250 300 Aluminum nitride 200 Beryllium oxide 260 Aluminum oxide 20 29

**(W/m K)** 

conductive composite materials to overcome the limitations of traditional polymers.

**5. Fillers for thermally conductive composites** 

particle and matrix, also known as Kapitza resistance, from the name of the discoverer of the temperature discontinuity at the metal–liquid interface. A very simple proof of thermal interfacial resistance is the fact that a thermal conductivity lower than the reference matrix was experimentally found with some composites containing particles with thermal conductivity higher than the matrix (Nan et al., 1997) and (Every et al., 1992). This phenomenon is explained by the very low efficiency of heat transfer between particles and matrix, so that the higher thermal conductivity of the filler cannot be taken into advantage and the composite behaves like a hollow material, thus reducing its conductivity compared to the dense reference matrix. Evaluation of the effective thermal conductivity of composite polymers by considering the filler size distribution law was investigated by Holotescu et al (Holotescu et al., 2009).

They presented an empirical model for the effective thermal conductivity (ETC) of a polymer composite that includes dependency on the filler size distribution—chosen as the Rosin-Rammler distribution. The ETC is determined based on certain hypotheses that connect the behavior of a real composite material A, to that of a model composite material B, filled with mono-dimensional filler. The application of these hypotheses to the Maxwell model for ETC is presented. The validation of the new model and its characteristic equation was carried out using experimental data from the reference. The comparison showed that by using the size distribution law a very good fit between the equation of the new model (the size distribution model for the ETC) and the reference experimental results is obtained, even for high volume fractions, up to about 50%.

## **4. Crystallinity and temperature dependence**

Polymer crystallinity strongly affects their thermal conductivity, which roughly varies from 0.2 W/m K for amorphous polymers such as polymethylmethacrylate (PMMA) or polystyrene (PS), to 0.5 W/m K for highly crystalline polymers as high-density polyethylene (HDPE) (Hu et al., 2007). The thermal conductivity of semi-crystalline polymers is reported to increase with crystallinity. As an example, the thermal conductivity of polytetrafluoroethylene (PTFE) was found to increase linearly with crystallinity at 232 °C (Price & Jarratt, 2002).

However, there is a large scatter in the reported experimental data of thermal conductivity of crystalline polymers, even including some contradictory results. It should be noticed that the thermal conductivities of polymers depend on many factors, such as chemical constituents, bond strength, structure type, side group molecular weight, molecular density distribution, type and strength of defects or structural faults, size of intermediate range order, processing conditions and temperature. Furthermore, due to the phonon scattering at the interface between the amorphous and crystalline phase and complex factors on crystallinity of polymer, the prediction of the thermal conductivity vs. crystallinity presents a significant degree of complexity (Han & Fina, 2010).

Semicrystalline and amorphous polymers also vary considerably in the temperature dependence of the thermal conductivity. At low temperature, semicrystalline polymers display a temperature dependence similar to that obtained from highly imperfect crystals, having a maximum in the temperature range near 100 K, shifting to lower temperatures and higher thermal conductivities as the crystallinity increases (Greig & Hardy, 1981) and (Yano

particle and matrix, also known as Kapitza resistance, from the name of the discoverer of the temperature discontinuity at the metal–liquid interface. A very simple proof of thermal interfacial resistance is the fact that a thermal conductivity lower than the reference matrix was experimentally found with some composites containing particles with thermal conductivity higher than the matrix (Nan et al., 1997) and (Every et al., 1992). This phenomenon is explained by the very low efficiency of heat transfer between particles and matrix, so that the higher thermal conductivity of the filler cannot be taken into advantage and the composite behaves like a hollow material, thus reducing its conductivity compared to the dense reference matrix. Evaluation of the effective thermal conductivity of composite polymers by considering the filler size distribution law was investigated by Holotescu et al

They presented an empirical model for the effective thermal conductivity (ETC) of a polymer composite that includes dependency on the filler size distribution—chosen as the Rosin-Rammler distribution. The ETC is determined based on certain hypotheses that connect the behavior of a real composite material A, to that of a model composite material B, filled with mono-dimensional filler. The application of these hypotheses to the Maxwell model for ETC is presented. The validation of the new model and its characteristic equation was carried out using experimental data from the reference. The comparison showed that by using the size distribution law a very good fit between the equation of the new model (the size distribution model for the ETC) and the reference experimental results is obtained, even

Polymer crystallinity strongly affects their thermal conductivity, which roughly varies from 0.2 W/m K for amorphous polymers such as polymethylmethacrylate (PMMA) or polystyrene (PS), to 0.5 W/m K for highly crystalline polymers as high-density polyethylene (HDPE) (Hu et al., 2007). The thermal conductivity of semi-crystalline polymers is reported to increase with crystallinity. As an example, the thermal conductivity of polytetrafluoroethylene (PTFE) was found to increase linearly with crystallinity at 232 °C

However, there is a large scatter in the reported experimental data of thermal conductivity of crystalline polymers, even including some contradictory results. It should be noticed that the thermal conductivities of polymers depend on many factors, such as chemical constituents, bond strength, structure type, side group molecular weight, molecular density distribution, type and strength of defects or structural faults, size of intermediate range order, processing conditions and temperature. Furthermore, due to the phonon scattering at the interface between the amorphous and crystalline phase and complex factors on crystallinity of polymer, the prediction of the thermal conductivity vs. crystallinity presents

Semicrystalline and amorphous polymers also vary considerably in the temperature dependence of the thermal conductivity. At low temperature, semicrystalline polymers display a temperature dependence similar to that obtained from highly imperfect crystals, having a maximum in the temperature range near 100 K, shifting to lower temperatures and higher thermal conductivities as the crystallinity increases (Greig & Hardy, 1981) and (Yano

(Holotescu et al., 2009).

(Price & Jarratt, 2002).

for high volume fractions, up to about 50%.

**4. Crystallinity and temperature dependence** 

a significant degree of complexity (Han & Fina, 2010).

& Yamaoka, 1995), while amorphous polymers display temperature dependence similar to that obtained for inorganic glasses with no maximum, but a significant plateau region at low temperature range (Reese, 1969). The thermal conductivity of an amorphous polymer increases with increasing temperature to the glass transition temperature (*Tg*), while it decreases above *Tg* (Zhong et al., 2001) and (Dashora & Gupta, 1996). The study of the thermal conductivity of some amorphous and partially crystalline polymers (PE, PS, PTFE and epoxy resin) as a function of temperature in a common-use range (273–373 K) indicates that the conductivity of amorphous polymers increases with temperature and that the conductivity is significantly higher in crystalline than amorphous regions (Kline, 1961).

From the general overview given in the preceding, it appears that very limited thermal conductivity is usually characteristic of polymers. On the other hand, there are many reasons to increase thermal conductivity of polymer-based materials in various industrial applications including circuit boards in power electronics, heat exchangers, electronics appliances and machinery. This justifies the recent significant research efforts on thermally conductive composite materials to overcome the limitations of traditional polymers.

## **5. Fillers for thermally conductive composites**

Many applications would benefit from the use of polymers with enhanced thermal conductivity. For example, when used as heat sinks in electric or electronic systems, composites with a thermal conductivity approximately from 1 to 30 W/m K are required (King et al., 1999). The thermal conductivity of polymers has been traditionally enhanced by the addition of thermally conductive fillers, including graphite, carbon black, carbon fibers, ceramic or metal particles (see Table 2) (Pierson, 1993), (Wypych, 2000), (Fischer, 2006),


Table 2. Thermal conductivities of some thermally conductive fillers (Pierson, 1993), (Wypych, 2000), (Fischer, 2006), (Wolff & Wang, 1993) and (Kelly, 1981).

Thermal Conductivity of Nanoparticles Filled Polymers 527

graphite platelets and the morphology of the nanocomposites. The thermal conductivity of these composites was investigated by three different methods, namely, by DSC, modified hot wire, and halogen flash lamp methods. The addition of small amounts of exfoliated graphite flakes showed a marked improvement in thermal and electrical conductivity of the

Carbon fiber, typically vapor grown carbon fiber (VGCF), is another important carbon-based filler. Polymer/VGCF composites have been reviewed by Tibbetts et al. (Tibbetts et al., 2007). Since VGCF is composed of an annular geometry parallel to the fiber axis, thermal conductive properties along the fiber axis are very different from the transverse direction (estimated up to 2000 W/m K in the axial direction vs. 10–110 W/m K in the transverse direction (Chen & Ting, 2002) and (Zhang et al, 2000)), directly affecting the thermal conductivity of aligned composites (Mohammed & Uttandaraman, 2009) and (Kuriger et al.,

Carbon black particles are aggregates of graphite microcrystals and characteristic of their particle size (10–500 nm) and surface area (25–150 m2/g) (Pierson, 1993). Carbon black is reported to contribute to electrical conductivity rather than thermal conductivity (Wong et

The filling of a polymer with metallic particles may result in both increase of thermal conductivity and electrical conductivity in the composites. However, a density increase is also obtained when adding significant metal loadings to the polymer matrix, thus limiting applications when lightweight is required. Metallic particles used for thermal conductivity improvement include powders of aluminum, silver, copper and nickel. Boudenne et al studied the thermal behavior of polypropylene filled with copper particles (Kumlutaş et al., 2003). In this work thermal conductivity, diffusivity, effusivity and specific heat of polypropylene matrix filled with copper particles of two different sizes were investigated. A parallel study of the evolution of the electrical conductivity was also carried out. The highest heat transport ability was observed for the composites filled with the smaller particles. The Agari's model provides a good estimation of the thermal conductivity of composites for all filler concentrations. Polymers modified with the inclusion of metallic particles include polyethylene (Kumlutaş et al., 2003), polypropylene (Boudenne et al., 2005), polyamide (Tekce et al., 2007), polyvinylchloride and epoxy resins (Mamunya et al., 2002), showing thermal conductivity performance depending on the thermal conductivity of the metallic fillers, the particle shape and size, the volume fraction and spatial arrangement in the polymer matrix. Thermal conductivity of metal powder-polymer feedstock for powder

injection moulding was studied by Kowalski et al. (Kowalski et al., 1999).

Thermal conductivity of a powder injection molding feedstock (mixture of metal powders and polymers) in solid and molten states has been measured by using the laser flash method. The filler material was 316L stainless steel powder and its content in the mixture amounted 60% by volume. An attempt has been made to employ two most promising existing mathematical models (theoretical Maxwell- and semi-theoretical Lewis & Nielsen model) to calculate the thermal conductivity of the mixture (see section 1.3.2). Comparison of the experimental and calculated results has revealed that the Lewis & Nielsen model

al., 2001), (Abdel-Aal et al., 2008) and (King et al., 2006).

composites.

2002).

**5.2 Metallic fillers** 

(Wolff & Wang, 1993) and (Kelly, 1981). It is worth noticing that significant scatter of data are typically reported for thermal conductivity of fillers. This is caused by several factors, including filler purity, crystallinity, particle size and measurement method. It is also important to point out that some materials, typically fibers and layers, are highly anisotropic and can show much higher conductivity along a main axis or on a plane, compared to perpendicular direction.

High filler loadings (>30 vol.%) are typically necessary to achieve the appropriate level of thermal conductivity in thermally conductive polymer composites, which represents a significant processing challenge. Indeed, the processing requirements, such as possibility to be extruded and injection molded, often limit the amount of fillers in the formulation and, consequently, the thermal conductivity performance (King et al., 2008). Moreover, high inorganic filler loading dramatically alters the polymer mechanical behavior and density. For these reasons, obtaining composites having thermal conductivities higher than 4 W/m K and usual polymer processability is very challenging at present (Han & Fina, 2010).

## **5.1 Carbon-based fillers**

Carbon-based fillers appear to be the best promising fillers, coupling high thermal conductivity and lightweight. Graphite, carbon fiber and carbon black are well-known traditional carbon-based fillers. Graphite is usually recognized as the best conductive filler because of its good thermal conductivity, low cost and fair dispersability in polymer matrix (Causin et al., 2006) and (Tu & Ye, 2009). Single graphene sheets constituting graphite show intrinsically high thermal conductivity of about 800 W/m K (Liu et al., 2008) or higher (theoretically estimated to be as high as 5300 W/m K ( Veca et al., 2009) and (Stankovich et al., 2006)), this determining the high thermal conductivity of graphite, usually reported in the range from 100 to 400 W/m K. Expanded graphite (EG), an exfoliated form of graphite with layers of 20–100 nm thickness, has also been used in polymer composites (Ganguli et al., 2008), for which the thermal conductivity depends on the exfoliation degree (Park et al., 2008), its dispersion in matrix (Mu & Feng, 2007) and the aspect ratio of the EG (Kalaitzidou et al., 2007).

Thermal conductivity of exfoliated graphite nanocomposites was investigated by Fukushima et al. (Fukushima et al., 2006). Since the late 1990's, research has been reported where intercalated, expanded, and/or exfoliated graphite nanoflakes could also be used as reinforcements in polymer systems. The key point to utilizing graphite as a platelet nanoreinforcement is in the ability to exfoliate graphite using Graphite Intercalated Compounds (GICs). Natural graphite is still abundant and its cost is quite low compared to the other nano–size carbon materials, the cost of producing graphite nanoplatelets is expected to be ~\$5/lb. This is significantly less expensive than single wall nanotubes (SWNT) (>\$45000/lb) or vapor grown carbon fiber (VGCF) (\$40–50/lb), yet the mechanical, electrical, and thermal properties of crystalline graphite flakes are comparable to those of SWNT and VGCF. The use of exfoliated graphite flakes (xGnP) opens up many new applications where electromagnetic shielding, high thermal conductivity, gas barrier resistance or low flammability are required. A special thermal treatment was developed to exfoliate graphite flakes for the production of nylon and high density polypropylene nanocomposites. X-ray diffraction (XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM) were used to assess the degree of exfoliation of the graphite platelets and the morphology of the nanocomposites. The thermal conductivity of these composites was investigated by three different methods, namely, by DSC, modified hot wire, and halogen flash lamp methods. The addition of small amounts of exfoliated graphite flakes showed a marked improvement in thermal and electrical conductivity of the composites.

Carbon fiber, typically vapor grown carbon fiber (VGCF), is another important carbon-based filler. Polymer/VGCF composites have been reviewed by Tibbetts et al. (Tibbetts et al., 2007). Since VGCF is composed of an annular geometry parallel to the fiber axis, thermal conductive properties along the fiber axis are very different from the transverse direction (estimated up to 2000 W/m K in the axial direction vs. 10–110 W/m K in the transverse direction (Chen & Ting, 2002) and (Zhang et al, 2000)), directly affecting the thermal conductivity of aligned composites (Mohammed & Uttandaraman, 2009) and (Kuriger et al., 2002).

Carbon black particles are aggregates of graphite microcrystals and characteristic of their particle size (10–500 nm) and surface area (25–150 m2/g) (Pierson, 1993). Carbon black is reported to contribute to electrical conductivity rather than thermal conductivity (Wong et al., 2001), (Abdel-Aal et al., 2008) and (King et al., 2006).

## **5.2 Metallic fillers**

526 Smart Nanoparticles Technology

(Wolff & Wang, 1993) and (Kelly, 1981). It is worth noticing that significant scatter of data are typically reported for thermal conductivity of fillers. This is caused by several factors, including filler purity, crystallinity, particle size and measurement method. It is also important to point out that some materials, typically fibers and layers, are highly anisotropic and can show much higher conductivity along a main axis or on a plane, compared to

High filler loadings (>30 vol.%) are typically necessary to achieve the appropriate level of thermal conductivity in thermally conductive polymer composites, which represents a significant processing challenge. Indeed, the processing requirements, such as possibility to be extruded and injection molded, often limit the amount of fillers in the formulation and, consequently, the thermal conductivity performance (King et al., 2008). Moreover, high inorganic filler loading dramatically alters the polymer mechanical behavior and density. For these reasons, obtaining composites having thermal conductivities higher than 4 W/m K

Carbon-based fillers appear to be the best promising fillers, coupling high thermal conductivity and lightweight. Graphite, carbon fiber and carbon black are well-known traditional carbon-based fillers. Graphite is usually recognized as the best conductive filler because of its good thermal conductivity, low cost and fair dispersability in polymer matrix (Causin et al., 2006) and (Tu & Ye, 2009). Single graphene sheets constituting graphite show intrinsically high thermal conductivity of about 800 W/m K (Liu et al., 2008) or higher (theoretically estimated to be as high as 5300 W/m K ( Veca et al., 2009) and (Stankovich et al., 2006)), this determining the high thermal conductivity of graphite, usually reported in the range from 100 to 400 W/m K. Expanded graphite (EG), an exfoliated form of graphite with layers of 20–100 nm thickness, has also been used in polymer composites (Ganguli et al., 2008), for which the thermal conductivity depends on the exfoliation degree (Park et al., 2008), its dispersion in matrix (Mu & Feng, 2007) and the aspect ratio of the EG (Kalaitzidou

Thermal conductivity of exfoliated graphite nanocomposites was investigated by Fukushima et al. (Fukushima et al., 2006). Since the late 1990's, research has been reported where intercalated, expanded, and/or exfoliated graphite nanoflakes could also be used as reinforcements in polymer systems. The key point to utilizing graphite as a platelet nanoreinforcement is in the ability to exfoliate graphite using Graphite Intercalated Compounds (GICs). Natural graphite is still abundant and its cost is quite low compared to the other nano–size carbon materials, the cost of producing graphite nanoplatelets is expected to be ~\$5/lb. This is significantly less expensive than single wall nanotubes (SWNT) (>\$45000/lb) or vapor grown carbon fiber (VGCF) (\$40–50/lb), yet the mechanical, electrical, and thermal properties of crystalline graphite flakes are comparable to those of SWNT and VGCF. The use of exfoliated graphite flakes (xGnP) opens up many new applications where electromagnetic shielding, high thermal conductivity, gas barrier resistance or low flammability are required. A special thermal treatment was developed to exfoliate graphite flakes for the production of nylon and high density polypropylene nanocomposites. X-ray diffraction (XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM) were used to assess the degree of exfoliation of the

and usual polymer processability is very challenging at present (Han & Fina, 2010).

perpendicular direction.

**5.1 Carbon-based fillers** 

et al., 2007).

The filling of a polymer with metallic particles may result in both increase of thermal conductivity and electrical conductivity in the composites. However, a density increase is also obtained when adding significant metal loadings to the polymer matrix, thus limiting applications when lightweight is required. Metallic particles used for thermal conductivity improvement include powders of aluminum, silver, copper and nickel. Boudenne et al studied the thermal behavior of polypropylene filled with copper particles (Kumlutaş et al., 2003). In this work thermal conductivity, diffusivity, effusivity and specific heat of polypropylene matrix filled with copper particles of two different sizes were investigated. A parallel study of the evolution of the electrical conductivity was also carried out. The highest heat transport ability was observed for the composites filled with the smaller particles. The Agari's model provides a good estimation of the thermal conductivity of composites for all filler concentrations. Polymers modified with the inclusion of metallic particles include polyethylene (Kumlutaş et al., 2003), polypropylene (Boudenne et al., 2005), polyamide (Tekce et al., 2007), polyvinylchloride and epoxy resins (Mamunya et al., 2002), showing thermal conductivity performance depending on the thermal conductivity of the metallic fillers, the particle shape and size, the volume fraction and spatial arrangement in the polymer matrix. Thermal conductivity of metal powder-polymer feedstock for powder injection moulding was studied by Kowalski et al. (Kowalski et al., 1999).

