Potential Application of Nanoporous Materials in Biomedical Field

*Saraswati Prasad Mishra, Shweta Dutta, Anil Kumar Sahu, Koushlesh Mishra and Pankaj Kashyap*

#### **Abstract**

Nanoporous materials are the substances having pores of size 100 nanometers in a frame work organic or inorganic substance. These substances are used in medical devices such as bioartificial organ and biosensing. Nanoporous material has also importance in the field of diagnostics. This chapter basically explains about the nanoporous material in detail along with its types. The methods of fabrication of these nanoporous material area also explained. The chapter also deals with the characterization of the materials. Moreover present application of nanoporous material such as in the field of biomedicals along with the future prospects is explained in the present chapter.

**Keywords:** nanoporous material, biosensing, organic, inorganic, medical device

#### **1. Introduction**

Nanoporous material is a structure containing framework of organic or inorganic substances having pores of size 100 nanometers. The pores found in nanoporous material contain either gas or liquid filled in it. A Nanoporous material is used recently in novel medical devices, implants or making bioartificial organs and biosensing. Advancement in the field of nanofabrication made it possible to produce nanoporous material with desired size of pores, distribution of pores in the nanoporous material as well as their porosity and chemical nature. Eventually it made the nanoporous material more attractive to carry out process of regulation and transportation at the molecular level. Basically nanoporous material is used for size sorting; antibiofouling behavior along with it is used in medical devices as mentioned above. In near future it is possible that nanoporous material can be functionalized with smart polymers that can initiate or modulate transportation at bio-molecular level in response to different kind of stimuli such as ion, change in pH or temperature [1]. This can eventually help in development of such medical device that can act in accordance to the changing physiological needs. The body cells naturally have proteins of nano-size that helps in regulating movement of biomolecules across the membranes. In similar way nanoporous material functionalized with smart polymer will differentiate between the biomolecules that has to be transported from the biomolecules that are not to be transported. As nanoporous material have small pore size but contains a larger surface porosity it becomes ideal

to be used in activities like ion exchange, catalysis, sensing [2–4]. Nanoporous material has an important role to play diagnostic field as it is used in combinatorial biochemistry on-a-chip, in analysis of DNA, in activity like cell manipulation and chromatography as well [5, 6]. Moreover it can also be used in boosting devices that are used to store energy as nanoporous material shows a greater conductivity to electrolytes. The present chapter explains about the nanoporous materials, their relevance in present day as well as their future prospects and their classification. The chapter also elaborates about the fabrication methods, nanopores techniques along with the characterization of nanoporous material and their applications [7–10].

#### **2. Types of nanoporous materials**

Nanoporous material are generally grouped into two class i.e. bulk material and membranes. Under bulk material activated carbon and zeolites are the examples whereas when membranes are concerned then cell membrane is an example of nanoporous membrane. Nanoporous materials are made using a chemical reagent that is basically inorganic and a structure is provided by using the organic templates. It can be said that nanoporous material is made by polymerization of inorganic monomers that are assiated by the templates of organic molecules. Many nanoporous material are also made by using minerals instead of chemicals reagent as inorganic source. In case of mineral nanoporous material templating is based on the initial structure of the mineral itself [11, 12].

#### **2.1 Classifications**

Nanoporous materials can be of different types as discussed above. Below are classification of nanoporous material based on pore size and the network material used.

#### *2.1.1 Classication by pore size*

The pores of nanoporous material vary from 1 nm to 1000 nm. In accordance to IUPAC there are following class of nanoporous material [11–13].


Comparison between these three pore systems is given in **Figure 1**. There is no order found between above mentioned pore materials, mostly they are random in nature (**Table 1**) [14–17].

#### *2.1.2 Classication based on network material*

In the field of nanoporous material one of the most important thing is to have network material of desired chemical composition. These network materials can be classed into two categories

*Potential Application of Nanoporous Materials in Biomedical Field DOI: http://dx.doi.org/10.5772/intechopen.95928*


One of the most important goals in the field of nanoporous materials is to achieve any possible chemical composition in the network materials "hosting" the pores. It makes sense to divide the materials into two categories:


As organic material act as template for the inorganic material to form the structure so it is the smaller group used nanoporous material. Different kinds of polymers are used under this category [18, 19].

	- Inorganic oxide type materials such as porous silica or porous titania or porpous material of zirconia is used.
	- Nanoporous carbon materials are also used where active carbons are used. Mesoporous carbon materials are example under these groups.
	- Sulphide and nitrites are also used under inorganic material. An AlPO4 material also comes under this.

#### **3. Fabrication methods**

The area of fabrication in materials of nanostructure is ever improving area with involvement of innovative techniques that helpful to different field of research and

**Figure 1.** *Biomedical applications of nanoporous materials.*


*That table contains various properties of nanoporous.*

#### *Nanopores*

*Potential Application of Nanoporous Materials in Biomedical Field DOI: http://dx.doi.org/10.5772/intechopen.95928*

development [21]. Improvement seen in the field of nanofabrication and the growing interest in the domain of nano-manufacturing can help in the enhancement in methods of ultrafiltration [22]. Ideal properties of a protein sieve or a molecular membrane is that it contains uniformly distributed pores on an ultrathin membrane and that is fabricated in such a way that can be used in scalable and robust manner. It should be cleanable and reusable after sterilization. In this fabrication method, nanoporous membrane are made with ratio of pore size to thickness is around one. The said ratio between pore size to thickness helps in effective mass transportation due to enhanced selectivity and permeability. Fabrication of membrane is done at very lost cost so that it is scalable enough to have manufacturing at large scale. The defects that are seen during fabrication of membrane are pore size variation and absence of pores in membrane. As far as ultrafiltration is concerned absence of pore size is not that important and optimization of variation in pore size can be performed to have better functioning of membrane and optimum efficiency.

#### **3.1 Nanopore techniques**

Nanopores are nothing but pores having size in nanometer. They can be made either by using proteins that can form pores or by creating pores of nanosize in molecules. When nanopores are coated with iron and are present in a membrane which is electrically insulating act as single molecule identifier. Additionally it also acts as network of biological protein in bilayer of phospholipid. Nanopore technology is used as a detector for detecting the biological and chemical agent in nanoscale at molecular level. By the use of principle of electrophoresis a device based on nanopores pulls the molecules through nanopores into the solution and detect the molecule and ascertain their competence at analytically. Characterization of nucleic acid polymer is done in narrow and confined space in the nanopores. Nanopore sequencing technique has made DNA sequencing inexpensive and fast as characterization of single stranded DNA and RNA without labelling and amplification of it [23]. As nanopores are highly sensitive that lead to many research that helps in analyzing nucleic acid [24, 25].

#### **3.2 Biological nanopores**

Proteins are also capable of forming nanopores [26]. This kind of protein are typically have a structure like mushroom and the core of the mushroom shaped structure has hollow in it. Examples of some proteins capable of pores are α hemolysin, Phi 29 connector and MspA porin. The most initial biological nanopore is α hemolysin (α -HL) which is used in the area DNA sequencing. α-HL is produced from bacterium *Staphylococcus aureus* as an exotoxin. The specification of mushroom shaped protein is 232.4 kDa of transmembrane channel with a cap of diameter around 3.6 nm and barrel of 2.6 diameter barrel [27]. Then it is inserted in lipid bilayer and then manipulation is done [28].