Thermal conductivity of a powder injection molding feedstock (mixture of metal powders and polymers) in solid and molten states has been measured by using the laser flash method. The filler material was 316L stainless steel powder and its content in the mixture amounted 60% by volume. An attempt has been made to employ two most promising existing mathematical models (theoretical Maxwell- and semi-theoretical Lewis & Nielsen model) to calculate the thermal conductivity of the mixture (see section 1.3.2). Comparison of the experimental and calculated results has revealed that the Lewis & Nielsen model

Thermal Conductivity of Nanoparticles Filled Polymers 529

nanocomposites over conventional micro-composites: (1) low-percolation threshold (about 0.1–2 vol.%), (2) particle–particle correlation (orientation and position) arising at lowvolume fractions (less than 0.001), (3) large number density of particles per particle volume (106 to 108 particles/μm3), (4) extensive interfacial area per volume of particles (103 to 104 m2/ml), (5) short distances between particles (10–50 nm at 1–8 vol.%) and (6) comparable size scales among the rigid nanoparticles inclusion, distance between particles, and the

Different nanoparticles have been used to improve thermal conductivity of polymers. As a few examples, HDPE filled with 7 vol.% nanometer size expanded graphite has a thermal conductivity of 1.59 W/m K, twice that of microcomposites (0.78 W/m K) at the same volume content (Ye et al., 2006). Poly(vinyl butyral) (PVB), PS, PMMA and poly(ethylene vinyl alcohol) (PEVA) based nanocomposites with 24 wt.% boron nitride nanotubes (BNNT) have thermal conductivities of 1.80, 3.61, 3.16 and 2.50 W/m K, respectively (Zhi et al., 2009). Carbon nanofiber was also reported to improve the thermal conductivity of polymer composites (Sui et al., 2008) and (Elgafy & Lafdi, 2005). However, the most widely used and studied nanoparticles for thermal conductivity are certainly carbon nanotubes (either single wall-SWCNT or multiwall-MWCNT), which have attracted growing research interest. Indeed, CNT couples very high thermal conductivity with outstanding aspect ratio, thus

Droval and co-workers (Droval et al., 2006) investigated the effect of boron nitride (BN), talc (Mg3Si4O10 (OH)2), aluminum nitride (AlN) and aluminum oxide (Al2O3) particles, and their impact on thermal properties. Lewis and Nielson, Cheng and Vachon, Agari and Uno models were used to predict the evolution of thermal conductivity with filler content and were found to describe correctly thermal conductivity. Only BN shows a real exponential increase of conductivity over 20% v/v filler. Consequently, in best conditions introducing

A technology has been developed for making carbon-ceramic composite refractories by combining carbon fibers as reinforcing component with a mixture matrix, which allows one to make refractory components of various sizes and geometry, including thin-walled large constructions (Chernenko et al., 2009). The heat resistance of these composite refractories increases with the bulk silicization during ceramic production on a carbon-carbon substrate. The degree of silicization is determined by the volume of the open microporosity of transport type, which is formed by pyrolysis of a polymer coke-forming matrix in the initial carbon plastic. The transport micropores are produced by a modification of the phenolformaldehyde resin additive treatment, which does not give rise to coke on pyrolysis. As a result, the content of open pores in the carbon framework attains 55%, which enables one to make a silicized composite refractory of density up to 2.7 g/cm3 with a compressive strength of 250 – 300 MPa, bending strength 120–140, and tensile strength 60–80 MPa, elastic modulus 120–140 GPa, linear expansion coefficient 3.5×10–6 – 4.5×10–6 K–1, and thermal conductivity 6 – 8 W/(m K). These refractories are widely used in various branches of industry. Thermal conductivity of particle filled polyethylene composite materials was investigated by Kumlutas et al. (Kumlutas et al., 2003). In this study, the effective thermal conductivity of aluminum filled high-density polyethylene composites is investigated numerically as a function of filler concentration. The obtained values are compared with experimental results and the existing theoretical and empirical models. The thermal

30% v/v of BN allows the thermal conductivity to be multiplied by six.

relaxation volume of polymer chains (Han & Fina, 2010).

forming percolating network at very low loadings.

predicts better than Maxwell model the thermal conductivity of the feedstock. As the difference between the calculated (Maxwell model) and the measured results amounts to 15–85%, it is suggested that it can only be used for preliminary assessment of the thermal conductivity of so highly filled composite material. If accurate thermal conductivity data are required (as in case of numerical simulation of the powder injection moulding process), measurement of this property has to be performed if meaningful simulation results are to be expected.

## **5.3 Ceramic fillers**

Ceramic powder reinforced polymer materials have been used extensively as electronic materials. Being aware of the high electrical conductivity of metallic particles, several ceramic materials such as aluminum nitride (AlN), boron nitride (BN), silicon carbide (SiC) and beryllium oxide (BeO) gained more attention as thermally conductive fillers due to their high thermal conductivity and electrical resistivity (Nu et al., 2008) and (Ishida & Rimdusit, 1998). Thermal conductivities of composites with ceramic filler are influenced by filler packing density(Ohashi et al., 2005), particle size and size distribution (Yu et al., 2002) and (Mu et al., 2007), surface treatment (Gu et al., 2009) and mixing methods (Zhou et al., 2007). Models and theories for predicting the thermal conductivity of polymer composites were discussed. Effective Medium Theory (EMT), Agari model and Nielsen model respectively are introduced and are applied as predictions for the thermal conductivity of ceramic particle filled polymer composites. Thermal conductivity of experimentally prepared Si3N4/epoxy composite and some data cited from the literature are discussed using the above theories. Feasibility of the three methods as a prediction in the whole volume fraction region of the filler from 0 to 1 was evaluated for a comparison. As a conclusion: both EMT and Nielsen model can give a well prediction for the thermal conductivity at a low volume fraction of the filler; Agari model give a better prediction in the whole range, but with larger error percentage (He et al., 2007).

## **6. Nanocomposites for thermal conductivity**

Polymer nanocomposites are commonly defined as the combination of a polymer matrix and additives that have at least one dimension in the nanometer range. The additives can be one-dimensional (examples include nanotubes and fibres), two-dimensional (which include layered minerals like clay), or three-dimensional (including spherical particles). Over the past decade, polymer nanocomposites have attracted considerable interests in both academia and industry, owing to their outstanding mechanical properties like elastic stiffness and strength with only a small amount of the nanoadditives. This is caused by the large surface area to volume ratio of nanoadditives when compared to the micro- and macro-additives. Other superior properties of polymer nano-composites include barrier resistance, flame retardancy, scratch/wear resistance, as well as optical, magnetic, thermal conductivity and electrical properties. Polymer based nanocomposites can be obtained by the addition of nanoscale particles which are classified into three categories depending on their dimensions: nanoparticles, nanotubes and nanolayers. The interest in using nanoscaled fillers in polymer matrices is the potential for unique properties deriving from the nanoscopic dimensions and inherent extreme aspect ratios of the nanofillers (Mai et al., 2006). Kumar et al. (Kumar et al., 2009) summarized six interrelated characteristics of

predicts better than Maxwell model the thermal conductivity of the feedstock. As the difference between the calculated (Maxwell model) and the measured results amounts to 15–85%, it is suggested that it can only be used for preliminary assessment of the thermal conductivity of so highly filled composite material. If accurate thermal conductivity data are required (as in case of numerical simulation of the powder injection moulding process), measurement of this property has to be performed if meaningful simulation results are to be

Ceramic powder reinforced polymer materials have been used extensively as electronic materials. Being aware of the high electrical conductivity of metallic particles, several ceramic materials such as aluminum nitride (AlN), boron nitride (BN), silicon carbide (SiC) and beryllium oxide (BeO) gained more attention as thermally conductive fillers due to their high thermal conductivity and electrical resistivity (Nu et al., 2008) and (Ishida & Rimdusit, 1998). Thermal conductivities of composites with ceramic filler are influenced by filler packing density(Ohashi et al., 2005), particle size and size distribution (Yu et al., 2002) and (Mu et al., 2007), surface treatment (Gu et al., 2009) and mixing methods (Zhou et al., 2007). Models and theories for predicting the thermal conductivity of polymer composites were discussed. Effective Medium Theory (EMT), Agari model and Nielsen model respectively are introduced and are applied as predictions for the thermal conductivity of ceramic particle filled polymer composites. Thermal conductivity of experimentally prepared Si3N4/epoxy composite and some data cited from the literature are discussed using the above theories. Feasibility of the three methods as a prediction in the whole volume fraction region of the filler from 0 to 1 was evaluated for a comparison. As a conclusion: both EMT and Nielsen model can give a well prediction for the thermal conductivity at a low volume fraction of the filler; Agari model give a better prediction in the whole range, but with larger

Polymer nanocomposites are commonly defined as the combination of a polymer matrix and additives that have at least one dimension in the nanometer range. The additives can be one-dimensional (examples include nanotubes and fibres), two-dimensional (which include layered minerals like clay), or three-dimensional (including spherical particles). Over the past decade, polymer nanocomposites have attracted considerable interests in both academia and industry, owing to their outstanding mechanical properties like elastic stiffness and strength with only a small amount of the nanoadditives. This is caused by the large surface area to volume ratio of nanoadditives when compared to the micro- and macro-additives. Other superior properties of polymer nano-composites include barrier resistance, flame retardancy, scratch/wear resistance, as well as optical, magnetic, thermal conductivity and electrical properties. Polymer based nanocomposites can be obtained by the addition of nanoscale particles which are classified into three categories depending on their dimensions: nanoparticles, nanotubes and nanolayers. The interest in using nanoscaled fillers in polymer matrices is the potential for unique properties deriving from the nanoscopic dimensions and inherent extreme aspect ratios of the nanofillers (Mai et al., 2006). Kumar et al. (Kumar et al., 2009) summarized six interrelated characteristics of

expected.

**5.3 Ceramic fillers** 

error percentage (He et al., 2007).

**6. Nanocomposites for thermal conductivity** 

nanocomposites over conventional micro-composites: (1) low-percolation threshold (about 0.1–2 vol.%), (2) particle–particle correlation (orientation and position) arising at lowvolume fractions (less than 0.001), (3) large number density of particles per particle volume (106 to 108 particles/μm3), (4) extensive interfacial area per volume of particles (103 to 104 m2/ml), (5) short distances between particles (10–50 nm at 1–8 vol.%) and (6) comparable size scales among the rigid nanoparticles inclusion, distance between particles, and the relaxation volume of polymer chains (Han & Fina, 2010).

Different nanoparticles have been used to improve thermal conductivity of polymers. As a few examples, HDPE filled with 7 vol.% nanometer size expanded graphite has a thermal conductivity of 1.59 W/m K, twice that of microcomposites (0.78 W/m K) at the same volume content (Ye et al., 2006). Poly(vinyl butyral) (PVB), PS, PMMA and poly(ethylene vinyl alcohol) (PEVA) based nanocomposites with 24 wt.% boron nitride nanotubes (BNNT) have thermal conductivities of 1.80, 3.61, 3.16 and 2.50 W/m K, respectively (Zhi et al., 2009). Carbon nanofiber was also reported to improve the thermal conductivity of polymer composites (Sui et al., 2008) and (Elgafy & Lafdi, 2005). However, the most widely used and studied nanoparticles for thermal conductivity are certainly carbon nanotubes (either single wall-SWCNT or multiwall-MWCNT), which have attracted growing research interest. Indeed, CNT couples very high thermal conductivity with outstanding aspect ratio, thus forming percolating network at very low loadings.

Droval and co-workers (Droval et al., 2006) investigated the effect of boron nitride (BN), talc (Mg3Si4O10 (OH)2), aluminum nitride (AlN) and aluminum oxide (Al2O3) particles, and their impact on thermal properties. Lewis and Nielson, Cheng and Vachon, Agari and Uno models were used to predict the evolution of thermal conductivity with filler content and were found to describe correctly thermal conductivity. Only BN shows a real exponential increase of conductivity over 20% v/v filler. Consequently, in best conditions introducing 30% v/v of BN allows the thermal conductivity to be multiplied by six.

A technology has been developed for making carbon-ceramic composite refractories by combining carbon fibers as reinforcing component with a mixture matrix, which allows one to make refractory components of various sizes and geometry, including thin-walled large constructions (Chernenko et al., 2009). The heat resistance of these composite refractories increases with the bulk silicization during ceramic production on a carbon-carbon substrate. The degree of silicization is determined by the volume of the open microporosity of transport type, which is formed by pyrolysis of a polymer coke-forming matrix in the initial carbon plastic. The transport micropores are produced by a modification of the phenolformaldehyde resin additive treatment, which does not give rise to coke on pyrolysis. As a result, the content of open pores in the carbon framework attains 55%, which enables one to make a silicized composite refractory of density up to 2.7 g/cm3 with a compressive strength of 250 – 300 MPa, bending strength 120–140, and tensile strength 60–80 MPa, elastic modulus 120–140 GPa, linear expansion coefficient 3.5×10–6 – 4.5×10–6 K–1, and thermal conductivity 6 – 8 W/(m K). These refractories are widely used in various branches of industry. Thermal conductivity of particle filled polyethylene composite materials was investigated by Kumlutas et al. (Kumlutas et al., 2003). In this study, the effective thermal conductivity of aluminum filled high-density polyethylene composites is investigated numerically as a function of filler concentration. The obtained values are compared with experimental results and the existing theoretical and empirical models. The thermal

Thermal Conductivity of Nanoparticles Filled Polymers 531

nanocomposites, PP/carbon nanotube composites and PP/nanoclay composites (Han & Fina , 2011; Frormann et al., 2008; Vakili et al., 2011) have been reported. However there are

> PP+10wt% nanofiller

PP+10wt% nanofiller

PP+15wt% nanofiller

PP+15wt% nanofiller

nanofiller

Tm (°C) 167.8 168.5 168.8 167.0 ΔHm (Jg-1) 78.0 91.2 108.9 107.7 Xc (%) 37.7 44.0 52.6 52.0

nanofiller

Tm (°C) 167.8 168.6 168.1 168.4 ΔHm (Jg-1) 78.0 81.4 85.8 104.6 Xc (%) 37.7 39.3 41.4 50.5

Thermal conductivity was measured using a TCA Thermal Conductivity Analyser (TCA-200LT-A, Netzsch, Selb, Germany) with the guarded heat flow meter method. Each compression molded sample (30cm×30cm sheets with 10 mm thickness) was placed between two heated surface controlled at different temperatures with a flow of heat from the hot to the cold surface. When thermal equilibrium was attained thermal conductivity data were taken within an accuracy of 3%. Fig. 1 compares the effect of the nanoparticles' content on the thermal conductivity of the nanocomposites. As seen, the value of thermal conductivity increased with an increase in the nanoparticle concentration up to 64% and 82% for CaCO3 and ZnO respectively. The increase in TC for ZnO nanoparticles is more than CaCO3 due to the nature of nanofiller and also crystallinity degree regarding to DSC results (Table 3). These increases in TC for both nanoparticles are higher than that of reported values for CNF

The values obtained from the experimental study of PP nanocomposites were compared with several TC models (Figs 2.a and 2.b). As seen the experimental results were found to fall in between the Series and Parallel models. However, the lower bound model (series) is

Maxwell, Lewis & Nielson, Bruggeman, Bottcher and De Loor models predict fairly well thermal conductivity values up to 10 wt% for PP/ZnO nanocomposites (Fig. 2.a). In the concentration of 15 wt% no model could predict well the TC values and all of the mentioned models underestimated the TC values of nanocomposite whereas in the case 5 wt% all

Table 3. Crystallization parameters of neat PP and nanocomposites. a) PP/ZnO

some contradicting results in the literature (Zhao & Li, 2006).

Neat PP PP+5wt%

nanocomposite. b) PP/CaCO3 nanocomposite.

**6.1.2 Thermal conductivity measurement** 

in a PP matrix (Frormann et al., 2008).

usually closer to the experimental data.

models overestimated the TC values.

a)

b)

Neat PP PP+5wt%

conductivity is measured by a modified hot-wire technique. For numerical study, the effective thermal conductivity of particle-filled composite was calculated numerically using the micro structural images of them. By identifying each pixel with a finite difference equation and accompanying appropriate image processing, the effective thermal conductivity of composite material is determined numerically. As a result of this study, numerical results, experimental values and all the models are close to each other at low particle content. For particle content greater than 10%, the effective thermal conductivity is exponentially formed. All the models fail to predict thermal conductivity in this region. But, numerical results give satisfactory values in the whole range of aluminum particle content.

#### **6.1 Nanocomposites using inorganic fillers**

Thermally conductive polymer nanocomposites based on polypropylene has been studied (Vakili et al., 2011; Ebadi-Dehaghani et al., 2011). In this study three nanocomposite containing 5 to 15 wt% of ZnO and CaCO3 nanoparticles prepared by extrusion were used. The thermal conductivity (TC) of compression moulded polypropylene (PP) and PP filled nanoparticles was studied using thermal conductivity analyser (TCA). The effect of nanoparticle content and crystallinity on thermal conductivity was investigated using conventional methods like SEM, XRD and DSC. The incorporation of nanoparticles improved crystallinity and thermal conductivity simultaneously. The experimental TC values of PP nanocomposites with different level of nanoparticles concentration showed a linear increase with an increase in crystallinity.

#### **6.1.1 Differential Scanning Calorimetry (DSC)**

DSC measurements were investigated by conventional differential scanning calorimeter Labsys TG (Setaram Instumentation, Caluire, France). A pellet of extruded sample, with a weight of 8-10 mg, was placed into an alumina pan in the presence of air as the furnace atmosphere. Measurements were performed from ambient temperature up to 200°C with heating rate of 10°C/min. The DSC results for pure PP and nanocomposites, The Tm (peak temperature of melting) and ΔHm (enthalpy of melting), are listed in Table 3.

The degree of crystallinity of a specimen can be calculated from the melting heat of crystallization according to the following equation:

$$X\_{\oplus} = \frac{\Delta H\_{\text{m}}}{\Delta H\_{\text{0}}(1 - W\_{\text{f}})} \times 100\,\text{}$$

Where wf is the weight fraction of nanofiller and ΔH0=207.1 Jg-1 is the melting heat of 100% crystalline PP (Bai et al., 1999).

The DSC results indicated that the addition of both nanoparticles to the PP caused only a marginal effect on melting temperature (Tm) and no correlation of the results with the filler concentration could be established. The calculated degree of crystallinity of the PP phase increased with increasing content of both nanoparticles, indicating that the nanofillers nucleated the crystallization process. (Frormann et al., 2008) This implies that the existence of nanoparticles facilitates the crystallization of PP and this effect becomes more evident with higher nanoparticle content (Zhao & Li, 2006). Similar results for PP/CaCO3


nanocomposites, PP/carbon nanotube composites and PP/nanoclay composites (Han & Fina , 2011; Frormann et al., 2008; Vakili et al., 2011) have been reported. However there are some contradicting results in the literature (Zhao & Li, 2006).

b)

530 Smart Nanoparticles Technology

conductivity is measured by a modified hot-wire technique. For numerical study, the effective thermal conductivity of particle-filled composite was calculated numerically using the micro structural images of them. By identifying each pixel with a finite difference equation and accompanying appropriate image processing, the effective thermal conductivity of composite material is determined numerically. As a result of this study, numerical results, experimental values and all the models are close to each other at low particle content. For particle content greater than 10%, the effective thermal conductivity is exponentially formed. All the models fail to predict thermal conductivity in this region. But, numerical results give satisfactory values in the whole range of aluminum particle content.

Thermally conductive polymer nanocomposites based on polypropylene has been studied (Vakili et al., 2011; Ebadi-Dehaghani et al., 2011). In this study three nanocomposite containing 5 to 15 wt% of ZnO and CaCO3 nanoparticles prepared by extrusion were used. The thermal conductivity (TC) of compression moulded polypropylene (PP) and PP filled nanoparticles was studied using thermal conductivity analyser (TCA). The effect of nanoparticle content and crystallinity on thermal conductivity was investigated using conventional methods like SEM, XRD and DSC. The incorporation of nanoparticles improved crystallinity and thermal conductivity simultaneously. The experimental TC values of PP nanocomposites with different level of nanoparticles concentration showed a

DSC measurements were investigated by conventional differential scanning calorimeter Labsys TG (Setaram Instumentation, Caluire, France). A pellet of extruded sample, with a weight of 8-10 mg, was placed into an alumina pan in the presence of air as the furnace atmosphere. Measurements were performed from ambient temperature up to 200°C with heating rate of 10°C/min. The DSC results for pure PP and nanocomposites, The Tm (peak

The degree of crystallinity of a specimen can be calculated from the melting heat of

 (14) Where wf is the weight fraction of nanofiller and ΔH0=207.1 Jg-1 is the melting heat of 100%

The DSC results indicated that the addition of both nanoparticles to the PP caused only a marginal effect on melting temperature (Tm) and no correlation of the results with the filler concentration could be established. The calculated degree of crystallinity of the PP phase increased with increasing content of both nanoparticles, indicating that the nanofillers nucleated the crystallization process. (Frormann et al., 2008) This implies that the existence of nanoparticles facilitates the crystallization of PP and this effect becomes more evident with higher nanoparticle content (Zhao & Li, 2006). Similar results for PP/CaCO3

temperature of melting) and ΔHm (enthalpy of melting), are listed in Table 3.

**6.1 Nanocomposites using inorganic fillers** 

linear increase with an increase in crystallinity.

**6.1.1 Differential Scanning Calorimetry (DSC)** 

crystallization according to the following equation:

crystalline PP (Bai et al., 1999).

Table 3. Crystallization parameters of neat PP and nanocomposites. a) PP/ZnO nanocomposite. b) PP/CaCO3 nanocomposite.

## **6.1.2 Thermal conductivity measurement**

Thermal conductivity was measured using a TCA Thermal Conductivity Analyser (TCA-200LT-A, Netzsch, Selb, Germany) with the guarded heat flow meter method. Each compression molded sample (30cm×30cm sheets with 10 mm thickness) was placed between two heated surface controlled at different temperatures with a flow of heat from the hot to the cold surface. When thermal equilibrium was attained thermal conductivity data were taken within an accuracy of 3%. Fig. 1 compares the effect of the nanoparticles' content on the thermal conductivity of the nanocomposites. As seen, the value of thermal conductivity increased with an increase in the nanoparticle concentration up to 64% and 82% for CaCO3 and ZnO respectively. The increase in TC for ZnO nanoparticles is more than CaCO3 due to the nature of nanofiller and also crystallinity degree regarding to DSC results (Table 3). These increases in TC for both nanoparticles are higher than that of reported values for CNF in a PP matrix (Frormann et al., 2008).

The values obtained from the experimental study of PP nanocomposites were compared with several TC models (Figs 2.a and 2.b). As seen the experimental results were found to fall in between the Series and Parallel models. However, the lower bound model (series) is usually closer to the experimental data.

Maxwell, Lewis & Nielson, Bruggeman, Bottcher and De Loor models predict fairly well thermal conductivity values up to 10 wt% for PP/ZnO nanocomposites (Fig. 2.a). In the concentration of 15 wt% no model could predict well the TC values and all of the mentioned models underestimated the TC values of nanocomposite whereas in the case 5 wt% all models overestimated the TC values.