#### **3.3 Solid-state nanopores**

These kinds of nanopores are made from silicon film, mostly silicon nitride. Various techniques are employed for solid state nanopores manufacturing which involves "fabrication by electron beam" and "Deploying and sculpting with ion beam" [29]. Solid nanopores have diameter ranging from sub nanometers to nanometers in hundreds and the change in diameter is based on the requirement of experimental parameter. SiN used in manufacturing of solid state nanopores shows better chemical and thermal stability as compared to lipid membrane [30]. Nanopores made of graphene expressed chemical properties that are unique and shows btter gains over the biological complements [31]. Solid state nanopores created many paths for research especially in DNA sequencing. Identifications of protein interaction nanofluidic device assembly. Solid state nanopores are suitable substitute for biological nanopores due to the unique chemical properties. Various measurement technique such as electronic and optical measurement are compatible with solid state nanopores. Reecent nanopores fabrication techniques are membrane technology for ion tracking [32, 33]. Production of metallic surfaced oxidative film ionic beam sculpting.

#### **3.4 Anodic oxidation method on the metal aluminum**

When electrochemistry and electrophysiology of anodic oxidation of metals was observed it resulted in fabrication of nanoporous oxides of metals that are self-ordering. Metals included are anodized form of aluminum oxide, nanotubular titania oxide and silicon [34]. The reasons due to which the anodic alumina oxide stands out are its hardness, high surface area and stability it shows chemically and thermally [35]. Selective metals such as Al, Nb, Ti, are studied for ordering behavior during the process of anodic oxidation. These metals are known as valve element [36]. Factors responsible for enhancement of the process are electrolyte type, its pH as well as concentration, temperature, surface and the voltage and current applied [37, 38].

#### **3.5 Ion track-etching technology**

This technology is used for generation of pore in materials that are insulating in nature. Several polymers are used to produce filtration films. The underlying principle is that when a material comes in the path of straight ion, due to penetration by high energy heavy ion a pore is seen in the material. By the help of appropriate reagent etching is done to enlarge the pores. Pore size can be made of dimension of nanometers to micrometers and cylindrical pores as well [39, 40].

To have a uniform etching surfactant are added during the process of ion track etching [41].

While using surfactants following few things are to be taken into consideration.


#### **3.6 Ion-beam sculpting**

Ion beam sculpting has been matter of interest for the researchers for the meeting the challenges of nanopores. As it has low rate of shattering of ions, it gives better firmness and patterning of substrate which makes it crucial in meeting nanopore challenges High resolution of focused ion beam offers nanometer based sculpting [43].

#### **3.7 Ion current rectification**

Specific kind of transportation effect has been seen in nanocapillaries or nanopores having uneven shape and the reason being the nanosize of the opening. It is seen that there is rectification of ion current in this kind of nanopores whereas pH of electrolyte and the concentration remains the same. For the purpose of observation of rectification current voltage curves are used [44, 45]. Ion current rectification is behavior seen in many nanoporous system. A biological nanopore as well as artificial nanopores shows rectifying behavior [46, 47].

#### **3.8 Electron-beam fabrication**

Fabrication of solid state nanopore with small diameter is difficult. It is almost impossible to fabricate the nanopores which are less than 30 nm in terms of shape and size. By use of FIB nanopres can be etched but due to low etch rate limitation on film thicknesss can be seen [48–50]. Nanopores can be significantly condensed to almost 10 nanometer from 50 to 100 nanometrs by use of ion beam or electron beam having high energy. Solid state nanopores are very effective in detection of single molecule when pore diameter is as equal as molecule diameter [51, 52].

### **4. Characterization**

#### **4.1 FTIR spectroscopy**

Fourier transform infrared spectroscopy (FTIR) is a type of spectroscopy that concerned with the infrared portion of the electromagnetic spectrum that helps in identifying a compound by investigating the composition of a sample. Specific frequencies of Infra-red (IR) radiation is absorbed by molecule based the functional group present in it [53].

#### **4.2 Raman spectroscopy**

It is a type of vibrational spectroscopy at molecular level which originated as inelastic light scattering process. In this spectroscopy sample molecules scatters a laser photon and there will be gain or loss of energy. Energy lost is indicator of change in energy or wavelength of the laser photon. Energy lost is characteristic to a specific bond in molecule. With Raman spectroscopy an exact spectral fingerprint can be obtained specific to molecule or any molecular structure [54].

#### **4.3 UV-Vis spectroscopy**

UV–Vis spectroscopy is different from earlier two as it is concerned with electronic transition occurring within a molecule. When a continuous striking of radiation is done on a molecule then some portion of the radiation get absorbed and the remaining radiation is passed across a prism it gives spectrum that has gap in between. This spectrum is called as absorption spectrum and due to absorption of energy there is transition of molecule from low energy to higher energy state [55].

#### **4.4 Energy-dispersive X-ray spectroscopy (EDX)**

These spectroscopies are used for analysis of element and determine the characteristics of chemical aspect of sample. X-ray is a form of energy released when sample is being bombared with high energy beam that leads to ejection of excited electron from inner shelf creating a hole and the hole formed is filled by electron from a high energy outer cell and during this energy. To measure the X-ray in terms of number and energy the instrument used is energy-dispersive spectrometer. X-ray helps in determining composition of element in a specimen [56].

#### **4.5 X-ray diffraction (XRD)**

X-ray Diffraction (XRD) is a technique which studies the diffraction produced by X-ray through the lattice and determines the characteristics of lattice. It helps in determine structure of zeolite. The sample preparation for this technique is easy and the pace of the test is quick [57].

#### **4.6 Scanning electron microscope (SEM)**

Scanning electron microscope (SEM) is an instrument that is different from normal microscope as it makes image by using electrons rather than light. In SEM when scanning of sample is done by the beam of primary electron, the surface electrons get excited and that leads to release or emission secondary electron from the surface that results in formation of image. SEM is capable of producing images having high resolution that enablkes the observer to examine the close features with higher magnification. The images formed from SEM gives details about particle size and surface of sample [58].

#### **4.7 Transmission electron microscope**

In TEM utilizes the electron beam that has transmitted partially across a very thin specimen. This beam helps in getting the image. TEM helps in determining or acquiring information about structure and particle size of the sample under study. TEM is slightly better in magnitude than SEM [59].

#### **4.8 Nitrogen adsorption/desorption isotherms**

This technique is used for determination of characteristics of surface zeolite. It provides information related to the entire surface such as internal, external along with the diameters of mesopores [60].

#### **5. Biomedical applications of nanoporous materials**

Applications of nanoporous materials in biomedical field has been explored and discovered and there are many more under exploration still to be discovered. Nnaoporous membranes act as semipermeable membrane or compartment in many implantable devices that keep the drug or the implant and allow the passage of desired molecule. Moreover nanoporous material has application in variety of biomolecular application. It is also used in field of diagnosis and separation of protein [61].

#### **5.1 Separation and sorting of biomolecules**

Sorting or separation is essential to purify and isolate the molecules from the stream of biological feed. This application has a huge importance in the industry like pharmaceutical manufacturing, biotechnology and food industry. Currently techniques like gel electrophoresis or size exclusion chromatography are relevant and used in separation science [62, 63]. Examination of biomolecular separation in pores which are more ordered has been done recently. Synthetic nanoporous membrane has been used as support system for the cells of kidney as they filter blood and retain proteins present in serum and filter out the waste

materials [64]. The material that flow through the nanoporous material can be regulated externally [65].

#### **5.2 Biosensing**

Proteins pores that are membrane bound are used by sensory system as a detector of stimuli and facilitate the cells to respond accordingly. Biosensing has its application in fields like pharmaceutical industry, in the sector of medical diagnosis and it is also used for detecting of hazardous biomolecules. In these applications there is combination of physiochemical detection component with biological component for detection of analytes in stream of biological feed. Sensory systems use a variety of membrane-bound protein pores to detect molecules and facilitate cells to respond to stimuli. Such biosensing is also important in many technological areas including pharmaceutical industry, medical diagnosis, and detection of hazardous biomolecules. In a majority of these applications the biosensing device combines a biological component with a physiochemical detection component to detect analytes in biological feed streams [66].