Thermal Conductivity of Nanoparticles Filled Polymers 533

This fact can be attributed to the intrinsic thermal conductivity of both nanoparticles and their large surface area which even at lower loadings of nanofillers they are still effective to transfer heat through the samples (Frormann et al., 2008). At a higher volume fraction, this effect becomes stronger. Fig. 2.b the values obtained from the experimental study for PP/CaCO3 nanocomposites are compared with a number of TC models. As seen the Ce Wen Nan model predicts fairly well the thermal conductivity values up to 15 wt%. For the concentration of 10 wt% all the models predict the TC values well. In the case of 15 wt% other models underestimated the TC values of nanocomposites except for the Ce Wen Nan model, whereas for 5 wt% all models overestimated the TC value. The predicted TC values by the models depend on the nature of nanofiller and their relative concentrations

The TC improvement in PP/ZnO nanocomposite is greater than that of PP/calcium carbonate nanocomposites. This fact can be attributed to intrinsic thermal conductivity of the ZnO nanoparticles. Several models have been used for prediction of TC in the nanocomposites (see section 3.2). In the PP/ZnO nanocomposites TC values correlated well with the values predicted by Series, Maxwell, Lewis & Nielson, Bruggeman and De Loor

As electronic devices tend to become slimmer and more integrated, heat management become a central task for device design and application. Similar issues are faced in several other applications, including electric motors and generators, heat exchangers in power generation, automotive, etc. Metallic materials are widely used as heat dissipation materials, but there have been many attempts to replace the metallic materials with highly thermally conductive polymer based composites due to their lightweight, corrosion resistance, easy

Thermally conductive polymer based composites are tentatively prepared by the incorporation of thermally conductive fillers. The outstanding thermal conductivity of mentioned fillers makes them a promising candidates to obtain highly thermally conductive

PP nanocomposites were prepared by melt extrusion in a twin screw extruder. The introduction of nanoparticles resulted in an increase in crystallinity. Scanning electron microscopy (SEM) indicated a good dispersion of the nanofillers within the PP matrix that might enhance the thermal conductivity of the nanocomposites even at lower nanofiller loadings owing to enhanced filler-matrix interaction. The thermal conductivity of PP/ZnO nanocomposites had an increase of 82% at 15 wt% concentration comparing to that of pure PP, while for PP/CaCO3 nanocomposite with same level of nanoparticle content it was 64%, so it is concluded that ZnO nanoparticles had more intrinsic potential to improve thermal conductivity of PP comparing to CaCO3 nanoparticles regarding to its nature and

The thermal conductivity was increased from K=0.22 W/mK for pure PP by 64% for the sample with 15 wt% of CaCO3 nanoparticles. These results for both nanocomposites (PP/ZnO and PP/CaCO3) are higher than the values which reported for CNF in a PP matrix

(Weidenfeller et al., 2004; Frormann et al., 2008).

processing and lower manufacturing cost.

polymer based composites.

crystallinity.

models up to 10 wt%.

**7. Conclusions** 

Fig. 1. Comparing the effect of nanoparticles on the TC of PP.

Fig. 2. Comparing the experimental TC values vs nanoparticle content with theoretical models. a) PP/ZnO nanocomposite b) PP/CaCO3 nanocomposite.

This fact can be attributed to the intrinsic thermal conductivity of both nanoparticles and their large surface area which even at lower loadings of nanofillers they are still effective to transfer heat through the samples (Frormann et al., 2008). At a higher volume fraction, this effect becomes stronger. Fig. 2.b the values obtained from the experimental study for PP/CaCO3 nanocomposites are compared with a number of TC models. As seen the Ce Wen Nan model predicts fairly well the thermal conductivity values up to 15 wt%. For the concentration of 10 wt% all the models predict the TC values well. In the case of 15 wt% other models underestimated the TC values of nanocomposites except for the Ce Wen Nan model, whereas for 5 wt% all models overestimated the TC value. The predicted TC values by the models depend on the nature of nanofiller and their relative concentrations (Weidenfeller et al., 2004; Frormann et al., 2008).

The TC improvement in PP/ZnO nanocomposite is greater than that of PP/calcium carbonate nanocomposites. This fact can be attributed to intrinsic thermal conductivity of the ZnO nanoparticles. Several models have been used for prediction of TC in the nanocomposites (see section 3.2). In the PP/ZnO nanocomposites TC values correlated well with the values predicted by Series, Maxwell, Lewis & Nielson, Bruggeman and De Loor models up to 10 wt%.

## **7. Conclusions**

532 Smart Nanoparticles Technology

Fig. 2. Comparing the experimental TC values vs nanoparticle content with theoretical

wt% of Nanofiller

b

Experimental Value

Pralell Series Model Bruggeman Model

Bottcher Deloor Model Nan Model

models. a) PP/ZnO nanocomposite b) PP/CaCO3 nanocomposite.

Fig. 1. Comparing the effect of nanoparticles on the TC of PP.

a

Thermal Conductivity (W/m.K)

As electronic devices tend to become slimmer and more integrated, heat management become a central task for device design and application. Similar issues are faced in several other applications, including electric motors and generators, heat exchangers in power generation, automotive, etc. Metallic materials are widely used as heat dissipation materials, but there have been many attempts to replace the metallic materials with highly thermally conductive polymer based composites due to their lightweight, corrosion resistance, easy processing and lower manufacturing cost.

Thermally conductive polymer based composites are tentatively prepared by the incorporation of thermally conductive fillers. The outstanding thermal conductivity of mentioned fillers makes them a promising candidates to obtain highly thermally conductive polymer based composites.

PP nanocomposites were prepared by melt extrusion in a twin screw extruder. The introduction of nanoparticles resulted in an increase in crystallinity. Scanning electron microscopy (SEM) indicated a good dispersion of the nanofillers within the PP matrix that might enhance the thermal conductivity of the nanocomposites even at lower nanofiller loadings owing to enhanced filler-matrix interaction. The thermal conductivity of PP/ZnO nanocomposites had an increase of 82% at 15 wt% concentration comparing to that of pure PP, while for PP/CaCO3 nanocomposite with same level of nanoparticle content it was 64%, so it is concluded that ZnO nanoparticles had more intrinsic potential to improve thermal conductivity of PP comparing to CaCO3 nanoparticles regarding to its nature and crystallinity.

The thermal conductivity was increased from K=0.22 W/mK for pure PP by 64% for the sample with 15 wt% of CaCO3 nanoparticles. These results for both nanocomposites (PP/ZnO and PP/CaCO3) are higher than the values which reported for CNF in a PP matrix

Thermal Conductivity of Nanoparticles Filled Polymers 535

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SWCNT single-walled carbon nanotube *Tg* glass transition temperature *v* average phonon velocity VGCF vapor grown carbon fiber *Α* thermal diffusivity *ρ* density of the material *Φm* volume fractions of matrix *Φp* volume fractions of particles wf weight fraction of particles

Frormann L, Iqbal A, Abdullah S.A. 2008. The measured values were also compared with various models in the investigated range of nanofiller concentration. The Series, Maxwell, Lewis & Nielson, Bruggeman, Bottcher, De Loor and Ce Wen Nan models predicted fairly well the thermal conductivity values for the samples containing more than 5 wt% of nanoparticles. The experimental TC values of PP nanocomposites showed a linear increase with an increase in concentration and crystallinity.

## **8. Abbreviations**



#### **9. References**

534 Smart Nanoparticles Technology

Frormann L, Iqbal A, Abdullah S.A. 2008. The measured values were also compared with various models in the investigated range of nanofiller concentration. The Series, Maxwell, Lewis & Nielson, Bruggeman, Bottcher, De Loor and Ce Wen Nan models predicted fairly well the thermal conductivity values for the samples containing more than 5 wt% of nanoparticles. The experimental TC values of PP nanocomposites showed a linear increase

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EG expanded graphite

BNNT boron nitride nanotubes CNT carbon nanotube *Cp* heat capacity

DSC differential scanning calorimetry DWCNT double-walled carbon nanotube

EPDM ethylene propylene diene rubber EVA poly(ethylene vinyl acetate) GNP graphite nanoplatelet HDPE high density polyethylene

 effective thermal conductivity) *kc* thermal conductivity of composite *km* thermal conductivity of matrix *kp* thermal conductivity of particle

*l* phonon mean free path *L* length parameter

LDPE low density polyethylene

PBT poly(butylene terephthalate)

PDMS poly(dimethylsiloxane)

PEEK polyetheretherketone PET poly(ethylene terephthalate) PEVA poly(ethylene vinyl alcohol)

PMDA pyromellitic dianhydride PMMA polymethylmethacrylate

PPS polyphenylene sulfide PPSU polyphenylsulfone

PA6 polyamide 6 PA66 polyamide 6-6

PC polycarbonate

PE polyethylene

PI polyimide

PP polypropylene

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**24** 

 *Turkey* 

**Magnetic Properties and Size Effects of** 

**Nanoparticles in Different Type Lattices** 

Orhan Yalçn1, Rza Erdem*2* and Zafer Demir3 *1Department of Physics, Niğde University, Niğde 2Department of Physics, Akdeniz University, Antalya* 

**Spin-1/2 and Spin-1 Models of Core-Surface** 

*3Institute of Graduate School of Natural and Applied Sciences, Niğde University, Niğde* 

Dimension in the range of 1 to 100 nm**,** is called the nano regime. In recent years, nanoparticles/quantum dots are in a class of magnetic nanostructures (Aktaş et al., 2003, 2006; Kartopu & Yalçn, 2010). Nanoparticles (NPs) have been steadily interesting in Physics, Chemistry, Biology, Biomedicine, Spintronics, etc. As the dimensions of magnetic NPs decrease down to the nanometer scale, these core-surface NPs start to exhibit new and interesting physical properties mainly due to quantum size effects. Even the intrinsic physical characteristics of NPs are observed to change drastically compared to their macroscopic counterparts. The potential applications of NPs are very attractive for magnetosensor, bio-sensor, magneto-electronics, data storage media, computer hard disks, microwave electronic devices, nano-transistors, etc. Especially, the studies of core-surface NPs are extremely important for technology because of transmission of data at high density to optical computer, nanorobot to assemble, compose rigid disk. The nanoparticles have relevance to thin film devices in the new breed of magnetoelectronics, spin-valve, spintransistors, spin-dependence tunneling devices and etc. (Babin, et al., 2003). The hysteresis in fine magnetic particles applied to new technologies such as Magnetic Random Access

In generally, a nanoparticle is divided into the inner, outer and intermediate regions. These zones are called core (C), surface (S) and core-surface (CS), respectively. The size effects of core-surface NPs are very important for technological and biomedicine applications (Fraerman et al., 2001; Pankhurst et al., 2003). Especially, superparamagnetic (singledomain) NPs are important for non surgecial interfere of human body. The ferromagnetic (FM) orders in magnetic systems were dominated as mono-domain (or single-domain) nanoparticles consisting of FM surface and antiferromagnetic (AFM) core regions which couple with each other (Rego & Figueiredo, 2001; Leite & Figueiredo, 2004). At the lower temperatures, the FM surface and AFM core are only ordered in the noninteracting (monodomain) NPs. Stoner-Wohlfarth (Stoner & Wohlfarth, 1948) and Heisenberg model (Heisenberg, 1928) to describe the fine structure were fistly used in detail. Magnetic

**1. Introduction** 

Memory (MRAM).


## **Magnetic Properties and Size Effects of Spin-1/2 and Spin-1 Models of Core-Surface Nanoparticles in Different Type Lattices**

Orhan Yalçn1, Rza Erdem*2* and Zafer Demir3 *1Department of Physics, Niğde University, Niğde 2Department of Physics, Akdeniz University, Antalya 3Institute of Graduate School of Natural and Applied Sciences, Niğde University, Niğde Turkey* 

## **1. Introduction**

540 Smart Nanoparticles Technology

Wolff S. & Wang M.J. (1993), Carbon black science & technology (2nd ed.), Marcel Dekker,

Wong Y.W.; Lo K.L. & Shin F.G. (2001), Electrical and thermal properties of composite of

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Zeng J.; Fu R.; Agathopoulos S.; Zhang S.; Song X. & He H. (2009), Numerical simulation of

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Zhou W.; Qi S.; An Q.; Zhao H. & Liu N. (2007), Thermal conductivity of boron nitride

nanotubes as fillers, *Advanced Functional Materials*, vol.19, pp. 1857–1862. Zhong C.; Yang Q. & Wang W. (2001), Correlation and prediction of the thermal conductivity of amorphous polymers, *Fluid Phase Equilibria,* vol.181, pp. 195–202. Zhou H.; Zhang S. & Yang M. (2007), The effect of heat-transfer passages on the effective

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ChemTec Publishing, Toronto.

vol.20, pp. 585–613.

Dimension in the range of 1 to 100 nm**,** is called the nano regime. In recent years, nanoparticles/quantum dots are in a class of magnetic nanostructures (Aktaş et al., 2003, 2006; Kartopu & Yalçn, 2010). Nanoparticles (NPs) have been steadily interesting in Physics, Chemistry, Biology, Biomedicine, Spintronics, etc. As the dimensions of magnetic NPs decrease down to the nanometer scale, these core-surface NPs start to exhibit new and interesting physical properties mainly due to quantum size effects. Even the intrinsic physical characteristics of NPs are observed to change drastically compared to their macroscopic counterparts. The potential applications of NPs are very attractive for magnetosensor, bio-sensor, magneto-electronics, data storage media, computer hard disks, microwave electronic devices, nano-transistors, etc. Especially, the studies of core-surface NPs are extremely important for technology because of transmission of data at high density to optical computer, nanorobot to assemble, compose rigid disk. The nanoparticles have relevance to thin film devices in the new breed of magnetoelectronics, spin-valve, spintransistors, spin-dependence tunneling devices and etc. (Babin, et al., 2003). The hysteresis in fine magnetic particles applied to new technologies such as Magnetic Random Access Memory (MRAM).

In generally, a nanoparticle is divided into the inner, outer and intermediate regions. These zones are called core (C), surface (S) and core-surface (CS), respectively. The size effects of core-surface NPs are very important for technological and biomedicine applications (Fraerman et al., 2001; Pankhurst et al., 2003). Especially, superparamagnetic (singledomain) NPs are important for non surgecial interfere of human body. The ferromagnetic (FM) orders in magnetic systems were dominated as mono-domain (or single-domain) nanoparticles consisting of FM surface and antiferromagnetic (AFM) core regions which couple with each other (Rego & Figueiredo, 2001; Leite & Figueiredo, 2004). At the lower temperatures, the FM surface and AFM core are only ordered in the noninteracting (monodomain) NPs. Stoner-Wohlfarth (Stoner & Wohlfarth, 1948) and Heisenberg model (Heisenberg, 1928) to describe the fine structure were fistly used in detail. Magnetic

Magnetic Properties and Size Effects of Spin-1/2 and Spin-1

normalization condition the point variables can be written as

1

normalized by <sup>2</sup>

chemical potential such as <sup>2</sup>

current interest (Kaneyoshi et al., 1998).

variables are normalized by , 1 <sup>1</sup> *<sup>n</sup>*

energy per site can be found from

**2.2 Pair approximation** 

1 *n*

where

Models of Core-Surface Nanoparticles in Different Type Lattices 543

where *h* is the external magnetic field at the site *i* and the summation is performed for nearest-neighbour sites. *J* is the exchange interaction between neighbouring sites *ij* . Two distinctive cases corresponding to different signs of intersite interaction is considered, i.e., *J* 0 (ferromagnetic (FM) coupling) and 0 *J* (antiferromagnetic (AFM) coupling). The fractions of 1 *Si* spins given by *Xi* are called the point (or state) variables. The *Xi* are

magnetization ( ) *M* and it is defined by *M X X* 1 2 . From this definition and the

On the other hand, Eq. (1) may be extended by allowing values *s S* 0, 1, 2,..., for the variables. It is then possible to consider higher order interactions such as 2 2

Blume-Emery-Griffiths (BEG) model (Blume et al., 1971). Recently, there have been many theoretical studies of mixed spin Ising systems. These are of interest because they have less translational symmetry than their single-spin counterparts since they consist of two interpenetrating inequivalent sublattices. The latter property is very important to study a certain type of ferrimagnetism, namely molecular-based magnetic materials which are of

In the pair approximation, we consider the pair correlations between the spins. Besides the point variables ( ) *Xi* , we introduce new variables ( ) *Yij* , indicating the average number of the states in which the first member of the nearest-neighbour pair is in state *i* and the second member in state *j* . These will be called the pair or bond variables. The bond

*i ij <sup>j</sup> X Y* . Here *n* is the number of spin states in the given spin *S* model. The

, 2 *n*

*ij ij i j EN Y* 

 

, 1 , 1 ( 1) ln( ) ln( ) <sup>2</sup> *n n E ii ij ji i j i j S Nk XX YY*

*ij* are called the bond energies for the spin pairs (, ) *i j* and determined from Eq. (1). The free

1 /*kT* ( *k* Boltzmann's constant and *T* temperature). In Eq. (3), the parameters

 

interaction energy *E* and entropy *SE* can be written in terms of *Yij* as

<sup>1</sup> (1 ) 2 *X M* , 2

*S J SS h S S* , with 1 *Si* , (1)

<sup>1</sup> <sup>1</sup> *<sup>i</sup> <sup>i</sup> <sup>X</sup>* . The long-range order parameter in the model is called the

<sup>1</sup> (1 ) 2

*<sup>i</sup> <sup>i</sup> <sup>S</sup>* . These generalizations are regarded as extensions of the

*ij i j <sup>Y</sup>* and related to the state varibales by the relations

, (3)

, (4)

*X M* . (2)

*<sup>i</sup> <sup>j</sup> ij K SS* or a

 ( ) *i i <sup>j</sup> <sup>i</sup> <sup>j</sup> ij ij*

evolutions with temperatures (Babin, et al., 2003; Szlaferek, 2004; Usov & Gudoshnikov, 2005), thermodynamic properties (Vargas et al., 2002) and experimental techniques (Wernsdorfer et al., 1995; Wernsdorfer et al., 2000) were performed by different type works for the core-surface NPs. A simple (Bakuzis & Morais, 2004) and the first atomic-scale models of the ferrimagnetic and heterogeneous systems in which the exchange energy plays a central role in determining the magnetization of the NPs, were studied (Kodama et al., 1996, 1999; Kodama & Berkowitz, 1999).

Ising models and real magnets have provided a rich and productive field for the interaction between theory and experiment over the past 86 years (Ising, 1925; Peierls, 1936). Ising models (Erdem, 1995; Keskin, & Erdem 1997; Erdem & Keskin, 2001; Erdem, 2009; Erdem, 2008; Chen & Levy, 1973) and thier variants such as Blume-Capel (Blume, 1966; Capel, 1966; Bakchich, et al., 1994), Blume-Emery-Griffiths (Blume, et al., 1971; Achiam, 1985; Hoston, & Berker, 1991; Bakkali, 1996; Goveas & Mukhopadhyay, 1997; Keskin, et al., 1999; Temizer, 2008) and mixed spin (Benayad & Dakhama 1997; Kaneyoshi, 1998; Albayrak, & Yigit, 2005; Albayrak, & Yigit, 2006; Albayrak, 2007; Albayrak, 2007; Deviren, et al., 2009) models were regarded as theoretical simplifications, designed to model the essential aspects of cooperative system (Kikuchi,1951) without detailed correspondence to specific materials.

In the scope of this chapter, we give a detailed analysis for both spin *S* 1/2 and 1 *S* Ising models of homegeneous and core-surface composite NPs to describe the magnetic properties of these particles. These models are based on the pair approximation in the Kikuchi version (Kikuchi, 1974; Keskin, 1986; Erdinç & Keskin, 2002; Yalçn, et al. 2008, Özüm, 2010; Çiftçi, 2011). Incorporating the pair correlations between the spins inside the NPs, we calculated the free energy and minimized with respect to pair variables to obtain the field-cooled magnetization. The field cooling magnetization (*M*) curves of homogeneous and composite NPs are given as a function of the reduced temperature with different radius and different type lattices. Hysteresis loops and coercive fields with their linear fit to the data were plotted as a function of radius and temperature of different NPs. We compared our result with other works (Kaneyoshi, 2005; Kodama, 1999; Usov & Gudoshnikov, 2005).

## **2. Theoretical model**

## **2.1 Ising model**

Ising model, which was introduced in the field of magnetism, is one of the most studied models in modern statistical physics. Although its greatest success during the last century has been in the theory of phase transitions, the model today is viewed as a mathematical structure which can represent a variaty of different physical phenomena. In this section, we give a brief summary for the basics of the model before its application to the nanoparticle (NP) magnetism.