#### **5.3 Single molecular analysis**

Nanoporous materials are also used probing of biomacromolecules such as DNA, RNA, and proteins one by one for single-molecule analysis. Information of biomacromolecules such as concentration, sequence, size or structure can be accessed by measurement of magnitude, frequency and blockage duration of ion current when the biomolecules are passed through the nanopore which is embedded in insulating membrane [67]. Earlier research in the field of single molecule analysis had utilized lipid membrane that had been incorporated in polymeric films like Teflon having aperture of microsize. The only drawback with micro-sized pores having polymeric support is rupture of lipid membrane after a small period of use and this technique has to be improved to have better durability. But nanoporous membrane shows better result in supporting protein pores in the process of single molecule analysis [68].

#### **5.4 Immunoisolation**

Immunoisolation means to protect implanted cells or the drug release systems from any kind of an immune reaction. It is done by encapsulating the implanted cell or drug in a nanoporous semipermeable membrane. This nanoporous material isolate the encapsulated drug or cell from the immune system of body. The pores allows entry of glucose, insulin and oxygen to pass through but it is impearmable to immunoglobulins. Only requirement for nanoporous material to use in immunoisolation is that it should be compatible foul resistant for *in vivo* functions [69].

#### **5.5 Drug delivery**

*In vivo* delivery systems are developed to supply of drugs in a controlled manner where it is needed. Controlled delivery system is used to deliver drugs in effective way so as to eliminate any kind of improper dosing. Nanoporous membranes having controlled pore size, desired membrane thickness and porosity can deliver controlled release drugs in capsule form [70]. By coupling it with biosensors a smart drug delivery systems can be developed that will respond according to the physiological conditions.

#### **5.6 Forensing analysis**

Nanoporous gold (NPG) being a good conductor and having suitable pore-size distribution with large surface area, and can enhance the electrochemical response to the enzymatic substrates namely NADH and H2O2 depending on their low coordinated Au atoms. All said advantages make it perfect for construction of dehydrogenase- and oxidase-based biosensors which will show improved sensitivity and anti-interference ability. DNA sensor which is based on an NPG electrode and is prepared by the process of dealloying Ag from Au/Ag alloy and multifunctional encoded AuNP. The active surface area of the NPG electrode is 9.2 times larger as compared to bare flat as characterized by CVs. Fabrication of DNA biosensor was done by immobilizing capture-probe DNA on the NPG electrode and hybridization with target DNA, which further hybridized with the reporter DNA loaded on the AuNP. The AuNP contained two kinds of bio bar-code DNA, one complementary to the target DNA, while the other was not, reducing the cross reaction between the targets and reporter DNA on the same AuNP. Besides DNA detection, NPG is also used in making an amperometric immunosensor [71–73].

#### **6. Application**

Nanoporous materials can enhance the performance devices used in biomedical field such as immunoisolation devices, devices used for dialysis, targeted drug delivery systems, bioanalytical devices, and biosensors. The main properties that nanoporous membranes should have so that it can be used in biomedical applications are having a pore size of a few tens of nanometers or below it and the pore size distribution should be in order that help us to achieve high biomolecule selectivity; high porosity as well as low thickness in order to enable high analyte flux; mechanical stability; and chemical stability [74]. The central issue of membrane is Pore geometry, biofouling resistance, and biocompatibility so that it can be used like interfaces in implantable devices. Porous material has become a potential drug delivery system for lots of biomedical application. They can be modified internally as well as externally to load the required molecule efficiently. Moreover outer layer can acts as a barrier and help in delaying the release of drug. Porous material has many advantages over the prominently used organic material for the drug delivery. They show better stability, better loading capacity, and provide better protection to the loaded material from degradation. Although porous material has potential to used but the obstacle is how it can be transferred to the clinic successfully [75].