Ising model is considered on a regular lattice where each interior site has the same number of nearest-neighbour sites. This is called the coordination number of the lattice and will be denoted by . The system under consideration is composed of the magnetic atoms (also called the spins) located at the lattice sites. It is assumed that, in the thermodynamic limit, boundary sites can be disregarded and that, with *N* sites, the number of nearest-neighbour site pairs is *N*2 . The standard Hamiltonian for the the simplest Ising model is given by

$$\text{H}\begin{Bmatrix} S\_i \end{Bmatrix} = -\varprojlim\_{\{\bar{v}\}} S\_i S\_j - h \sum\_{\{\bar{v}\}} (S\_i + S\_j) \text{, with } S\_i = \pm 1 \text{, }\tag{1}$$

where *h* is the external magnetic field at the site *i* and the summation is performed for nearest-neighbour sites. *J* is the exchange interaction between neighbouring sites *ij* . Two distinctive cases corresponding to different signs of intersite interaction is considered, i.e., *J* 0 (ferromagnetic (FM) coupling) and 0 *J* (antiferromagnetic (AFM) coupling). The fractions of 1 *Si* spins given by *Xi* are called the point (or state) variables. The *Xi* are normalized by <sup>2</sup> <sup>1</sup> <sup>1</sup> *<sup>i</sup> <sup>i</sup> <sup>X</sup>* . The long-range order parameter in the model is called the magnetization ( ) *M* and it is defined by *M X X* 1 2 . From this definition and the normalization condition the point variables can be written as

$$X\_1 = \frac{1}{2}(1+M) \, \, \, X\_2 = \frac{1}{2}(1-M) \, \,. \tag{2}$$

On the other hand, Eq. (1) may be extended by allowing values *s S* 0, 1, 2,..., for the variables. It is then possible to consider higher order interactions such as 2 2 *<sup>i</sup> <sup>j</sup> ij K SS* or a chemical potential such as <sup>2</sup> *<sup>i</sup> <sup>i</sup> <sup>S</sup>* . These generalizations are regarded as extensions of the Blume-Emery-Griffiths (BEG) model (Blume et al., 1971). Recently, there have been many theoretical studies of mixed spin Ising systems. These are of interest because they have less translational symmetry than their single-spin counterparts since they consist of two interpenetrating inequivalent sublattices. The latter property is very important to study a certain type of ferrimagnetism, namely molecular-based magnetic materials which are of current interest (Kaneyoshi et al., 1998).

#### **2.2 Pair approximation**

542 Smart Nanoparticles Technology

evolutions with temperatures (Babin, et al., 2003; Szlaferek, 2004; Usov & Gudoshnikov, 2005), thermodynamic properties (Vargas et al., 2002) and experimental techniques (Wernsdorfer et al., 1995; Wernsdorfer et al., 2000) were performed by different type works for the core-surface NPs. A simple (Bakuzis & Morais, 2004) and the first atomic-scale models of the ferrimagnetic and heterogeneous systems in which the exchange energy plays a central role in determining the magnetization of the NPs, were studied (Kodama et al.,

Ising models and real magnets have provided a rich and productive field for the interaction between theory and experiment over the past 86 years (Ising, 1925; Peierls, 1936). Ising models (Erdem, 1995; Keskin, & Erdem 1997; Erdem & Keskin, 2001; Erdem, 2009; Erdem, 2008; Chen & Levy, 1973) and thier variants such as Blume-Capel (Blume, 1966; Capel, 1966; Bakchich, et al., 1994), Blume-Emery-Griffiths (Blume, et al., 1971; Achiam, 1985; Hoston, & Berker, 1991; Bakkali, 1996; Goveas & Mukhopadhyay, 1997; Keskin, et al., 1999; Temizer, 2008) and mixed spin (Benayad & Dakhama 1997; Kaneyoshi, 1998; Albayrak, & Yigit, 2005; Albayrak, & Yigit, 2006; Albayrak, 2007; Albayrak, 2007; Deviren, et al., 2009) models were regarded as theoretical simplifications, designed to model the essential aspects of cooperative system (Kikuchi,1951) without detailed correspondence to specific materials.

In the scope of this chapter, we give a detailed analysis for both spin *S* 1/2 and 1 *S* Ising models of homegeneous and core-surface composite NPs to describe the magnetic properties of these particles. These models are based on the pair approximation in the Kikuchi version (Kikuchi, 1974; Keskin, 1986; Erdinç & Keskin, 2002; Yalçn, et al. 2008, Özüm, 2010; Çiftçi, 2011). Incorporating the pair correlations between the spins inside the NPs, we calculated the free energy and minimized with respect to pair variables to obtain the field-cooled magnetization. The field cooling magnetization (*M*) curves of homogeneous and composite NPs are given as a function of the reduced temperature with different radius and different type lattices. Hysteresis loops and coercive fields with their linear fit to the data were plotted as a function of radius and temperature of different NPs. We compared our result with other works (Kaneyoshi, 2005; Kodama, 1999; Usov & Gudoshnikov, 2005).

Ising model, which was introduced in the field of magnetism, is one of the most studied models in modern statistical physics. Although its greatest success during the last century has been in the theory of phase transitions, the model today is viewed as a mathematical structure which can represent a variaty of different physical phenomena. In this section, we give a brief summary for the basics of the model before its application to the nanoparticle

Ising model is considered on a regular lattice where each interior site has the same number of nearest-neighbour sites. This is called the coordination number of the lattice and will be

called the spins) located at the lattice sites. It is assumed that, in the thermodynamic limit, boundary sites can be disregarded and that, with *N* sites, the number of nearest-neighbour

. The system under consideration is composed of the magnetic atoms (also

2 . The standard Hamiltonian for the the simplest Ising model is given by

1996, 1999; Kodama & Berkowitz, 1999).

**2. Theoretical model** 

**2.1 Ising model** 

(NP) magnetism.

denoted by

site pairs is *N*

In the pair approximation, we consider the pair correlations between the spins. Besides the point variables ( ) *Xi* , we introduce new variables ( ) *Yij* , indicating the average number of the states in which the first member of the nearest-neighbour pair is in state *i* and the second member in state *j* . These will be called the pair or bond variables. The bond variables are normalized by , 1 <sup>1</sup> *<sup>n</sup> ij i j <sup>Y</sup>* and related to the state varibales by the relations 1 *n i ij <sup>j</sup> X Y* . Here *n* is the number of spin states in the given spin *S* model. The interaction energy *E* and entropy *SE* can be written in terms of *Yij* as

$$\mathcal{B} \to \mathcal{N} \frac{\mathcal{Y}}{2} \sum\_{i,j}^{n} \eta\_{ij} \mathcal{Y}\_{ij} \tag{3}$$

$$S\_E = \text{Nk}\left(\left\{\mathcal{Y} - \mathbf{1}\right\} \sum\_{i,j=1}^n X\_i \ln(X\_i) - \frac{\mathcal{Y}}{2} \sum\_{i,j=1}^n Y\_{ij} \ln(Y\_{ji})\right) \tag{4}$$

where 1 /*kT* ( *k* Boltzmann's constant and *T* temperature). In Eq. (3), the parameters *ij* are called the bond energies for the spin pairs (, ) *i j* and determined from Eq. (1). The free energy per site can be found from

Magnetic Properties and Size Effects of Spin-1/2 and Spin-1

,

,

*i j*

1 for *S* 1/2 and 0, 1 for 1 *S* Ising systems.

the core spin values and

shortly in term of *Yij* as

given by

with

Models of Core-Surface Nanoparticles in Different Type Lattices 545

The magnetic particles become single domain below a critical size in contrast with the usual multidomain structure of the bulk materials. Therefore, in the scope of this section, we study size effects and magnetic properties of monodomain NPs manifestations. We consider a noninteracting monodomain NP with Ising spins on both hexagonal and square lattices for any two-dimensional (2D) regular arrays which can also be extended to hexagonal closed packed (hcp) and simple cubic (sc) lattices for the three-dimensional (3D) case as in Fig.1. The shells and their numbers originate from the nearest-neighbor pair interactions for the hexagonal and square lattices in 2D. In this structure, number of shells for hexagonal and square lattices can be associated with radius ( *R* ) of the NPs. This behaviour can be seen explicitly in Fig. 2 for hexagonal lattice and in Fig. 3 for square lattice. The value of *R* includes number of shells and the size of a NP increases as the number of shells increses. Therefore, we have considered Ising spins in three parts that are core (*C* ), core-surface (*CS* ) and surface ( *S* ) within the NP. Each of these parts contain core spin number ( *NC* ), coresurface spin number ( *NCS* ) and surface spin number ( *NS* ), respectively. The total number of spins ( *N* ) in a single NP involves core and surface spin numbers, i.e. *NN N C S* . The *C* and *S* spins interact ferromagnetically ( 0) *J* or antiferromagnetically ( 0) *J* . The *S* 1/2 and 1 *S* Ising model Hamiltonians with dipol-dipol interaction ( )*J* for a NP is

> , , ( ) *CCi <sup>j</sup> <sup>i</sup> <sup>j</sup> ij ij J SS h S S* ,

> > *CS CS i j i j*

, , ( ) *SS i <sup>j</sup> <sup>i</sup> <sup>j</sup> ij ij J h* 

where *CJ* , *CS J* and *SJ* represent exchange interactions for *C* , *CS* and *S* atoms, respectively. If *C CS S JJ J* , the NP is known as a homegeneous NP. It is called a composite NP when *C CS S JJ J* , *C CS S JJ J* , *C CS S JJ J* or *CS C S J JJ* . In Eqs. (9), *Si* is called

The interaction energies for *S* 1/2 and 1 *S* models of an Ising NP in 2D can be written

( ) *C C CS CS S S P ij P ij P ij ij*

 ,

*<sup>i</sup>* is the surface spin values. These variables take on the values

*E N N NY* , (10)

*J S*

C CS S , (8)

, (9)

**3. Magnetic properties of** *S* 1/2 **and** *S* 1 **Ising nanoparticles** 

$$
\Phi = \frac{\mathcal{J} \cdot \mathcal{F}}{N} = \frac{\mathcal{J}}{N} (E - TS\_E) \,. \tag{5}
$$

For the system at equilibrium, the minimization of Eq. (5) with respect to *Yij* (/ 0 *Yij* ) leads to the following set of self-consistent equations:

$$Y\_{ij} = \frac{1}{Z} (X\_i X\_j)^{\overline{\mathcal{T}}} e^{-\beta \eta\_{\overline{\eta}}} \equiv \frac{\mathcal{e}\_{\overline{\mathcal{U}}}}{Z} \, \, \, \tag{6}$$

where ( 1) / and *Z* is the partition function:

$$Z = \exp(2\beta\lambda \; / \; \gamma) = \sum\_{i,j=1}^{n} e\_{ij} \; . \tag{7}$$

In Eq. (7), is introduced to maintain the normalization condition. Applications of the above formulation to 1 / 2 *S* and 1 *S* Ising systems can be found in many works in the literature (Meijer et al., 1986; Keskin & Meijer, 1986; Keskin & Erdinç, 1995; Erdinç & Keskin, 2002). These applications are summerized for comparison in Table 1.


Table 1. Comparison of the *S* 1 2 and 1 *S* Ising models under the pair approximation.

#### **3. Magnetic properties of** *S* 1/2 **and** *S* 1 **Ising nanoparticles**

The magnetic particles become single domain below a critical size in contrast with the usual multidomain structure of the bulk materials. Therefore, in the scope of this section, we study size effects and magnetic properties of monodomain NPs manifestations. We consider a noninteracting monodomain NP with Ising spins on both hexagonal and square lattices for any two-dimensional (2D) regular arrays which can also be extended to hexagonal closed packed (hcp) and simple cubic (sc) lattices for the three-dimensional (3D) case as in Fig.1. The shells and their numbers originate from the nearest-neighbor pair interactions for the hexagonal and square lattices in 2D. In this structure, number of shells for hexagonal and square lattices can be associated with radius ( *R* ) of the NPs. This behaviour can be seen explicitly in Fig. 2 for hexagonal lattice and in Fig. 3 for square lattice. The value of *R* includes number of shells and the size of a NP increases as the number of shells increses. Therefore, we have considered Ising spins in three parts that are core (*C* ), core-surface (*CS* ) and surface ( *S* ) within the NP. Each of these parts contain core spin number ( *NC* ), coresurface spin number ( *NCS* ) and surface spin number ( *NS* ), respectively. The total number of spins ( *N* ) in a single NP involves core and surface spin numbers, i.e. *NN N C S* . The *C* and *S* spins interact ferromagnetically ( 0) *J* or antiferromagnetically ( 0) *J* . The *S* 1/2 and 1 *S* Ising model Hamiltonians with dipol-dipol interaction ( )*J* for a NP is given by

with

544 Smart Nanoparticles Technology

For the system at equilibrium, the minimization of Eq. (5) with respect to *Yij* (/ 0 *Yij* )

<sup>1</sup> ( ) *ij ij*

*Z Z* 

*N N* 

*ij i j*

and *Z* is the partition function:

2002). These applications are summerized for comparison in Table 1.

Spin state variables *Xi* 1 2 *X X*, <sup>123</sup> *XXX* , ,

Spin values *Si* 1, 1 1, 0, 1

11 12 21 22

*Y Y Y Y*

2 2

*i i j X Y* 

2

1 *i ij j X Y* 

1 11 12 2 21 22 *XY Y XY Y* 

–––––

1 ,1

( 1, 1), ( 1, 1) ( 1, 1), ( 1, 1)

 

1, 1 *<sup>i</sup> ij*

*M X X* 1 2 *M X X* 1 3

Table 1. Comparison of the *S* 1 2 and 1 *S* Ising models under the pair approximation.

*MY Y Y Y* 11 12 21 22

*Y XX e*

exp(2 / )

*Z e* 

above formulation to 1 / 2 *S* and 1 *S* Ising systems can be found in many works in the literature (Meijer et al., 1986; Keskin & Meijer, 1986; Keskin & Erdinç, 1995; Erdinç & Keskin,

*S* 1 2 *S* 1

leads to the following set of self-consistent equations:

where 

In Eq. (7),

Bond variables (, ) *YSS ij i j*

Normalization

variables and pair variables

Avarage

Relations between point

magnetization ( *M Si* )

Quadrupole moment

<sup>2</sup> *QQ S <sup>i</sup>*

 ( 1) / 

 

( ) *<sup>E</sup> <sup>F</sup> E TS*

*e*

, 1

*i j*

is introduced to maintain the normalization condition. Applications of the

*n ij*

. (5)

, (6)

. (7)

11 12 13 21 22 23 31 32 33

1, 1 *<sup>i</sup> ij*

*Y YY Y YY Y YY*

3 3

*i i j X Y* 

3

1 *i ij j X Y* 

*QX X* 1 3

1 11 12 13 2 21 22 23 3 31 32 33

11 12 13 31 32 33 *M YYY YYY* 

*QY Y Y Y Y Y* 11 12 13 31 32 33

*XY Y Y XY Y Y XY Y Y*

 

1 ,1

( 1, 1), ( 1,0), ( 1, 1) (0, 1), (0,0), (0, 1) ( 1, 1), ( 1,0), ( 1, 1)

 

$$\begin{aligned} \mathbf{H}\_{C} &= -f\_{C} \sum\_{\{i,j\}} S\_{i} S\_{j} - h \sum\_{\{i,j\}} (S\_{i} + S\_{j}) \; , \\\\ \mathbf{H}\_{CS} &= -f\_{CS} \sum\_{\{i,j\}} S\_{i} \sigma\_{j} \; , \\\\ \mathbf{H}\_{S} &= -f\_{S} \sum\_{\{i,j\}} \sigma\_{i} \sigma\_{j} - h \sum\_{\{i,j\}} (\sigma\_{i} + \sigma\_{j}) \; , \end{aligned} \tag{9}$$

C CS S , (8)

where *CJ* , *CS J* and *SJ* represent exchange interactions for *C* , *CS* and *S* atoms, respectively. If *C CS S JJ J* , the NP is known as a homegeneous NP. It is called a composite NP when *C CS S JJ J* , *C CS S JJ J* , *C CS S JJ J* or *CS C S J JJ* . In Eqs. (9), *Si* is called the core spin values and *<sup>i</sup>* is the surface spin values. These variables take on the values 1 for *S* 1/2 and 0, 1 for 1 *S* Ising systems.

The interaction energies for *S* 1/2 and 1 *S* models of an Ising NP in 2D can be written shortly in term of *Yij* as

$$\mathcal{J}\,E = \sum\_{\{i,j\}} \left( \mathbf{N}\_P^{\complement} \boldsymbol{\eta}\_{\overleftarrow{\boldsymbol{\eta}}}^{\complement} + \mathbf{N}\_P^{\complement} \boldsymbol{\eta}\_{\overleftarrow{\boldsymbol{\eta}}\overleftarrow{\boldsymbol{\eta}}}^{\complement} + \mathbf{N}\_P^{\complement} \boldsymbol{\eta}\_{\overleftarrow{\boldsymbol{\eta}}\overleftarrow{\boldsymbol{\eta}}}^{S} \right) Y\_{\overleftarrow{\boldsymbol{\eta}}} \,\tag{10}$$

Magnetic Properties and Size Effects of Spin-1/2 and Spin-1

Models of Core-Surface Nanoparticles in Different Type Lattices 547

Fig. 2. Schematic representation of a NP on a hexagonal lattice in 2D exhibiting nine shells of spins. Small full coloured circles correspond to ten radius of the NP. Solid grey lines are number of the core-shell pairs. Solid coloured lines are number of shell pair (this line

corresponds to core and shell number for *R* 2 ).

where the numbers of spin pairs for *C* , *CS* and *S* regions are defined by ( 2) *<sup>C</sup> NN N P C C CS* , 2 2 *CS N N P CS CS* and 2 *<sup>S</sup> N N P SS* , respectively. Similarly *<sup>C</sup>* , *CS* , *<sup>S</sup>* denote the coordination numbers for these regions. Since we consider the arrays of Ising spins for a structure made up of bigger particles in 2D, we choose 6 *<sup>C</sup>* , 2 *CS S* for hexagonal lattice and 4 *<sup>C</sup>* , 0 *<sup>S</sup>* , 2 *CS* for square lattice, as depicted in Figs. 2 and 3, respectively. The values of these numbers for both suructures in 2D are given in Table 2. The expressions for the bond energies *<sup>C</sup> ij* , *CS ij* and *<sup>S</sup> ij* of three regions are found using Eq. (9) for both models, as listed in Table 3.

Fig. 1. A spherical monodomain magnetic NP spaced coherently in a form of 3D arrays. The shape of a single NP consists of the hexagonal lattice. The dashed lines displayed shells of spins in a 2D finite arrays. The radius of NP ( *R* ) includes shell numbers. The insets exhibit coordination numbers ( ) of hexagonal closed packed (hcp) and simple cubic (sc) lattices in 3D as well as hexagonal and square lattices in 2D structure.

where the numbers of spin pairs for *C* , *CS* and *S* regions are defined by

and 3, respectively. The values of these numbers for both suructures in 2D are given in Table

Fig. 1. A spherical monodomain magnetic NP spaced coherently in a form of 3D arrays. The shape of a single NP consists of the hexagonal lattice. The dashed lines displayed shells of spins in a 2D finite arrays. The radius of NP ( *R* ) includes shell numbers. The insets exhibit

) of hexagonal closed packed (hcp) and simple cubic (sc) lattices in

and 2 *<sup>S</sup> N N P SS*

*ij* and *<sup>S</sup>* 

denote the coordination numbers for these regions. Since we consider the arrays of

, respectively. Similarly *<sup>C</sup>*

*ij* of three regions are found using

for square lattice, as depicted in Figs. 2

,

 , 2 *CS S* 

 , 0 *<sup>S</sup>*

Ising spins for a structure made up of bigger particles in 2D, we choose 6 *<sup>C</sup>*

 , 2 *CS* 

> *ij* , *CS*

( 2) *<sup>C</sup> NN N P C C CS* 

coordination numbers (

3D as well as hexagonal and square lattices in 2D structure.

for hexagonal lattice and 4 *<sup>C</sup>*

*CS* , *<sup>S</sup>*

, 2 2 *CS N N P CS CS*

2. The expressions for the bond energies *<sup>C</sup>*

Eq. (9) for both models, as listed in Table 3.

Fig. 2. Schematic representation of a NP on a hexagonal lattice in 2D exhibiting nine shells of spins. Small full coloured circles correspond to ten radius of the NP. Solid grey lines are number of the core-shell pairs. Solid coloured lines are number of shell pair (this line corresponds to core and shell number for *R* 2 ).

Magnetic Properties and Size Effects of Spin-1/2 and Spin-1

Pair

Table 3. Bond energies for *S* 1 2 and 1 *S* models.

1

1

1

1

*Z*

Spin Model

*S* 1 2 ( 2 *n* )

*S* 1 ( 3 *n* )

surface NPs:

Models of Core-Surface Nanoparticles in Different Type Lattices 549

Bond energy for Core –Surface ( *CS ij* )

<sup>11</sup> 2 *<sup>C</sup> J h CS J* 2 *<sup>S</sup> J h*

<sup>12</sup> *<sup>C</sup> J CS J <sup>S</sup> J*

<sup>21</sup> *<sup>C</sup> J CS J <sup>S</sup> J*

<sup>22</sup> 2 *<sup>C</sup> J h CS J* 2 *<sup>S</sup> J h*

<sup>11</sup> 2 *<sup>C</sup> J h CS J* 2 *<sup>S</sup> J h*

<sup>12</sup> *h* 0 *h*

<sup>13</sup> *<sup>C</sup> J CS J <sup>S</sup> J*

<sup>21</sup> *h* 0 *h*

<sup>22</sup> 0 0 0

<sup>23</sup> *h* 0 *h*

<sup>31</sup> *<sup>C</sup> J CS J <sup>S</sup> J*

<sup>32</sup> *h* 0 *h*

Using Eq. (6) we obtain four self-consistent equations of *Yij* for *S* 1/2 model of core-

*<sup>e</sup> Y XX N N N Z Z*

*<sup>e</sup> Y XX NN N Z Z*

*<sup>e</sup> Y XX N N N Z Z*

*<sup>e</sup> Y XX N N N*

11 1 1 11 11 11

12 1 2 12 12 12

21 2 1 21 21 21

22 2 2 22 22 22

Similarly, nine self-consistent equations of *Yij* for 1 *S* model of these particles are

exp

<sup>33</sup> 2 *<sup>C</sup> J h CS J* 2 *<sup>S</sup> J h*

exp ,

 

*C C CS CS S S PP P C C CS CS S S PP P C C CS CS S S PP P C C CS CS S S PP P*

 

> 

 

> 

exp ,

 

exp ,

 

> 

11

12

21

(11)

22 . *Z*

Bond energy for Surface ( *<sup>S</sup> ij* )

Bond energy for Core ( *<sup>C</sup> ij* )

Fig. 3. Same as Fig. 2 but for the NP on square lattice in 2D.