#### **7. Future prospects**

Porous materials are the materials of future as they show many advantages over the prominent materials used in recent times. They provide versatile porosity and the pore size can be tailored according to the need. It also has better drug loading capacity. With all the said advanatges nanopores material can be in demand in future in many fields.

*Potential Application of Nanoporous Materials in Biomedical Field DOI: http://dx.doi.org/10.5772/intechopen.95928*

### **Author details**

Saraswati Prasad Mishra1 \*, Shweta Dutta2 , Anil Kumar Sahu<sup>2</sup> , Koushlesh Mishra3 and Pankaj Kashyap2

1 RITEE College of Pharmacy, Raipur, Chhattisgarh, India

2 Royal College of Pharmacy, Raipur, Chhattisgarh, India

3 Raigarh College of Pharmacy, Raigarh, Chhattisgarh, India

\*Address all correspondence to: saraswatim3@gmail.com

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### **References**

[1] Adiga SP, Curtiss LA, Elam JW, Pellin MJ, Shih CC, Shih CM, Lin SJ, Su YY, Gittard SD, Zhang J, Narayan RJ. Nanoporous materials for biomedical devices. Jom. 2008 Mar 1;60(3):26-32.

[2] J. Ly, M. Alexander, and S.E. Quaggin, Current Opin- ion in Nephrology and Hypertension, 13 (2004), pp. 299-305.

[3] D.A. LaVan, T. McGuire, and R. Langer, Nature Bio- technology, 21 (2003), pp. 1184-1191.

[4] *L. Leoni*, A. Boiarski, and T.A. Desai, Biomedical Mi- crodevices, 4 (2002), pp. 131-139.

[5] Z. Huang et al., Journal of Medical Devices, 1 (2007), pp. 79-83.

[6] F. Martin et al., Journal of Controlled Release, 102 (2005), pp. 123-133.

[7] M. E. Davis, "Ordered porous materials for emerging applications," Nature 417, 813-821 (2002).

[8] I. Moriguchi, M. Honda, T. Ohkubo, Y. Mawatari, and Y. Teraoka, "Adsorption and photocatalytic decomposition of methylene blue on mesoporous metallosilicates," Catal. Today 90, 297-303 (2004).

[9] H. Yamada, H. Nakamura, F. Nakahara, I. Moriguchi, and T. Kudo, "Electrochemical study of high electrochemical double layer capacitance of ordered porous carbons with both meso/macropores and micropores," J. Phys. Chem. C 111, 227- 233 (2007).

[10] L. L. Zhang and X. S. Zhao, "Carbon-based materials as supercapacitor electrodes," Chem. Soc. Rev. 38, 2520-2531 (2009).

[11] Polarz S, Smarsly B. Nanoporous materials. Journal of nanoscience

and nanotechnology. 2002 Dec 1;2(6):581-612.

[12] Ng EP, Mintova S. Nanoporous materials with enhanced hydrophilicity and high water sorption capacity. Microporous and Mesoporous Materials. 2008 Sep 1;114(1-3):1-26.

[13] J. Rouqerol, D. Avnir, C. W. Fairbridge, D. H. Everett, J. H. Haynes, N. Pernicone, J. D. Ramsay, K. S. W. Sing, and K. K. Unger, *Pure Appl. Chem.* 66, 1739 (1994).

[14] K. S. W. Sing, D. H. Everett, R. A. W. Haul, L. Moscou, R. A. Pierotti, J. Rouquérol, and T. Siemieniewska, *Pure Appl. Chem.* 57, 603 (1985).11 12:

[15] D. W. Schaefer and K. D. Keefer, *Phys. Rev. Lett.* 53, 1383 (1984).

[16] Á. Kukovecz, Z. Kónya, I. Pálinkó, D. Mönter, W. Reschetilowski, and I. Kiricsi, *Chem. Mater.* 13, 345 (2001).