Table 2. Numbers of the spins and spin pairs within the *C* , *CS* and *S* regions (Yalçn, et al., 2008).

Fig. 3. Same as Fig. 2 but for the NP on square lattice in 2D.

**Hexagonal Lattice in 2D** 

**Square Lattice in** 

**2D** 

2008).

**Lattice Type** R **2 3 4 5 6 7 8 9 10** 

Table 2. Numbers of the spins and spin pairs within the *C* , *CS* and *S* regions (Yalçn, et al.,

*NC* 7 19 37 61 91 127 169 217 271 *NS* 12 18 24 30 36 42 48 54 60 *NCS* 9 15 21 27 33 39 45 51 57 *<sup>C</sup> NP* 12 42 90 156 240 342 462 600 756 *<sup>S</sup> NP* 12 18 24 30 36 42 48 54 60 *CS NP* 18 30 42 54 66 78 90 102 114

*NC* 5 13 25 41 61 85 113 145 181 *NS* 8 12 16 20 24 28 32 36 40 *NCS* 6 10 14 18 22 26 30 34 38 *<sup>C</sup> NP* 4 16 36 64 100 144 196 256 324 *CS NP* 12 20 28 36 44 52 60 68 76


Table 3. Bond energies for *S* 1 2 and 1 *S* models.

Using Eq. (6) we obtain four self-consistent equations of *Yij* for *S* 1/2 model of coresurface NPs:

$$\begin{split} Y\_{11} &= \frac{1}{Z} (X\_1 X\_1)^{\tilde{V}} \exp\left[ -\beta \left( N\_P^{\mathbb{C}} \eta\_{11}^{\mathbb{C}} + N\_P^{\mathbb{C}S} \eta\_{11}^{\mathbb{C}S} + N\_P^{\mathbb{S}} \eta\_{11}^{\mathbb{S}} \right) \right] \equiv \frac{e\_{11}}{Z}, \\ Y\_{12} &= \frac{1}{Z} (X\_1 X\_2)^{\tilde{V}} \exp\left[ -\beta \left( N\_P^{\mathbb{C}} \eta\_{12}^{\mathbb{C}} + N\_P^{\mathbb{C}S} \eta\_{12}^{\mathbb{C}S} + N\_P^{\mathbb{S}} \eta\_{12}^{\mathbb{S}} \right) \right] \equiv \frac{e\_{12}}{Z}, \\ Y\_{21} &= \frac{1}{Z} (X\_2 X\_1)^{\tilde{V}} \exp\left[ -\beta \left( N\_P^{\mathbb{C}} \eta\_{21}^{\mathbb{C}} + N\_P^{\mathbb{C}S} \eta\_{21}^{\mathbb{C}S} + N\_P^{\mathbb{S}} \eta\_{22}^{\mathbb{S}} \right) \right] \equiv \frac{e\_{21}}{Z}, \\ Y\_{22} &= \frac{1}{Z} (X\_2 X\_2)^{\tilde{V}} \exp\left[ -\beta \left( N\_P^{\mathbb{C}} \eta\_{22}^{\mathbb{C}S} + N\_P^{\mathbb{C}S} \eta\_{22}^{\mathbb{C}S} + N\_P^{\mathbb{S}} \eta\_{22}^{\mathbb{S}} \right) \right] \equiv \frac{e\_{22}}{Z}. \end{split} \tag{11}$$

Similarly, nine self-consistent equations of *Yij* for 1 *S* model of these particles are

Magnetic Properties and Size Effects of Spin-1/2 and Spin-1

and 5(d).

*h* 0.0-0.1.

Models of Core-Surface Nanoparticles in Different Type Lattices 551

particle radius it approaches to the Crue temperatures of the bulk materials. This is consistent with the mean-field approximation for the magnetic structure of Heisenberg NP (Usov & Gudoshnikov, 2005). On the other hand, it is interesting that composite *S* 1 2 and *S* 1 Ising NPs show smaller transition temperatures than their corresponding homegeneous NPs. This can easily be seen by comparing the same coloured fits in Figs. 4(d)

Fig. 4. Normalized magnetization ( *M* ) vs. reduced temperature ( *<sup>B</sup>* / <sup>0</sup> *kT J* ) and particle size dependence of the transition temperature *TC* from FM to PM phases for homogeneous *S* 1 2 and 1 *S* Ising NPs on the hexagonal and square lattices. 0 1 *C CS S JJ J J* and

 11 11 1 1 11 11 11 12 12 1 2 12 12 12 13 13 1 3 13 13 13 21 2 1 21 21 21 1 exp , 1 exp , 1 exp , 1 exp *C C CS CS S S PP P C C CS CS S S PP P C C CS CS S S PP P C C CS CS S S PP P <sup>e</sup> Y XX N N N Z Z <sup>e</sup> Y XX NN N Z Z <sup>e</sup> Y XX N N N Z Z <sup>e</sup> Y XX N N N Z* 21 22 22 2 2 22 22 22 23 23 2 3 23 23 23 31 31 3 1 31 31 31 32 3 2 32 32 32 , 1 exp , 1 exp , 1 exp , 1 exp *C C CS CS S S PP P C C CS CS S S PP P C C CS CS S S PP P C C CS CS S S PP P Z <sup>e</sup> Y XX N N N Z Z <sup>e</sup> Y XX N N N Z Z <sup>e</sup> Y XX N N N Z Z Y XX N N N Z* 32 33 33 3 3 33 33 33 , 1 . exp . *C C CS CS S S PP P e Z <sup>e</sup> Y XX NN N Z Z* (12)

Eqs. (11) and (12) are solved numerically using Newton-Raphson method and normalized magnetization ( *M* ) is easily calculated for both *S* 1 2 and 1 *S* models of homegeneous and core-surface composite NPs. Results are shown as the magnetization curves and hysteresis loops in Figs. 4–9.

#### **4. Result and discussions**

#### **4.1 Magnetization**

The evolution of normalized magnetization ( ) *M* as a function of the reduced temperature ( *<sup>B</sup>* / <sup>0</sup> *kT J* ) and particle size dependence of the transition temperature *TC* from FM to paramagnetic (PM) phases for homogeneous and composite Ising NPs are shown in Figs. 4 and 5, respectively. The magnetization curves in Fig. 4 are plotted for *S* 1 2 and 1 *S* models of homogeneous NPs using the FM core ( <sup>0</sup>*J* 1 , 1 *CJ* ), FM surface ( *<sup>S</sup>* <sup>0</sup> *J J* ) and FM core-surface ( *CS* <sup>0</sup> *J J* ) interactions and the curves in Fig. 5 are obtained for both models of the composite NPs based on FM core ( *<sup>C</sup>* <sup>0</sup> *J J* ), FM surface ( *<sup>S</sup>* <sup>0</sup> *J J* ) and AFM coresurface ( *CS* <sup>0</sup> *J J* ) interactions. In the plots, different values for the applied magnetic field are considered ( 0.0-0.1 *h* ). The solid curves in the figures correspond to hexagonal lattice while dotted ones denote the square lattice. As seen from the figures, the changes in the magnetization with the reduced temperature point out an interesting aspect for NPs on the hexagonal and square lattices in 2D. The magnetization curves are decreasing from one (1) to zero (0) value while the reduced temperature is increasing (Figs. 4(a), 4(b), 5(a), 5(b)). These decreases terminate at the phase transition temperature (or Curie temperature, *TC* ) from FM phase to PM phase for 0.0 *h* , seen in Figs. 4(c) and 5(c). To show the size dependence of the critical temperature we plot *TC* vs *R* in Figs. 4(d) and 5(d). All critical temperature values follow a linear increase with the particle radius. With increase in the

*<sup>e</sup> Y XX N N N Z Z*

*<sup>e</sup> Y XX NN N Z Z*

*<sup>e</sup> Y XX N N N Z Z*

*<sup>e</sup> Y XX N N N*

*<sup>e</sup> Y XX N N N Z Z*

*<sup>e</sup> Y XX N N N Z Z*

*<sup>e</sup> Y XX N N N Z Z*

exp ,

 

*C C CS CS S S PP P C C CS CS S S PP P C C CS CS S S PP P C C CS CS S S PP P*

 

> 

 

 

> 

 

 

> 

> >

exp ,

 

exp ,

 

 

exp ,

 

*C C CS CS S S PP P C C CS CS S S PP P C C CS CS S S PP P C C CS CS S S PP P*

exp ,

 

exp ,

 

> 

> >

. exp . *C C CS CS S S PP P*

11 1 1 11 11 11

1

1

1

1

*Z*

1

1

1

1

*Z*

1

hysteresis loops in Figs. 4–9.

**4. Result and discussions** 

**4.1 Magnetization** 

12 1 2 12 12 12

13 1 3 13 13 13

21 2 1 21 21 21

22 2 2 22 22 22

23 2 3 23 23 23

31 3 1 31 31 31

32 3 2 32 32 32

33 3 3 33 33 33

*Y XX N N N*

 

exp

exp

 11

12

13

21

*Z*

,

(12)

22

23

31

32

*e Z*

,

33

Eqs. (11) and (12) are solved numerically using Newton-Raphson method and normalized magnetization ( *M* ) is easily calculated for both *S* 1 2 and 1 *S* models of homegeneous and core-surface composite NPs. Results are shown as the magnetization curves and

The evolution of normalized magnetization ( ) *M* as a function of the reduced temperature ( *<sup>B</sup>* / <sup>0</sup> *kT J* ) and particle size dependence of the transition temperature *TC* from FM to paramagnetic (PM) phases for homogeneous and composite Ising NPs are shown in Figs. 4 and 5, respectively. The magnetization curves in Fig. 4 are plotted for *S* 1 2 and 1 *S* models of homogeneous NPs using the FM core ( <sup>0</sup>*J* 1 , 1 *CJ* ), FM surface ( *<sup>S</sup>* <sup>0</sup> *J J* ) and FM core-surface ( *CS* <sup>0</sup> *J J* ) interactions and the curves in Fig. 5 are obtained for both models of the composite NPs based on FM core ( *<sup>C</sup>* <sup>0</sup> *J J* ), FM surface ( *<sup>S</sup>* <sup>0</sup> *J J* ) and AFM coresurface ( *CS* <sup>0</sup> *J J* ) interactions. In the plots, different values for the applied magnetic field are considered ( 0.0-0.1 *h* ). The solid curves in the figures correspond to hexagonal lattice while dotted ones denote the square lattice. As seen from the figures, the changes in the magnetization with the reduced temperature point out an interesting aspect for NPs on the hexagonal and square lattices in 2D. The magnetization curves are decreasing from one (1) to zero (0) value while the reduced temperature is increasing (Figs. 4(a), 4(b), 5(a), 5(b)). These decreases terminate at the phase transition temperature (or Curie temperature, *TC* ) from FM phase to PM phase for 0.0 *h* , seen in Figs. 4(c) and 5(c). To show the size dependence of the critical temperature we plot *TC* vs *R* in Figs. 4(d) and 5(d). All critical temperature values follow a linear increase with the particle radius. With increase in the

*<sup>e</sup> Y XX NN N Z Z*

particle radius it approaches to the Crue temperatures of the bulk materials. This is consistent with the mean-field approximation for the magnetic structure of Heisenberg NP (Usov & Gudoshnikov, 2005). On the other hand, it is interesting that composite *S* 1 2 and *S* 1 Ising NPs show smaller transition temperatures than their corresponding homegeneous NPs. This can easily be seen by comparing the same coloured fits in Figs. 4(d) and 5(d).

Fig. 4. Normalized magnetization ( *M* ) vs. reduced temperature ( *<sup>B</sup>* / <sup>0</sup> *kT J* ) and particle size dependence of the transition temperature *TC* from FM to PM phases for homogeneous *S* 1 2 and 1 *S* Ising NPs on the hexagonal and square lattices. 0 1 *C CS S JJ J J* and *h* 0.0-0.1.

Magnetic Properties and Size Effects of Spin-1/2 and Spin-1

<sup>2</sup> 1 *R* **.** 

Models of Core-Surface Nanoparticles in Different Type Lattices 553

materials. The size dependence of the coercive fields *Ch* is determined from the hysteresis loops in Fig. 7. In Fig. 7, the full red and blue circles correspond to the curves obtained for *R* 2 9 in the Figs. 6(a) and 6(c), respectively. Similarly, the open red and blue circles correspond to the curves obtained for *R* 3 11 and *R* 4 10 in Figs. 6(b) and 6(d), respectively. The straight solid and dotted lines are the results from a linear fit to the calculated data. From this fit, it is obvious that the coercive field ( *Ch* ) depends linearly on

Fig. 6. (a) Hysteresis loops of a homegeneous S 1/2 Ising NP on the hexagonal lattice for various sizes. (b) Same as Fig. 6(a) but for NP on the square lattice. (c) Hysteresis loops of a homegeneous S 1 Ising NP on the hexagonal lattice for different sizes. (d) Same as Fig. 6(c) but for NP on the square lattice. 0 1 *C CS S JJ J J* and 0 300 *T Jk <sup>B</sup>* .

Magnetic hysteresis loops of composite *S* 1/2 and 1 *S* Ising NPs on the hexagonal and square lattice (in 2D) structures for various values of particle sizes are shown in Fig. 8. The exchange interactions in the *C* and *S* regions are FM, i.e. 0 *C S JJ J* , while the coupling

Fig. 5. Same as Fig. 4 but for the core-surface composite NPs with 0 0 1, 1. *C S CS JJ J J J*

#### **4.2 Hysteresis loops**

The magnetic field evolution of normalized magnetization (or hysteresis loops) for the homegeneous S 1/2 and S 1 Ising NPs which has different particle sizes and their corresponding coercive field vs. *-*<sup>2</sup> *R* variation are given Figs. 6 and 7, respectively. We consider a FM coupling in core 0 ( ) *CJ J* , surface 0 ( ) *SJ J* and core-surface 0 ( ) *CS J J* regions with 0*J* 1 on the hexagonal and square lattice structures. The hysteresis curves of small diameters, namely with radius *R* 2,4,5 in Figs. 6(a)-6(d), are approximately the same. These behaviours are called superparamegnetic (SP) regime. However, the loops strongly depend on the size of NP. The hysteresis curves of high diamater values change sharply, as also shown in Figs. 6(a)-6(d). Moreover, the hysteresis curves for this type of NPs are broadening while the diamater of NPs is increasing so that it approaches to bulk

Fig. 5. Same as Fig. 4 but for the core-surface composite NPs with

The magnetic field evolution of normalized magnetization (or hysteresis loops) for the homegeneous S 1/2 and S 1 Ising NPs which has different particle sizes and their corresponding coercive field vs. *-*<sup>2</sup> *R* variation are given Figs. 6 and 7, respectively. We consider a FM coupling in core 0 ( ) *CJ J* , surface 0 ( ) *SJ J* and core-surface 0 ( ) *CS J J* regions with 0*J* 1 on the hexagonal and square lattice structures. The hysteresis curves of small diameters, namely with radius *R* 2,4,5 in Figs. 6(a)-6(d), are approximately the same. These behaviours are called superparamegnetic (SP) regime. However, the loops strongly depend on the size of NP. The hysteresis curves of high diamater values change sharply, as also shown in Figs. 6(a)-6(d). Moreover, the hysteresis curves for this type of NPs are broadening while the diamater of NPs is increasing so that it approaches to bulk

0 0 1, 1. *C S CS JJ J J J*

**4.2 Hysteresis loops** 

materials. The size dependence of the coercive fields *Ch* is determined from the hysteresis loops in Fig. 7. In Fig. 7, the full red and blue circles correspond to the curves obtained for *R* 2 9 in the Figs. 6(a) and 6(c), respectively. Similarly, the open red and blue circles correspond to the curves obtained for *R* 3 11 and *R* 4 10 in Figs. 6(b) and 6(d), respectively. The straight solid and dotted lines are the results from a linear fit to the calculated data. From this fit, it is obvious that the coercive field ( *Ch* ) depends linearly on <sup>2</sup> 1 *R* **.** 

Fig. 6. (a) Hysteresis loops of a homegeneous S 1/2 Ising NP on the hexagonal lattice for various sizes. (b) Same as Fig. 6(a) but for NP on the square lattice. (c) Hysteresis loops of a homegeneous S 1 Ising NP on the hexagonal lattice for different sizes. (d) Same as Fig. 6(c) but for NP on the square lattice. 0 1 *C CS S JJ J J* and 0 300 *T Jk <sup>B</sup>* .

Magnetic hysteresis loops of composite *S* 1/2 and 1 *S* Ising NPs on the hexagonal and square lattice (in 2D) structures for various values of particle sizes are shown in Fig. 8. The exchange interactions in the *C* and *S* regions are FM, i.e. 0 *C S JJ J* , while the coupling

Magnetic Properties and Size Effects of Spin-1/2 and Spin-1

Models of Core-Surface Nanoparticles in Different Type Lattices 555

Fig. 8. Same as Fig. 6 but for the composite NP. 0 0 1, . *C S CS JJ J J J*

given in Fig. 9(b).

Finally, the evolutions of hysteresis loops and their coercive field according to the temperature of composite Ising NPs are seen to change monotically as the temperature increases, illustrated in Fig. 9(a) and 9(b), respectively. Since the loops for both models of NPs on the hexagonal and square lattices display the same behaviour we have drawn only the loops of 1 / 2 *S* Ising NP on the hexagonal lattice. In this case, hysteresis for the NP is in superparamagnetic (SP) regime at 0 700 / *<sup>B</sup> J k* . But, the loops for the temperature regime between 0 150 *<sup>B</sup> J k* - <sup>0</sup> 600 / *<sup>B</sup> J k* belong to the FM phase (Fig. 9(a)). The tempereture dependence of the coercivity ( *Ch* ) are determined from the hysteresis loops of Fig. 9(a), as

between *C* and *S* is an AFM exchange constant *CS* <sup>0</sup> *J J* for each type of NP. From the figure, it is clear that the hysteresis loops strongly depend on the particle size. The loops for the *S* 1/2 and 1 *S* Ising NPs on the hexagonal lattice change suddenly in low radius values while those for the *S* 1/2 and 1 *S* Ising NPs on the square lattice in high radius values.

Fig. 7. The coercive field ( *Ch* ) plotted as a function of -2 R for the hysteresis loops of the homegeneous NP in Fig. 6.

between *C* and *S* is an AFM exchange constant *CS* <sup>0</sup> *J J* for each type of NP. From the figure, it is clear that the hysteresis loops strongly depend on the particle size. The loops for the *S* 1/2 and 1 *S* Ising NPs on the hexagonal lattice change suddenly in low radius values while those for the *S* 1/2 and 1 *S* Ising NPs on the square lattice in high radius

Fig. 7. The coercive field ( *Ch* ) plotted as a function of -2 R for the hysteresis loops of the

homegeneous NP in Fig. 6.

values.

Fig. 8. Same as Fig. 6 but for the composite NP. 0 0 1, . *C S CS JJ J J J*

Finally, the evolutions of hysteresis loops and their coercive field according to the temperature of composite Ising NPs are seen to change monotically as the temperature increases, illustrated in Fig. 9(a) and 9(b), respectively. Since the loops for both models of NPs on the hexagonal and square lattices display the same behaviour we have drawn only the loops of 1 / 2 *S* Ising NP on the hexagonal lattice. In this case, hysteresis for the NP is in superparamagnetic (SP) regime at 0 700 / *<sup>B</sup> J k* . But, the loops for the temperature regime between 0 150 *<sup>B</sup> J k* - <sup>0</sup> 600 / *<sup>B</sup> J k* belong to the FM phase (Fig. 9(a)). The tempereture dependence of the coercivity ( *Ch* ) are determined from the hysteresis loops of Fig. 9(a), as given in Fig. 9(b).

Magnetic Properties and Size Effects of Spin-1/2 and Spin-1

**6. Acknowledgements** 

**7. References** 

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ISSN:0378-4371.

1089-7550.

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e1163 ISSN: 0304-8853.

1071-1077, ISSN 1094-1622.

12276-12289, ISSN:1095-3795.

Models of Core-Surface Nanoparticles in Different Type Lattices 557

One of us (Orhan Yalçn) would like to express his gratitude to "The Scientific and Technological Research Council of Turkey" (TÜBİTAK) for financial support (Grant No.

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Fig. 9. (a) Temperature dependence of the hysteresis loops for the *S* 1/2 Ising NP on the hexagonal lattice exhibiting five shells of spins ( 5 *R* ). (b) The coercive field ( *Ch* ) plotted as function of 1/2 ( ) *Bk T* for two models of NP on both structures studied above. 0 0 1, *C S CS JJ J J J* .