[17] K. D. Keefer and D. W. Schaefer, *Phys. Rev. Lett.* 56, 2376 (1985).

[18] D. W. Schaefer, *Science* 243, 1023 (1989).

[19] N. Koshida and B. Gelloz, *Curr. Opin. Colloid Interface Sci.* 4, 309 (1999).

[20] K. L. Kavanagh and M. J. Sailor, *Science* 255, 66 (1992).30 31

[21] H. P. Hentze and M. Antonietti, *Curr. Opin. Solid State Mater. Sci.* 5, 343 (2001).

[22] Mireles M, Gaborski TR. Fabrication techniques enabling ultrathin nanostructured membranes for separations. Electrophoresis. 2017 Oct;38(19):2374-88.

[23] Montagne F, Blondiaux N, Bojko A, Pugin R. Molecular transport through

*Potential Application of Nanoporous Materials in Biomedical Field DOI: http://dx.doi.org/10.5772/intechopen.95928*

nanoporous siliconnitride membranes produced from self-assembling block copolymers. Nanoscale. 2012;4(19):5880-6.

[24] Rhee M & Burns MA (2006). Nanopore sequencing technology: research trends and applications. *Trends Biotechnol* 24(12): 580-586.

[25] Healy K, Schiedt B & Morrison AP (2007). Solid-state nanopore technologies for nanopore-based DNA analysis. *Nanomedicine (Lond)* 2(6): 875-897.

[26] Tobkes N, Wallace BA & Bayley H (1985). Secondary structure and assembly mechanism of an oligomeric channel protein. *Biochemistry* 24(8): 1915-1920.

[27] Storm AJ, Chen JH, Ling XS, Zandbergen HW & Dekker C (2003). Fabrication of solid-state nanopores with single-nanometre precision. *Nat Mater* 2(8): 537-540

[28] Song LZ, Hobaugh MR, Shustak C, Cheley S, Bayley H, Gouaux JE (1996). Structure of staphylococcal alpha-hemolysin, a heptameric transmembrane pore. *Science* 274: 1859-1866.

[29] Briggs K, Madejski G, Magill M, Kastritis K, de Haan HW, McGrath JL & Tabard- Cossa V (2018). DNA Translocations through Nanopores under Nanoscale Preconfinement. *Nano Lett* 18(2): 660-668.

[30] Bayley H (2009). Membraneprotein structure: Piercing insights. *Nature* 459(7247): 651-652.

[31] Thompson JF & Milos PM (2011). The properties and applications of singlemolecule DNA sequencing. *Genome Biol* 12(2): 217.

[32] Meyers S, Downing JR & Hiebert SW (1993). Identification of AML-1

and the (8;21) translocation protein (AML-1/ETO) as sequence-specific DNA-binding proteins: the runt homology domain is required for DNA binding and protein-protein interactions. *Mol Cell Biol* 13(10): 6336-6345.

[33] Abgrall P & Nguyen NT (2008). Nanofluidic devices and their applications. *Anal Chem* 80(7): 2326-2341.

[34] Anglin EJ, Cheng L, Freeman WR & Sailor MJ (2008). Porous silicon in drug delivery devices and materials. *Adv Drug Deliv Rev* 60(11): 1266-1277.

[35] Ghicov A & Schmuki P (2009). Selfordering electrochemistry: a review on growth and functionality of TiO2 nanotubes and other self-aligned MO(x) structures. *Chem Commun (Camb)* (20): 2791-2808.

[36] Chu YY, Wang WJ & Wang M (2010). Anodic oxidation process for the degradation of 2, 4-dichlorophenol in aqueous solution and the enhancement of biodegradability. *J Hazard Mater* 180(1-3): 247-252.

[37] Ren Y, Ma Z & Bruce PG (2012). Ordered mesoporous metal oxides: synthesis and applications. *Chem Soc Rev* 41(14): 4909-4927.