### **5. Conclusion**

In the scope of this chapter, we have focused on the magnetic properties with size effects for homogeneous and core-surface composite NPs which have Ising spins ( 1, 1 2 ) on 2D lattice structures (hexagonal, square). The transition for all NPs corresponds to a second-order phase transition in the absence of magnetic field ( 0 *h* ). The spin disorder can be caused by lower coordination of the surface atoms in core-surface NPs broken exchange interactions that produce spin-glass (SG) like state of spatially disordered spin in the surface captions with inhomogeneous surface effects (Kodama, 1999; Kaneyoshi, 2005). Our theoretical observations are scrutinized below briefly.


## **6. Acknowledgements**

One of us (Orhan Yalçn) would like to express his gratitude to "The Scientific and Technological Research Council of Turkey" (TÜBİTAK) for financial support (Grant No. 107T635) during the this work.

## **7. References**

556 Smart Nanoparticles Technology

Fig. 9. (a) Temperature dependence of the hysteresis loops for the *S* 1/2 Ising NP on the hexagonal lattice exhibiting five shells of spins ( 5 *R* ). (b) The coercive field ( *Ch* ) plotted as

In the scope of this chapter, we have focused on the magnetic properties with size effects for homogeneous and core-surface composite NPs which have Ising spins ( 1, 1 2 ) on 2D lattice structures (hexagonal, square). The transition for all NPs corresponds to a second-order phase transition in the absence of magnetic field ( 0 *h* ). The spin disorder can be caused by lower coordination of the surface atoms in core-surface NPs broken exchange interactions that produce spin-glass (SG) like state of spatially disordered spin in the surface captions with inhomogeneous surface effects (Kodama, 1999; Kaneyoshi, 2005). Our theoretical

i. All critical temperature ( ) *TC* values of both types of Ising NPs on 2D lattice structures follow a linear increase with the particle size. With increase in the NP size it approaches to the Crue temperature of the bulk materials. These results agree with the mean-field

ii. From the hysteresis loops for the homegeneous S 1/2 and S 1 Ising NPs which have different sizes and corresponding coercive field ( *Ch* ) vs. *-*<sup>2</sup> *<sup>R</sup>* variations, it is clearly seen that the coercivity strongly depends on the particle size. Due to the superparamegnetic regime the hysteresis curves of small diameters are almost independent of each other while the curves of big diameters sharply change. This

iii. The hysteresis loops at different temperatures show a monotonic change in the coercive field of composite Ising NPs on 2D lattice structures. This property probably is an

magnetic structure of Heisenberg NPs (Usov & Gudoshnikov, 2005).

important aspect in the future high-density magnetic data storage.

shows that the NP approaches to bulk materials.

function of 1/2 ( ) *Bk T* for two models of NP on both structures studied above.

0 0 1, *C S CS JJ J J J* .

observations are scrutinized below briefly.

**5. Conclusion** 


Magnetic Properties and Size Effects of Spin-1/2 and Spin-1

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Leite, V. S. & Figueiredo, W. (2004). Monte Carlo Simulations of Antiferromagnetic Small Particles. *BrazilianJournal of Physics,* Vol. 34, No. 2a, pp.452-454, ISSN 0103-9733. Meijer, P. H. E.; Keskin, M. & Bodegom, E. (October 1986). A Simple Model for the

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**25** 

*Beijing, P. R. China* 

**Organic Semiconductor Nanoparticle Film:** 

Organic semiconductors usually comprising -conjugated structure in their molecules can exhibit excellent optical and electronic properties. They have advantages of simple fabrication and ease of tuning the chemical structure to give desired features. So they can serve as attractive candidates for applications in bio/chemical sensors and optoelectronic devices.1,2 To meet the requirement of domains including information, energy and healthcare, nanoscale materials have emerged as new building blocks for optoelectronic devices, bioimaging agents, and drug delivery carriers in recent years.35 These nanomaterials especially nanoparticles have already shown great potential to offer exciting

Currently, most of the relevant works have been focused on inorganic semiconductor nanoparticles. Besides inorganic ones, organic semiconductor nanoparticles (OSNs) are desirable for a number of reasons. Their properties can be easily tuned for desired applications through the choice of functional molecules and surface modification. Additionally, their facile synthesis, good processability, high photoluminescence (PL) efficiency, high reaction activity, tunable properties, low toxicity and good biocompatibility further make them complementary to the inorganic nanomaterials and highly attractive in the material choice. As a result, OSNs have captured more and more interests. These OSNs can exhibit unique optical and electrical properties different from both the bulk solid samples and their molecular precursors. In comparison with molecule dispersed systems, OSNs are expected to show improved photostability and enhanced emission in various media.6,7 These properties are essentially important in fluorescent labeling applications, such as fluorescence bioimaging and single molecular spectroscopy. For example, single molecules of most commercial dyes undergo photo-bleaching in a few milliseconds under typical excitation conditions under the radiation of a laser beam. On the contrary, because large numbers of chromophores are incorporated in single nanoparticles, they can show bright fluorescence even at a low excitation power. Thus, the fluorescent nanoparticles do not undergo rapid photo-bleaching and give less emission blinking which are generally

**1. Introduction** 

opportunities in these areas.

observed in single molecule experiment.8

**Preparation and Application** 

*School of Materials Science and Engineering, University of Science and Technology Beijing,* 

Xinjun Xu and Lidong Li


## **Organic Semiconductor Nanoparticle Film: Preparation and Application**

Xinjun Xu and Lidong Li

*School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing, P. R. China* 

## **1. Introduction**

560 Smart Nanoparticles Technology

Temizer, U.; Kantar, E.; Keskin, M. & Canko, O. (2008). Multicritical Dynamical Phase

Usov, N. A. & Gudoshnikov, S. A. (2005). Magnetic Structure of a Nanoparticle in Mean-

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Dimensional Magnetic Nanoparticles. *Europhysics Letters,* Vol.58, No. 4, pp. 603-609,

(1995). DC-SQUID Magnetization Measurements of Single Magnetic Particles.

Techniques. *Journal of Applied Physics,* Vol. 87, No. 9, pp. 5094-5096, ISSN: 1089-

Organic semiconductors usually comprising -conjugated structure in their molecules can exhibit excellent optical and electronic properties. They have advantages of simple fabrication and ease of tuning the chemical structure to give desired features. So they can serve as attractive candidates for applications in bio/chemical sensors and optoelectronic devices.1,2 To meet the requirement of domains including information, energy and healthcare, nanoscale materials have emerged as new building blocks for optoelectronic devices, bioimaging agents, and drug delivery carriers in recent years.35 These nanomaterials especially nanoparticles have already shown great potential to offer exciting opportunities in these areas.

Currently, most of the relevant works have been focused on inorganic semiconductor nanoparticles. Besides inorganic ones, organic semiconductor nanoparticles (OSNs) are desirable for a number of reasons. Their properties can be easily tuned for desired applications through the choice of functional molecules and surface modification. Additionally, their facile synthesis, good processability, high photoluminescence (PL) efficiency, high reaction activity, tunable properties, low toxicity and good biocompatibility further make them complementary to the inorganic nanomaterials and highly attractive in the material choice. As a result, OSNs have captured more and more interests. These OSNs can exhibit unique optical and electrical properties different from both the bulk solid samples and their molecular precursors. In comparison with molecule dispersed systems, OSNs are expected to show improved photostability and enhanced emission in various media.6,7 These properties are essentially important in fluorescent labeling applications, such as fluorescence bioimaging and single molecular spectroscopy. For example, single molecules of most commercial dyes undergo photo-bleaching in a few milliseconds under typical excitation conditions under the radiation of a laser beam. On the contrary, because large numbers of chromophores are incorporated in single nanoparticles, they can show bright fluorescence even at a low excitation power. Thus, the fluorescent nanoparticles do not undergo rapid photo-bleaching and give less emission blinking which are generally observed in single molecule experiment.8

Organic Semiconductor Nanoparticle Film: Preparation and Application 563

Poly(phenylene vinylene)s (**15**),27 polyfluorenes (**1618**),2830 polythiophenes (**19**),31 laddertype poly(para-phenylene)s (LPPP) (**20**),32 poly(phenylene ethynylene)s (PPEs) (**21,22**),33 polyanilines (PANIs) (**23**),34 and some copolymers (**24,25**) have been utilized to prepare nanoparticles.35,36 Their molecular structures are shown in Figure 2. Polymers have longer chains than small molecules, so it is possible for polymers to form nanoparticles even with a

single molecule, which is advantageous for researches on single molecule behavior.

Fig. 2. Molecular structures of some polymer semiconductors for synthesizing OSNs.

In 1992, Nakanishi and co-workers proposed the reprecipitation method and demonstrated the nanoparticles with the particle size less than 100 nm dispersed in water.37 Since then, this method has been widely used in nanoparticle preparation for various kinds of molecules. In this method, a hydrophobic organic semiconductor material is dissolved in a good solvent (e.g., THF) for it and poured into a poor solvent (e.g., water), which is miscible with the good solvent. The resulting mixture is stirred vigorously using a magnetic stir bar or a sonicator to assist the formation of nanoparticles. After the nanoparticle formation the organic solvent is removed either by partial vacuum evaporation or by repeated dialysis process to leave behind water-dispersible nanoparticles. The main driving force for the formation of nanoparticles is the hydrophobic effect. When the solution of an organic semiconductor material in organic solvent is added to water, the compound molecules tend to avoid contacting with water. Consequently, in order to achieve minimum exposure they fold or packed into spherical shapes. The preparation does not involve the use of any additives such as surfactants and can be applied to a wide variety of organic semiconductors including both polymers and small molecules given that they are soluble in organic solvents. Moreover, using this method, it is possible to tune the size of nanoparticles by

**3. Methods for synthesizing organic semiconductor nanoparticles** 

adjusting the concentration and the temperature of the solutions.

**2.2 Polymer semiconductors** 

**3.1 Reprecipitation** 

Up to now, most of the OSNs are used in aqueous solutions to serve as biological labels,9,10 chemical sensors,11 and photocatalysis materials.12 To expand the application area of OSNs, there is an increasing effort to prepare OSNs as an active solid film in chemo/biosensors and optical and electronic devices.1316 Compared with bulk solid samples, nanoparticle films provide larger contact interface area, which is highly desired for chemical and biological sensing in sensors. So OSN based functional films tend to become a promising research area for applications in biosensing, energy conversion, photonic and optoelectronic devices.

In this review, after a brief introduction of organic semiconductor materials, we will summarize the methods for preparation OSN films. Then, its application in optical/electronic devices and chemo-/biosensors will be described. We hope this review can cast light on the advances and main problems in the research field of nanoparticle-based devices and sensors.

## **2. Organic semiconductor materials**

Organic semiconductor materials are mainly classified into two categories. One is small molecules and the other is polymers made from repeated small conjugated monomer units.

#### **2.1 Small molecule semiconductors**

Polyphenyl derivatives (**13**),17,18 fused aromatic rings (**48**),19,20 porphyrin derivatives (**9,10**),21,22 metal phthalocyanines (**11**),23 fullerenes (**12**),24 and some fluorescent dyes (**13,14**) have been made into nanoparticles.25,26 Their molecular structures are illustrated in Figure 1. Small molecules are more easily packed to form crystals than polymers, so in some cases the nanoparticles of small-molecule semiconductors can transform to nanorods, nanotubes and nanoflakes.

Fig. 1. Molecular structures of some small molecule semiconductors for synthesizing OSNs.

## **2.2 Polymer semiconductors**

562 Smart Nanoparticles Technology

Up to now, most of the OSNs are used in aqueous solutions to serve as biological labels,9,10 chemical sensors,11 and photocatalysis materials.12 To expand the application area of OSNs, there is an increasing effort to prepare OSNs as an active solid film in chemo/biosensors and optical and electronic devices.1316 Compared with bulk solid samples, nanoparticle films provide larger contact interface area, which is highly desired for chemical and biological sensing in sensors. So OSN based functional films tend to become a promising research area for applications in biosensing, energy conversion, photonic and optoelectronic

In this review, after a brief introduction of organic semiconductor materials, we will summarize the methods for preparation OSN films. Then, its application in optical/electronic devices and chemo-/biosensors will be described. We hope this review can cast light on the advances and main problems in the research field of nanoparticle-based

Organic semiconductor materials are mainly classified into two categories. One is small molecules and the other is polymers made from repeated small conjugated monomer units.

Polyphenyl derivatives (**13**),17,18 fused aromatic rings (**48**),19,20 porphyrin derivatives (**9,10**),21,22 metal phthalocyanines (**11**),23 fullerenes (**12**),24 and some fluorescent dyes (**13,14**) have been made into nanoparticles.25,26 Their molecular structures are illustrated in Figure 1. Small molecules are more easily packed to form crystals than polymers, so in some cases the nanoparticles of small-molecule semiconductors can transform to nanorods, nanotubes and

Fig. 1. Molecular structures of some small molecule semiconductors for synthesizing OSNs.

devices.

devices and sensors.

nanoflakes.

**2. Organic semiconductor materials** 

**2.1 Small molecule semiconductors** 

Poly(phenylene vinylene)s (**15**),27 polyfluorenes (**1618**),2830 polythiophenes (**19**),31 laddertype poly(para-phenylene)s (LPPP) (**20**),32 poly(phenylene ethynylene)s (PPEs) (**21,22**),33 polyanilines (PANIs) (**23**),34 and some copolymers (**24,25**) have been utilized to prepare nanoparticles.35,36 Their molecular structures are shown in Figure 2. Polymers have longer chains than small molecules, so it is possible for polymers to form nanoparticles even with a single molecule, which is advantageous for researches on single molecule behavior.

Fig. 2. Molecular structures of some polymer semiconductors for synthesizing OSNs.

## **3. Methods for synthesizing organic semiconductor nanoparticles**

## **3.1 Reprecipitation**

In 1992, Nakanishi and co-workers proposed the reprecipitation method and demonstrated the nanoparticles with the particle size less than 100 nm dispersed in water.37 Since then, this method has been widely used in nanoparticle preparation for various kinds of molecules. In this method, a hydrophobic organic semiconductor material is dissolved in a good solvent (e.g., THF) for it and poured into a poor solvent (e.g., water), which is miscible with the good solvent. The resulting mixture is stirred vigorously using a magnetic stir bar or a sonicator to assist the formation of nanoparticles. After the nanoparticle formation the organic solvent is removed either by partial vacuum evaporation or by repeated dialysis process to leave behind water-dispersible nanoparticles. The main driving force for the formation of nanoparticles is the hydrophobic effect. When the solution of an organic semiconductor material in organic solvent is added to water, the compound molecules tend to avoid contacting with water. Consequently, in order to achieve minimum exposure they fold or packed into spherical shapes. The preparation does not involve the use of any additives such as surfactants and can be applied to a wide variety of organic semiconductors including both polymers and small molecules given that they are soluble in organic solvents. Moreover, using this method, it is possible to tune the size of nanoparticles by adjusting the concentration and the temperature of the solutions.

Organic Semiconductor Nanoparticle Film: Preparation and Application 565

prepared compared to the repreciptation and miniemulsion method. However, as particle formation only occurs within the narrow laser beam, only small amounts of these nanoparticle dispersions can be prepared. Furthermore, the intense laser light may cause severe photochemical damage especially in the case of rather sensitive organic materials.

To overcome the above mentioned drawbacks, an approach for preparation of concentrated dispersions of organic nanoparticles by direct condensation the vapor of an organic semiconductor material into a liquid dispersion medium has been developed.19 This approach combines elements from the physical vapor deposition (PVD) technique with cooling and condensation of the vapor directly inside a liquid. An illustration of the apparatus used in the direct condensation method is shown in Figure 3. The apparatus consists of four main parts: a tube furnace, a double-walled heated-vapor injection tube, a condensation and receiving vessel, and a vacuum pumping system. Temperatures in the different zones are adjusted according to the organic material to be evaporated, and were maintained such that no condensation of the organic materials occurred in the tubes. The evaporated organic material will be carried by the inert gas flow to the vapor-injection tube, which guides the organic material into a liquid condensation medium. The condensation liquid typically consists of an aqueous solution containing surfactants or polymeric stabilizers. It rapidly cools down the gas leading to condensation of the organic vapor and formation of nanoparticles. These nanoparticles are subsequently stabilized in situ by the surfactant or polymeric additive at the bubble/liquid interface to form a stable dispersion. The size of OSNs prepared by this method is in the range of 100200 nm for fused aromatic

Fig. 3. Apparatus for direct condensation of organic vapor (Reproduced from Ref. 19,

Micelles can be used as soft templates to conduct the polymerization in the aqueous heterophase system. By dispersing the appropriate monomers, surfactant, solvent, and

hydrocarbons such as pentacene, rubrene, and tetracene.

Copyright 2009 Wiley-VCH Verlag GmbH & Co.)

**3.5 Template-based approaches** 

**3.5.1 Soft templates** 

## **3.2 Miniemulsion**

This is another commonly used method in the synthesis of OSNs. Using this method, Landfester and co-workers prepared nanoparticles from various polymers.38 To prepare OSNs, the compound is dissolved in a water immiscible organic solvent and then the resulting solution is injected into an aqueous solution of an appropriate surfactant. The mixture is stirred vigorously by ultrasonicating to form stable miniemulsions containing small droplets of the polymer solution. The organic solvent is then evaporated to obtain a stable dispersion of polymer nanoparticles in water. The size of nanoparticles could vary from 30 nm to 500 nm depending on the concentration of the polymer solution. However, the droplets could also be destabilized by Ostwald ripening as well as the flocculation caused by the coalescence of droplets. To prevent flocculation appropriate surfactants are needed, while Ostwald ripening can be suppressed by addition of a hydrophobic agent (hydrophobe) to the dispersed phase. The hydrophobic agent promotes the formation of an osmotic pressure inside the droplets that counteracts the Laplace pressure (the pressure difference between the inside and the outside of a droplet) preventing diffusion from one droplet to the surrounding aqueous medium.

## **3.3 Pulsed-laser ablation**

In this method, OSNs are formed by pulsed-laser ablation of large, several-micrometersized, organic crystals suspended in a liquid.39,40 The powder of organic semiconductors was added to an aqueous solution containing surfactants such as sodium dodecyl sulfate (SDS). Then, the suspension was sonicated for a while. The mixture was put into a quartz cuvette, stirred vigorously with a magnetic stirrer, and then simultaneously exposed to the second harmonic of a nanosecond YAG laser. The spot area was approximately tens of mm2, and the laser intensity was adjusted using a polarizer. The laser ablation mechanism for nanosecond laser ablation is based on photothermalization. The organic crystals in solutions absorb the laser light leading to a local increase in temperature and evaporation of a small amount of material from the crystal surface. The vaporized material is rapidly cooled by the surrounding liquid to form nanoparticles.

For nanosecond photothermal ablation in a solvent, rapid temperature elevation upon pulse excitation is compensated by a cooling process due to thermal diffusion to the solvent, and its balance gives the transient temperature determining the nanoparticle size. Higher fluence gives higher effective transient temperature, leading to efficient fragmentation to smaller particles. One advantage of the laser ablation method is its high controllability of size and phase of nanoparticles by tuning laser pulse width, wavelength, fluence, and shot number. However, this method is limited to fabricate OSNs based on small molecules only.

## **3.4 Direct condensation of organic vapor**

Due to the fact that in the reprecipitation or miniemulsion process a solution of organic material (of typically about millimolar concentration) is added to a large excess of nonsolvent, only very dilute particle dispersions can be obtained. That is one main disadvantage of these methods. The second one is that the reprecipitation or miniemulsion method is not applicable for organic materials that are poorly soluble in organic solvents (such as pentacene). As for laser ablation, more concentrated nanoparticle dispersions can be

This is another commonly used method in the synthesis of OSNs. Using this method, Landfester and co-workers prepared nanoparticles from various polymers.38 To prepare OSNs, the compound is dissolved in a water immiscible organic solvent and then the resulting solution is injected into an aqueous solution of an appropriate surfactant. The mixture is stirred vigorously by ultrasonicating to form stable miniemulsions containing small droplets of the polymer solution. The organic solvent is then evaporated to obtain a stable dispersion of polymer nanoparticles in water. The size of nanoparticles could vary from 30 nm to 500 nm depending on the concentration of the polymer solution. However, the droplets could also be destabilized by Ostwald ripening as well as the flocculation caused by the coalescence of droplets. To prevent flocculation appropriate surfactants are needed, while Ostwald ripening can be suppressed by addition of a hydrophobic agent (hydrophobe) to the dispersed phase. The hydrophobic agent promotes the formation of an osmotic pressure inside the droplets that counteracts the Laplace pressure (the pressure difference between the inside and the outside of a droplet) preventing diffusion from one

In this method, OSNs are formed by pulsed-laser ablation of large, several-micrometersized, organic crystals suspended in a liquid.39,40 The powder of organic semiconductors was added to an aqueous solution containing surfactants such as sodium dodecyl sulfate (SDS). Then, the suspension was sonicated for a while. The mixture was put into a quartz cuvette, stirred vigorously with a magnetic stirrer, and then simultaneously exposed to the second harmonic of a nanosecond YAG laser. The spot area was approximately tens of mm2, and the laser intensity was adjusted using a polarizer. The laser ablation mechanism for nanosecond laser ablation is based on photothermalization. The organic crystals in solutions absorb the laser light leading to a local increase in temperature and evaporation of a small amount of material from the crystal surface. The vaporized material is rapidly cooled by the

For nanosecond photothermal ablation in a solvent, rapid temperature elevation upon pulse excitation is compensated by a cooling process due to thermal diffusion to the solvent, and its balance gives the transient temperature determining the nanoparticle size. Higher fluence gives higher effective transient temperature, leading to efficient fragmentation to smaller particles. One advantage of the laser ablation method is its high controllability of size and phase of nanoparticles by tuning laser pulse width, wavelength, fluence, and shot number.

Due to the fact that in the reprecipitation or miniemulsion process a solution of organic material (of typically about millimolar concentration) is added to a large excess of nonsolvent, only very dilute particle dispersions can be obtained. That is one main disadvantage of these methods. The second one is that the reprecipitation or miniemulsion method is not applicable for organic materials that are poorly soluble in organic solvents (such as pentacene). As for laser ablation, more concentrated nanoparticle dispersions can be

However, this method is limited to fabricate OSNs based on small molecules only.

**3.2 Miniemulsion** 

droplet to the surrounding aqueous medium.

surrounding liquid to form nanoparticles.

**3.4 Direct condensation of organic vapor** 

**3.3 Pulsed-laser ablation** 

prepared compared to the repreciptation and miniemulsion method. However, as particle formation only occurs within the narrow laser beam, only small amounts of these nanoparticle dispersions can be prepared. Furthermore, the intense laser light may cause severe photochemical damage especially in the case of rather sensitive organic materials.

To overcome the above mentioned drawbacks, an approach for preparation of concentrated dispersions of organic nanoparticles by direct condensation the vapor of an organic semiconductor material into a liquid dispersion medium has been developed.19 This approach combines elements from the physical vapor deposition (PVD) technique with cooling and condensation of the vapor directly inside a liquid. An illustration of the apparatus used in the direct condensation method is shown in Figure 3. The apparatus consists of four main parts: a tube furnace, a double-walled heated-vapor injection tube, a condensation and receiving vessel, and a vacuum pumping system. Temperatures in the different zones are adjusted according to the organic material to be evaporated, and were maintained such that no condensation of the organic materials occurred in the tubes. The evaporated organic material will be carried by the inert gas flow to the vapor-injection tube, which guides the organic material into a liquid condensation medium. The condensation liquid typically consists of an aqueous solution containing surfactants or polymeric stabilizers. It rapidly cools down the gas leading to condensation of the organic vapor and formation of nanoparticles. These nanoparticles are subsequently stabilized in situ by the surfactant or polymeric additive at the bubble/liquid interface to form a stable dispersion. The size of OSNs prepared by this method is in the range of 100200 nm for fused aromatic hydrocarbons such as pentacene, rubrene, and tetracene.

Fig. 3. Apparatus for direct condensation of organic vapor (Reproduced from Ref. 19, Copyright 2009 Wiley-VCH Verlag GmbH & Co.)

#### **3.5 Template-based approaches**

#### **3.5.1 Soft templates**

Micelles can be used as soft templates to conduct the polymerization in the aqueous heterophase system. By dispersing the appropriate monomers, surfactant, solvent, and

Organic Semiconductor Nanoparticle Film: Preparation and Application 567

corresponding electrode under the driving of electric field force.50 The films thus obtained

This technique for prepare OSN film is based on a rapid expansion process of supercritical solution (e.g. CO2) which contains dissolved organic semiconductors.51 By using an apparatus illustrated in Figure 5, organic semiconductors dispersed in supercritical CO2 solution can be sprayed on the substrate through a long stainless steel capillary tube attached to the chamber. After the rapid evaporation of CO2, OSNs are precipitated on the surface of substrates. Using process conditions of compressed-fluid precipitation and formulation, it appears possible to produce organic nanoparticles with tunable sizes and optical properties. This capability opens up avenues to create devices and functional films using organic nanoparticles as building blocks, which may be tailored for the application.

Fig. 5. Apparatus for preparation of OSN films by RESS technique (Reproduced from Ref.

were washed with clean solvent and dried in air.

Fig. 4. Apparatus for electrophoretic deposition of OSNs

51, Copyright 2006 Wiley-VCH Verlag GmbH & Co.)

**4.2 Rapid expansion of supercritical solution (RESS) technique** 

catalysts in an aqueous medium, the Glaser coupling reaction can be carried out exclusively within the hydrophobic interior of surfactant micelles to produce the poly(arylene diethynylenes) nanoparticles.41 Similarly, poly(p-phenyleneethynylene) nanoparticles can also be prepared by this method.42

The molecular structure of surfactant used in the aqueous heterophase system has a big influence on the shape of the formed nanoparticles. Using dodecylbenzene sulfonic acid as a surfactant and doping agent for poly(3,4-ethylenedioxythiophene) (PEDOT) yielded amorphous and polydisperse particles with diameters in the range of 35100 nm.43 Short chain alcohol ethoxylate surfactants yielded more spherical particles, but significant amounts of surfactant residue were trapped on the PEDOT latex, and secondary nucleation could not be completely suppressed.44

These examples show that the soft template approach has been a versatile method for preparing conjugated polymer nanoparticles. However, control over important parameters such as particle diameter and polydispersity by this method is often not easy. Many of these issues can be addressed by the use of a hard template.

## **3.5.2 Hard templates**

Due to the shape persistence of hard templates, they typically offer a more reliable way of directing the shape of conjugated polymer nanostructures. Monodisperse nanoparticles such as silica and polystyrene particles can be used as a hard template for preparing core-shell structures. Conjugated polymers such as polypyrrole, PANI and PEDOT, highly fluorescent polymers such as PPE have also been attached to the surface of colloidal particles.45 The conjugated polymers can either be polymerized in situ from monomers absorbed on the surface of the particle templates or be deposited from a layer-by-layer technique through electrostatic interactions.46

## **4. Methods for preparing nanoparticles film**

Since OSNs are usually synthesized in solution with a low concentration, conventional thin film forming processes such as spin-coating or dip-casting are not appropriate for preparing OSN films. So other methods have been developed to prepare good OSN films.

## **4.1 Electrophoresis deposition**

Electrophoretic deposition, which is based on the electrical collection of small, charged particles dispersed in dielectric liquids, is one of the most widely used coating methods capable of patterning. It has been reported that the phosphors for a cathode ray tube,47 the oxide superconductors,48 and the carbon nanotubes for a cold cathode have been successfully coated by electrophoretic deposition.49 As for OSNs in solutions, they often carried charges on their surface. Such surface charges are generated according to Coehn's empirical rule. That is, the electrostatic charge separation may occur when two dielectrics are in intimate contact. The substance with the higher dielectric constant will receive the positive charge, while the other one will receive the negative charge. As illustrated in Figure 4, a DC voltage (usually hundreds of volts) was applied between two ITO-coated glass plates soaked in the nanoparticle suspension. Then nanoparticles will move towards the

catalysts in an aqueous medium, the Glaser coupling reaction can be carried out exclusively within the hydrophobic interior of surfactant micelles to produce the poly(arylene diethynylenes) nanoparticles.41 Similarly, poly(p-phenyleneethynylene) nanoparticles can

The molecular structure of surfactant used in the aqueous heterophase system has a big influence on the shape of the formed nanoparticles. Using dodecylbenzene sulfonic acid as a surfactant and doping agent for poly(3,4-ethylenedioxythiophene) (PEDOT) yielded amorphous and polydisperse particles with diameters in the range of 35100 nm.43 Short chain alcohol ethoxylate surfactants yielded more spherical particles, but significant amounts of surfactant residue were trapped on the PEDOT latex, and secondary nucleation

These examples show that the soft template approach has been a versatile method for preparing conjugated polymer nanoparticles. However, control over important parameters such as particle diameter and polydispersity by this method is often not easy. Many of these

Due to the shape persistence of hard templates, they typically offer a more reliable way of directing the shape of conjugated polymer nanostructures. Monodisperse nanoparticles such as silica and polystyrene particles can be used as a hard template for preparing core-shell structures. Conjugated polymers such as polypyrrole, PANI and PEDOT, highly fluorescent polymers such as PPE have also been attached to the surface of colloidal particles.45 The conjugated polymers can either be polymerized in situ from monomers absorbed on the surface of the particle templates or be deposited from a layer-by-layer technique through

Since OSNs are usually synthesized in solution with a low concentration, conventional thin film forming processes such as spin-coating or dip-casting are not appropriate for preparing

Electrophoretic deposition, which is based on the electrical collection of small, charged particles dispersed in dielectric liquids, is one of the most widely used coating methods capable of patterning. It has been reported that the phosphors for a cathode ray tube,47 the oxide superconductors,48 and the carbon nanotubes for a cold cathode have been successfully coated by electrophoretic deposition.49 As for OSNs in solutions, they often carried charges on their surface. Such surface charges are generated according to Coehn's empirical rule. That is, the electrostatic charge separation may occur when two dielectrics are in intimate contact. The substance with the higher dielectric constant will receive the positive charge, while the other one will receive the negative charge. As illustrated in Figure 4, a DC voltage (usually hundreds of volts) was applied between two ITO-coated glass plates soaked in the nanoparticle suspension. Then nanoparticles will move towards the

OSN films. So other methods have been developed to prepare good OSN films.

also be prepared by this method.42

could not be completely suppressed.44

**3.5.2 Hard templates** 

electrostatic interactions.46

**4.1 Electrophoresis deposition** 

issues can be addressed by the use of a hard template.

**4. Methods for preparing nanoparticles film** 

corresponding electrode under the driving of electric field force.50 The films thus obtained were washed with clean solvent and dried in air.

Fig. 4. Apparatus for electrophoretic deposition of OSNs

## **4.2 Rapid expansion of supercritical solution (RESS) technique**

This technique for prepare OSN film is based on a rapid expansion process of supercritical solution (e.g. CO2) which contains dissolved organic semiconductors.51 By using an apparatus illustrated in Figure 5, organic semiconductors dispersed in supercritical CO2 solution can be sprayed on the substrate through a long stainless steel capillary tube attached to the chamber. After the rapid evaporation of CO2, OSNs are precipitated on the surface of substrates. Using process conditions of compressed-fluid precipitation and formulation, it appears possible to produce organic nanoparticles with tunable sizes and optical properties. This capability opens up avenues to create devices and functional films using organic nanoparticles as building blocks, which may be tailored for the application.

Fig. 5. Apparatus for preparation of OSN films by RESS technique (Reproduced from Ref. 51, Copyright 2006 Wiley-VCH Verlag GmbH & Co.)

Organic Semiconductor Nanoparticle Film: Preparation and Application 569

Fig. 6. Scheme for the solvent-evaporation-induced self-assembly of OSNs on the substrates to form films. (Reproduced from Ref. 53, Copyright 2010 The American Chemical Society)

compounds with certain structures and is not a universal method for most polymer semiconducting materials. In addition, OSNs formed by this method are discrete and

Fig. 7. Photograph of the 1-cyano-trans-1-(4'-methylbiphenyl)-2-[4'-(2'-pyridyl)

from Ref. 54, Copyright 2007 Wiley-VCH Verlag GmbH & Co.)

phenyl]ethylene (Py-CN-MBE)/poly(methyl methacrylate) (PMMA) film before and after exposure to dichloromethane vapor (Left panel) and the SEM image of the Py-CN-MBE nanoparticles formed by the vapor-driven self-assembly process (Right panel). (Reproduced

continuous OSNs films can not be obtained.

Additionally, it is possible to mix building blocks of organic nanoparticles or combine different molecules within a building block. However, the limitation of this technique is that only small molecule based OSN film can be prepared while preparation of polymer based OSN films by this technique is not available. Also, surfactants such as the ammoniumexchanged Fluorolink 7004 (Cl(CF2CF(CF3)O)nCF2COO–NH4+) need to be introduced into the supercritical solution to adjust the size of ultimate nanoparticles.51

## **4.3 Solvent-evaporation induced self-assembly**

The evaporation behavior during the drying process of a solution plays a vital role in controlling the film morphology and the distribution of solute in the final films. It is well known that when a liquid drop containing dispersed solids evaporates on a surface, it commonly leaves a dense, ring-like deposit along the perimeter. The reason is that the contact line is pinned during the drying process, leading to a fixed contact area on the substrate. Therefore, a capillary flow of the solvent occurs from the center of the drop to the contact line to replenish the evaporation loss, and this flow transports the solutes to its periphery.52 As far as the OSNs solution is concerned, such phenomenon will result in an undesirably uneven distribution of nanoparticles across the deposited films. However, if another flow which has an opposite direction to the capillary flow is introduced into the OSNs solutions during the drying process, the transportation of nanoparticles towards the contact line by the capillary flow is expected to be counteracted. Marangoni effect is usually observed in a solution containing two kinds of solvents with different surface tensions and boiling points, and a flow is induced by the surface tension gradient existed in the solution caused by solvent evaporation. Such a flow is named as the Marangoni flow, and its direction can be controlled to be the same as the spreading of a drop on a solid surface (outward) or opposite to the spreading (inward), depending on the boiling points and surface tensions of the two solvents to be mixed. Consequently, by proper introduction of a second solvent into the solution, a Marangoni flow with an opposite direction to the capillary flow can be achieved.

The solvent-evaporation induced self-assembly method for preparing the thin nanoparticles films from their OSNs solutions is illustrated in Figure 6.53 By using ethylene glycol (EG) as the second solvent with a high boiling point but a low surface tension, the capillary flow in the solution can be counterbalanced by the Marangoni flow. The self-assembly of nanoparticles on the substrate can thus be achieved through the nanoparticle-substrate and nanoparticle-nanoparticle van der Waals interactions.

#### **4.4 Vapor-driven self-assembly**

The vapor-driven self-assembly process is based on the selective phase demixing and selfassembled aggregate formation. Such behaviors occur from a molecularly dispersed solid solution of specific fluorescent molecules in a polymer matrix when it is exposed to volatile organic solvent vapors.54 After solvent exposure, the supramolecular self-assembly of organic semiconductor materials leads to the formation of spherical nanoparticles (see Figure 7). The advantage of this method is to form nanoparticles films *in situ* on the substrate. Nevertheless, this kind of method is only appropriate for small-molecule

Additionally, it is possible to mix building blocks of organic nanoparticles or combine different molecules within a building block. However, the limitation of this technique is that only small molecule based OSN film can be prepared while preparation of polymer based OSN films by this technique is not available. Also, surfactants such as the ammoniumexchanged Fluorolink 7004 (Cl(CF2CF(CF3)O)nCF2COO–NH4+) need to be introduced into

The evaporation behavior during the drying process of a solution plays a vital role in controlling the film morphology and the distribution of solute in the final films. It is well known that when a liquid drop containing dispersed solids evaporates on a surface, it commonly leaves a dense, ring-like deposit along the perimeter. The reason is that the contact line is pinned during the drying process, leading to a fixed contact area on the substrate. Therefore, a capillary flow of the solvent occurs from the center of the drop to the contact line to replenish the evaporation loss, and this flow transports the solutes to its periphery.52 As far as the OSNs solution is concerned, such phenomenon will result in an undesirably uneven distribution of nanoparticles across the deposited films. However, if another flow which has an opposite direction to the capillary flow is introduced into the OSNs solutions during the drying process, the transportation of nanoparticles towards the contact line by the capillary flow is expected to be counteracted. Marangoni effect is usually observed in a solution containing two kinds of solvents with different surface tensions and boiling points, and a flow is induced by the surface tension gradient existed in the solution caused by solvent evaporation. Such a flow is named as the Marangoni flow, and its direction can be controlled to be the same as the spreading of a drop on a solid surface (outward) or opposite to the spreading (inward), depending on the boiling points and surface tensions of the two solvents to be mixed. Consequently, by proper introduction of a second solvent into the solution, a Marangoni flow with an opposite direction to the

The solvent-evaporation induced self-assembly method for preparing the thin nanoparticles films from their OSNs solutions is illustrated in Figure 6.53 By using ethylene glycol (EG) as the second solvent with a high boiling point but a low surface tension, the capillary flow in the solution can be counterbalanced by the Marangoni flow. The self-assembly of nanoparticles on the substrate can thus be achieved through the nanoparticle-substrate and

The vapor-driven self-assembly process is based on the selective phase demixing and selfassembled aggregate formation. Such behaviors occur from a molecularly dispersed solid solution of specific fluorescent molecules in a polymer matrix when it is exposed to volatile organic solvent vapors.54 After solvent exposure, the supramolecular self-assembly of organic semiconductor materials leads to the formation of spherical nanoparticles (see Figure 7). The advantage of this method is to form nanoparticles films *in situ* on the

substrate. Nevertheless, this kind of method is only appropriate for small-molecule

the supercritical solution to adjust the size of ultimate nanoparticles.51

**4.3 Solvent-evaporation induced self-assembly** 

capillary flow can be achieved.

**4.4 Vapor-driven self-assembly** 

nanoparticle-nanoparticle van der Waals interactions.

Fig. 6. Scheme for the solvent-evaporation-induced self-assembly of OSNs on the substrates to form films. (Reproduced from Ref. 53, Copyright 2010 The American Chemical Society)

compounds with certain structures and is not a universal method for most polymer semiconducting materials. In addition, OSNs formed by this method are discrete and continuous OSNs films can not be obtained.

Fig. 7. Photograph of the 1-cyano-trans-1-(4'-methylbiphenyl)-2-[4'-(2'-pyridyl) phenyl]ethylene (Py-CN-MBE)/poly(methyl methacrylate) (PMMA) film before and after exposure to dichloromethane vapor (Left panel) and the SEM image of the Py-CN-MBE nanoparticles formed by the vapor-driven self-assembly process (Right panel). (Reproduced from Ref. 54, Copyright 2007 Wiley-VCH Verlag GmbH & Co.)

Organic Semiconductor Nanoparticle Film: Preparation and Application 571

singularities around the particles that may result in regions of pinhole formation in electronic devices. Poly(vinyl alcohol),57 hexadecyl-modified poly(ethylene oxide) (PEO),55 and PEDOT:PSS 5860 are polymer matrixes used for this purpose. These binders have virtually no effect on the color characteristics of the electroluminescence spectrum since PVA, PEO, and PEDOT:PSS have a negligible absorption in the luminance regime of OSNs. Although by this means the film quality is improved, the additives remained in the nanoparticles films will be disadvantages to the optical and electrical properties of OSNs. For example, when using PEDOT:PSS as an additive to the OSNs aqueous solution for preparing thin nanoparticles films by spin-coating, the acidity of PEDOT:PSS will deteriorate the

LPPP, poly(9-vinylcarbazole) (PVK), 2-(4-tert-butylphenyl)-5-(4-biphenylyl)-1,3,4-oxadiazole (tBu-PBD), coumarins, nile red, nanoparticles prepared by miniemulsion method, core-shell nanoparticles with perylene as the core and poly[methyl methacrylate-co-vinylcarbazole-co-2-(3'-nitrophenyl)-5-(4'-acryloylphenyl)-1,3,4-oxadiazole] as the shell formed by emulsion copolymerization, poly(3-octadecylthiophene) nanoparticles prepared by reprecipitation method, multi-component nanoparticles prepared by RESS process or miniemulsion method have been reported to serve as an active layer in organic light-emitting diodes.61 For nanoparticles synthesized by both miniemulsion and RESS methods, surfactants, stabilizing agents or hydrophobes are necessary and can hardly be removed. Such additives will be disadvantageous to the native optoelectronic properties of OSNs in devices. It would be still interesting to fabricate optoelectronic devices from OSNs prepared via the reprecipitation method in which there would be no additives including surfactants, stabilizing agents and hydrophobes. Electrophoretic deposition of OSN films from reprecipitation-processed nanoparticle solutions has been employed in fabricating OLEDs.62 Although an electroluminescent emission from the device could be observed, the emission is not uniform because the nanoporosity of the OSN film prepared by electrophoretic deposition probably causes fatal pin-holes. As a result, an approach for preparing high-quality OSN films from reprecipitation-processed nanoparticle solutions is highly desired. Fortunately, the solventevaporation induced self-assembly method introduced above can meet this requirement. Currently, the main drawback of this method for fabricating OLEDs is that the solvent evaporation period is time-consuming. If there are some ways are found to overcome this

luminescent properties of the conjugated compounds largely.

**5.1 Organic light-emitting diodes** 

**5.2 Organic field-effect transistors** 

**5. Applications of OSN film in optical and electronic devices** 

drawback, this method is very promising for fabricating OSN based OLEDs.

Organic field-effect transistors (OFETs) fabricated using solution-deposition techqiques are particularly well-suited for large-area electronic devices. For meaningful practical applications, the organic semiconductors need to provide FET mobilities close to that of amorphous silicon. This will necessitate establishment of proper molecular order in the semiconductors to achieve high mobilities, since charge-carrier transport in organic semiconductors is dominated by hopping and disordered materials are not efficient chargetransporting media. In nanoparticles, molecules are closely packed and they are usually

## **4.5 Inkjet printing**

As mentioned above, when a droplet of OSN solution is dripped on the surface of a substrate, the OSNs tend to form coffee-stains after the evaporation of the solvent. So direct inkjet printing of OSN solutions can not provide good film morphology. To avoid this drawback, an aqueous dispersion of semiconducting polymer nanospheres is deposited by inkjet printing onto a polymer surface patterned by soft embossing.55 By interaction between the spheres and the undulated surface a self assembly process is triggered, resulting in the formation of OSN nanostructures determined by the template.

Fig. 8. The fabrication process for functional nanostructures from inkjet printing. Reprodcued from Ref. 55 (Copyright 2008 The Royal Society of Chemistry).

As shown in Figure 8, after a droplet of the OSN solution was printed on the surface of the structured polymeric template layer, OSNs assemble in the grooves of the embossed surface. This method relies on the application of a polymer template layer, so that the patterned structure that is formed with the OSNs can be incorporated into a device.

## **4.6 Spin-coating**

Due to the very low concentration of OSN solutions, good film can hardly be formed by spin-coating or dip-coating method without any additives. As a result, auxiliary underlayers or additives such as surfactants or polymer matrix have to be introduced to assist the deposition of nanoparticle films. As mentioned above, nanoparticles usually carry charges on their surfaces when they are dispersed in solutions. Therefore, negatively charged nanoparticles can be formed on polycationic films with the help of electrostatic interactions via spin-coating and vice versa. Layers of LPPP nanoparticles were spin-coated on poly(allylamine hydrochloride) (PAH) can exhibit a homogeneous fluorescence over large areas.38 Similarly, conjugated polymer nanoparticles such as polyfluorene derivatives and LPPP spin-coated on poly(3,4-ethylenedioxythiophene):poly(4-styrenesulfonate) (PEDOT:PSS) film can also exhibit a good film morphology.32,56 Besides auxiliary underlayers, polymer matrix can also been utilized to act as a binder to improve the film quality deposited from OSN solutions. This kind of binder for the nanoparticles can also assist in the reduction of electric field singularities around the particles that may result in regions of pinhole formation in electronic devices. Poly(vinyl alcohol),57 hexadecyl-modified poly(ethylene oxide) (PEO),55 and PEDOT:PSS 5860 are polymer matrixes used for this purpose. These binders have virtually no effect on the color characteristics of the electroluminescence spectrum since PVA, PEO, and PEDOT:PSS have a negligible absorption in the luminance regime of OSNs. Although by this means the film quality is improved, the additives remained in the nanoparticles films will be disadvantages to the optical and electrical properties of OSNs. For example, when using PEDOT:PSS as an additive to the OSNs aqueous solution for preparing thin nanoparticles films by spin-coating, the acidity of PEDOT:PSS will deteriorate the luminescent properties of the conjugated compounds largely.

## **5. Applications of OSN film in optical and electronic devices**

## **5.1 Organic light-emitting diodes**

570 Smart Nanoparticles Technology

As mentioned above, when a droplet of OSN solution is dripped on the surface of a substrate, the OSNs tend to form coffee-stains after the evaporation of the solvent. So direct inkjet printing of OSN solutions can not provide good film morphology. To avoid this drawback, an aqueous dispersion of semiconducting polymer nanospheres is deposited by inkjet printing onto a polymer surface patterned by soft embossing.55 By interaction between the spheres and the undulated surface a self assembly process is triggered, resulting in the

formation of OSN nanostructures determined by the template.

Fig. 8. The fabrication process for functional nanostructures from inkjet printing. Reprodcued from Ref. 55 (Copyright 2008 The Royal Society of Chemistry).

structure that is formed with the OSNs can be incorporated into a device.

As shown in Figure 8, after a droplet of the OSN solution was printed on the surface of the structured polymeric template layer, OSNs assemble in the grooves of the embossed surface. This method relies on the application of a polymer template layer, so that the patterned

Due to the very low concentration of OSN solutions, good film can hardly be formed by spin-coating or dip-coating method without any additives. As a result, auxiliary underlayers or additives such as surfactants or polymer matrix have to be introduced to assist the deposition of nanoparticle films. As mentioned above, nanoparticles usually carry charges on their surfaces when they are dispersed in solutions. Therefore, negatively charged nanoparticles can be formed on polycationic films with the help of electrostatic interactions via spin-coating and vice versa. Layers of LPPP nanoparticles were spin-coated on poly(allylamine hydrochloride) (PAH) can exhibit a homogeneous fluorescence over large areas.38 Similarly, conjugated polymer nanoparticles such as polyfluorene derivatives and LPPP spin-coated on poly(3,4-ethylenedioxythiophene):poly(4-styrenesulfonate) (PEDOT:PSS) film can also exhibit a good film morphology.32,56 Besides auxiliary underlayers, polymer matrix can also been utilized to act as a binder to improve the film quality deposited from OSN solutions. This kind of binder for the nanoparticles can also assist in the reduction of electric field

**4.5 Inkjet printing** 

**4.6 Spin-coating** 

LPPP, poly(9-vinylcarbazole) (PVK), 2-(4-tert-butylphenyl)-5-(4-biphenylyl)-1,3,4-oxadiazole (tBu-PBD), coumarins, nile red, nanoparticles prepared by miniemulsion method, core-shell nanoparticles with perylene as the core and poly[methyl methacrylate-co-vinylcarbazole-co-2-(3'-nitrophenyl)-5-(4'-acryloylphenyl)-1,3,4-oxadiazole] as the shell formed by emulsion copolymerization, poly(3-octadecylthiophene) nanoparticles prepared by reprecipitation method, multi-component nanoparticles prepared by RESS process or miniemulsion method have been reported to serve as an active layer in organic light-emitting diodes.61 For nanoparticles synthesized by both miniemulsion and RESS methods, surfactants, stabilizing agents or hydrophobes are necessary and can hardly be removed. Such additives will be disadvantageous to the native optoelectronic properties of OSNs in devices. It would be still interesting to fabricate optoelectronic devices from OSNs prepared via the reprecipitation method in which there would be no additives including surfactants, stabilizing agents and hydrophobes. Electrophoretic deposition of OSN films from reprecipitation-processed nanoparticle solutions has been employed in fabricating OLEDs.62 Although an electroluminescent emission from the device could be observed, the emission is not uniform because the nanoporosity of the OSN film prepared by electrophoretic deposition probably causes fatal pin-holes. As a result, an approach for preparing high-quality OSN films from reprecipitation-processed nanoparticle solutions is highly desired. Fortunately, the solventevaporation induced self-assembly method introduced above can meet this requirement. Currently, the main drawback of this method for fabricating OLEDs is that the solvent evaporation period is time-consuming. If there are some ways are found to overcome this drawback, this method is very promising for fabricating OSN based OLEDs.

### **5.2 Organic field-effect transistors**

Organic field-effect transistors (OFETs) fabricated using solution-deposition techqiques are particularly well-suited for large-area electronic devices. For meaningful practical applications, the organic semiconductors need to provide FET mobilities close to that of amorphous silicon. This will necessitate establishment of proper molecular order in the semiconductors to achieve high mobilities, since charge-carrier transport in organic semiconductors is dominated by hopping and disordered materials are not efficient chargetransporting media. In nanoparticles, molecules are closely packed and they are usually

Organic Semiconductor Nanoparticle Film: Preparation and Application 573

templates for the fabrication of conjugated polymer inverse photonic crystals, where the interstitial voids of the sphere template have been filled with conjugated polymer. This approach has been successfully used in the preparation of poly(p-phenylenevinylene) (PPV)

Although lots of applications of organic nanoparticles in chemo-/biosensors have been explored in recent year, most of them are carried out in solutions. Compared with solutions, solid-state samples can be more convenient for storage and transport which are highly desired for off-site laboratory analysis. Here we will introduce some applications of OSN

Hydroxyl radical is one of the most important reactive oxygen species, which is recognized to play an important role in physiological and pathological processes of the organisms. In addition, hydroxyl radical is also involved in many chemical, environmental, and pharmaceutical processes such as semiconductor photocatalysis in aqueous solution, wastewater treatment, and tumor cell killing. By using a binary nanoparticle system combining PFO nanoparticles and MEH-PPV nanoparticles, a linear relationship between the concentration of hydroxyl radical and the intensity ratio (Band I to Band III) of PFO nanoparticles can be found in the deposited nanoparticle film.67 The synergy between MEH-PPV NPs and PFO NPs are crucial to the response of free radicals in this kind of binary NP system. When exposed to free radicals, MEH-PPV NPs undergo molecular structure changes in the outer shell. As a result, a broad-sense polarity vector across the whole NP pointing from the weak-polarity core to the strong-polarity shell is established. Such a polarity vector will influence on the vibronic coupling among different electronic states of PFO molecules when the core-shell MEH-PPV NPs are adjacent to PFO NPs, which will change the relative

In general, conducting polymer nanoparticles are dispersed on the surface of the electrode to increase the area/volume ratio and to favor the adsorption of bio-molecules. By this means, uniform electrostatic adsorption of protein was enabled, thereby exhibiting higher signal-to-background ratios and shorter response times than electrochemically prepared films.68 Taking advantage of conducting polymer nanoparticles, sufficient amounts of enzyme were firmly immobilized during the fabrication of a phosphate biosensor. The response time of the biosensors was about 6 s. A linear response was observed between 1.0 M and 100 M and the detection limit was determined to be about 0.3 M.69 Besides, an ascorbic acid sensor has been fabricated via the drop-casting of PANI nanoparticles onto a screen-printed carbon-paste electrode.70 The PANI nanoparticles not only enhanced the catalytic reaction, but also allowed the detection of ascorbate at the reduced applied potential of 0 V and operation at neutral pH, avoiding the problem of

inverse photonic crystal films.66

film in chemical and biosensors.

**6.1 Chemical sensors** 

**6.2 Biosensors** 

sample interference.

**6. Applications of OSN film in chemo-/biosensors** 

PL emission intensity between bands I and III of PFO.

highly ordered. For example, both poy(3-hexylthiophene) (P3HT) and poly(9,9' dioctylfluorene) (PFO) nanoparticles can exhibit highly ordered structures and can be distinguished from the UV absorption spectrum with occurrence of a new peak.31,63 Poly(3,3'''-dialkylquarterthiophene)s (PQTs) nanoparticles have been explored for using in OFETs.64 As expected, the presence of lamellar stacking order in the nanoparticles can be verified by XRD and UV spectrum data. OFETs based on PQT nanoparticles show a 50 % improvement in mobility on bare SiO2 dielectric layer and an order of magnitude improvement in mobility on surface modified SiO2 dielectric layer relative to those based on normal films.

## **5.3 Organic solar cells**

It is well known that excitons formed in the active layer of organic solar cells usually have a migration distance less than 20 nm.65 So in organic solar cells, the distance for excitons diffused to the interface of electron donors and acceptors should be smaller than 20 nm to ensure good light conversion efficiency. However, because the entropy of mixing is generally low for polymers, solid polymer blends tend to phase-separate at the macroscopic scale. Moreover, when a thin layer of immiscible polymers is deposited from solution, the resulting morphology strongly depends on various parameters, such as the individual solubility of the polymers in the solvent used, the interaction with the substrate surface, the layer thickness and the method of deposition, drying and annealing. Therefore, controlling of the lengths of phase separation in thin layers is important for organic solar cells to avoid large-scale phase separation. Kietzke et al. have reported that by using the blend of poly(9,9 dioctylfluorene-co-benzothiadiazole) (F8BT) and poly(9,9-dioctylfluorene-co-N,N-bis(4 butylphenyl)-N,Ndiphenyl-1,4-phenylenediamine) (PFB) nanoparticles as the active layer the phase separation in organic solar cells can be controlled on the nanoscale.29,56

## **5.4 Photonic crystals**

If a photonic crystal is constructed from a material with sufficiently high refractive index, it can exhibit a photonic bandgap, a frequency range in which the mode density is zero and photons cannot propagate in any direction. Although this property is desirable since it would allow the inhibition of spontaneous emission and the ability to manipulate the flow of light, it is difficult to be achieved with organic semiconductors due to their relatively low refractive index. Instead, an organic photonic crystal would more likely have a partial bandgap, a frequency range where light can propagate in a limited number of directions. However, even in this case, the mode density for forbidden directions can be strongly modified by the photonic crystal. For frequencies just outside the partial bandgap, the mode density along these directions can be higher than in free space. This increase indicates that more optical modes are available to interact with electronic excitations. Thus, by combining organic semiconductors with photonic crystals, this enhanced interaction with light can be used to further improve optoelectronic properties.

One of the simplest ways of preparing photonic crystals is by the self assembly of monodisperse spheres, for instance, by the self-assembly of colloidal silica or polystyrene microspheres widely reported in the literatures. These spheres can then act as secondary templates for the fabrication of conjugated polymer inverse photonic crystals, where the interstitial voids of the sphere template have been filled with conjugated polymer. This approach has been successfully used in the preparation of poly(p-phenylenevinylene) (PPV) inverse photonic crystal films.66

## **6. Applications of OSN film in chemo-/biosensors**

Although lots of applications of organic nanoparticles in chemo-/biosensors have been explored in recent year, most of them are carried out in solutions. Compared with solutions, solid-state samples can be more convenient for storage and transport which are highly desired for off-site laboratory analysis. Here we will introduce some applications of OSN film in chemical and biosensors.

## **6.1 Chemical sensors**

572 Smart Nanoparticles Technology

highly ordered. For example, both poy(3-hexylthiophene) (P3HT) and poly(9,9' dioctylfluorene) (PFO) nanoparticles can exhibit highly ordered structures and can be distinguished from the UV absorption spectrum with occurrence of a new peak.31,63 Poly(3,3'''-dialkylquarterthiophene)s (PQTs) nanoparticles have been explored for using in OFETs.64 As expected, the presence of lamellar stacking order in the nanoparticles can be verified by XRD and UV spectrum data. OFETs based on PQT nanoparticles show a 50 % improvement in mobility on bare SiO2 dielectric layer and an order of magnitude improvement in mobility on surface modified SiO2 dielectric layer relative to those based on

It is well known that excitons formed in the active layer of organic solar cells usually have a migration distance less than 20 nm.65 So in organic solar cells, the distance for excitons diffused to the interface of electron donors and acceptors should be smaller than 20 nm to ensure good light conversion efficiency. However, because the entropy of mixing is generally low for polymers, solid polymer blends tend to phase-separate at the macroscopic scale. Moreover, when a thin layer of immiscible polymers is deposited from solution, the resulting morphology strongly depends on various parameters, such as the individual solubility of the polymers in the solvent used, the interaction with the substrate surface, the layer thickness and the method of deposition, drying and annealing. Therefore, controlling of the lengths of phase separation in thin layers is important for organic solar cells to avoid large-scale phase separation. Kietzke et al. have reported that by using the blend of poly(9,9 dioctylfluorene-co-benzothiadiazole) (F8BT) and poly(9,9-dioctylfluorene-co-N,N-bis(4 butylphenyl)-N,Ndiphenyl-1,4-phenylenediamine) (PFB) nanoparticles as the active layer

the phase separation in organic solar cells can be controlled on the nanoscale.29,56

If a photonic crystal is constructed from a material with sufficiently high refractive index, it can exhibit a photonic bandgap, a frequency range in which the mode density is zero and photons cannot propagate in any direction. Although this property is desirable since it would allow the inhibition of spontaneous emission and the ability to manipulate the flow of light, it is difficult to be achieved with organic semiconductors due to their relatively low refractive index. Instead, an organic photonic crystal would more likely have a partial bandgap, a frequency range where light can propagate in a limited number of directions. However, even in this case, the mode density for forbidden directions can be strongly modified by the photonic crystal. For frequencies just outside the partial bandgap, the mode density along these directions can be higher than in free space. This increase indicates that more optical modes are available to interact with electronic excitations. Thus, by combining organic semiconductors with photonic crystals, this enhanced interaction with light can be

One of the simplest ways of preparing photonic crystals is by the self assembly of monodisperse spheres, for instance, by the self-assembly of colloidal silica or polystyrene microspheres widely reported in the literatures. These spheres can then act as secondary

normal films.

**5.3 Organic solar cells** 

**5.4 Photonic crystals** 

used to further improve optoelectronic properties.

Hydroxyl radical is one of the most important reactive oxygen species, which is recognized to play an important role in physiological and pathological processes of the organisms. In addition, hydroxyl radical is also involved in many chemical, environmental, and pharmaceutical processes such as semiconductor photocatalysis in aqueous solution, wastewater treatment, and tumor cell killing. By using a binary nanoparticle system combining PFO nanoparticles and MEH-PPV nanoparticles, a linear relationship between the concentration of hydroxyl radical and the intensity ratio (Band I to Band III) of PFO nanoparticles can be found in the deposited nanoparticle film.67 The synergy between MEH-PPV NPs and PFO NPs are crucial to the response of free radicals in this kind of binary NP system. When exposed to free radicals, MEH-PPV NPs undergo molecular structure changes in the outer shell. As a result, a broad-sense polarity vector across the whole NP pointing from the weak-polarity core to the strong-polarity shell is established. Such a polarity vector will influence on the vibronic coupling among different electronic states of PFO molecules when the core-shell MEH-PPV NPs are adjacent to PFO NPs, which will change the relative PL emission intensity between bands I and III of PFO.

## **6.2 Biosensors**

In general, conducting polymer nanoparticles are dispersed on the surface of the electrode to increase the area/volume ratio and to favor the adsorption of bio-molecules. By this means, uniform electrostatic adsorption of protein was enabled, thereby exhibiting higher signal-to-background ratios and shorter response times than electrochemically prepared films.68 Taking advantage of conducting polymer nanoparticles, sufficient amounts of enzyme were firmly immobilized during the fabrication of a phosphate biosensor. The response time of the biosensors was about 6 s. A linear response was observed between 1.0 M and 100 M and the detection limit was determined to be about 0.3 M.69 Besides, an ascorbic acid sensor has been fabricated via the drop-casting of PANI nanoparticles onto a screen-printed carbon-paste electrode.70 The PANI nanoparticles not only enhanced the catalytic reaction, but also allowed the detection of ascorbate at the reduced applied potential of 0 V and operation at neutral pH, avoiding the problem of sample interference.

Organic Semiconductor Nanoparticle Film: Preparation and Application 575

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## **7. Conclusions and prospects**

Most of the organic semiconductors including both small molecules and conjugated polymers can be utilized for preparing OSNs, thus ensuring a very wide material selectivity for their applications. Various approaches have been reported for synthesizing OSNs. Besides reprecipitation method, additives such as surfactants are usually employed in other methods, which may be disadvantageous to the optical and electronic properties of OSNs. When depositing the OSN solution onto the substrate to form nanoparticle films, auxiliary underlayer and binders such as polymer matrix or surfactants are often used to improve the film quality. An exception is the vapor-driven self-assembly and solvent-evaporation induced self-assembly methods, which can prepare clean nanoparticle films and is highly desired for the optical and electronic applications.

Although OSNs have been proved to be effective building blocks in both optoelectronic devices and chemo/biosensors, a number of challenges and avenues of exploration remain. The interface between nanoparticles and the surroundings is crucial to its optical, electrical, and catalytic properties. So surface modification of OSNs can not only improve their contact properties but also endow them with a new function. However, the surface modification of OSNs is seldom reported yet.

The field of photonic crystals has recently provided a number of novel insights into the manipulation of light. These photonic properties have yet to be fully combined with the optoelectronic properties of OSNs, and the development of this area remains a very active area of research. Additionally, the ability to precisely control the morphology and alignment of OSNs is of importance to all fields of organic electronics.

In the field of electronic devices, OSN based OLEDs have been widely explored. However, OSN based OFETs still need to be paid more attention. By appropriate design, OFETs using OSNs as an active layer may be served as multifunctional optoelectronic devices.

With the great advantages of OSNs, they are believed to play an important role in more and more application fields and will provide new scientific insights in the coming years.

## **8. References**


Most of the organic semiconductors including both small molecules and conjugated polymers can be utilized for preparing OSNs, thus ensuring a very wide material selectivity for their applications. Various approaches have been reported for synthesizing OSNs. Besides reprecipitation method, additives such as surfactants are usually employed in other methods, which may be disadvantageous to the optical and electronic properties of OSNs. When depositing the OSN solution onto the substrate to form nanoparticle films, auxiliary underlayer and binders such as polymer matrix or surfactants are often used to improve the film quality. An exception is the vapor-driven self-assembly and solvent-evaporation induced self-assembly methods, which can prepare clean nanoparticle films and is highly

Although OSNs have been proved to be effective building blocks in both optoelectronic devices and chemo/biosensors, a number of challenges and avenues of exploration remain. The interface between nanoparticles and the surroundings is crucial to its optical, electrical, and catalytic properties. So surface modification of OSNs can not only improve their contact properties but also endow them with a new function. However, the surface modification of

The field of photonic crystals has recently provided a number of novel insights into the manipulation of light. These photonic properties have yet to be fully combined with the optoelectronic properties of OSNs, and the development of this area remains a very active area of research. Additionally, the ability to precisely control the morphology and alignment

In the field of electronic devices, OSN based OLEDs have been widely explored. However, OSN based OFETs still need to be paid more attention. By appropriate design, OFETs using

With the great advantages of OSNs, they are believed to play an important role in more and

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**7. Conclusions and prospects** 

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**8. References** 

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## *Edited by Abbass Hashim*

In the last few years, Nanoparticles and their applications dramatically diverted science in the direction of brand new philosophy. The properties of many conventional materials changed when formed from nanoparticles. Nanoparticles have a greater surface area per weight than larger particles which causes them to be more reactive and effective than other molecules. In this book, we (InTech publisher, editor and authors) have invested a lot of effort to include 25 most advanced technology chapters. The book is organised into three well-heeled parts. We would like to invite all Nanotechnology scientists to read and share the knowledge and contents of this book.

Photo by Evgeny Sergeev / iStock

Smart Nanoparticles Technology

Smart Nanoparticles

Technology

*Edited by Abbass Hashim*