[38] Yilmaz S, Uslu B & Ozkan SA (2001). Anodic oxidation of etodolac and its square wave and differential pulse voltammetric determination in pharmaceuticals and human serum. *Talanta* 54(2): 351-360.

[39] Kumeria T, Santos A & Losic D (2014). Nanoporous anodic alumina platforms: engineered surface chemistry and structure for optical sensing applications. *Sensors (Basel)* 14(7): 11878-11918.

[40] Li F, Guijt RM & Breadmore MC (2016). Nanoporous Membranes for

Microfluidic Concentration Prior to Electrophoretic Separation of Proteins in Urine. *Anal Chem* 88(16): 8257-8263.

[41] Fleischer RL, Price RB & Walker RM (1969). Nuclear tracks in solids. *Sci Am* 220(6): 30-39.

[42] Yuan Z, Wang C, Yi X, Ni Z, Chen Y & Li T (2018). Solid-State Nanopore. Nanoscale *Res Lett* 13(1): 56.

[43] Giselbrecht S, Gottwald E, Truckenmueller R, Trautmann C, Welle A, Guber A, Weibezahn KF et al (2008). Microfabrication of chip-sized scaffolds for three-dimensional cell cultivation. *J Vis Exp* (15): e699.

[44] Ali M, Ramirez P, Duznovic I, Nasir S, Mafe S & Ensinger W (2017). Label-free histamine detection with nanofluidic diodes through metal ion displacement mechanism. *Colloids Surf B Biointerfaces* 150: 201-208

[45] Oda K, Csige I, Henke RP & Benton EV (1992). A new method for internal calibration of nuclear track detectors. *Int J Rad Appl Instrum D* 20(3): 505-510.

[46] Ali M, Ramirez P, Nasir S, Nguyen QH, Ensinger W & Mafe S (2014). Current rectification by nanoparticle blocking in single cylindrical nanopores. *Nanoscale* 6(18): 10740-10745.

[47] Tong X, Aoyama H, Tsukihara T & Bai D (2014). Charge at the 46th residue of connexin 50 is crucial for the gap-junctional unitary conductance and transjunctional voltage-dependent gating. *J Physiol* 592(23): 5187-5202.

[48] Dondapati SK, Kreir M, Quast RB, Wustenhagen DA, Bruggemann A, Fertig N & Kubick S (2014). Membrane assembly of the functional KcsA potassium channel in a vesicle-based eukaryotic cell-free translation system. *Biosens Bioelectron* 59: 174-183.

[49] Yamamoto T & Doi M (2014). Electrochemical mechanism of ion current rectification of polyelectrolyte gel diodes. *Nat Commun* 5: 4162.

[50] Walz MM, Schirmer M, Vollnhals F, Lukasczyk T, Steinruck HP, Marbach, H (2010). Electrons as "invisible ink": fabrication of nanostructures by local electron beam induced activation of SiOx. *Angew Chem Int Ed Engl* 49(27): 4669-4673.

[51] Zhu C, Du D, Eychmuller A & Lin Y (2015). Engineering Ordered and Nonordered Porous Noble Metal Nanostructures: Synthesis, Assembly, and Their Applications in Electrochemistry. *Chem Rev* 115(16): 8896-8943.

[52] Fleischer R.L, Turner LG, Paretzke HG & Schraube H (1984). Personnel neutron dosimetry using particle tracks in solids: a comparison. *Health Phys* 47(4): 525-531.

[53] Noh JH, Nikiforov M, Kalinin SV, Vertegel AA & Rack PD (2010). Nanofabrication of insulated scanning probes for electromechanical imaging in liquid solutions. *Nanotechnol* 21(36): 365302.

[54] Sumikama T (2016). Origin of the Shape of Current-Voltage Curve through Nanopores: A Molecular Dynamics Study. *Sci Rep* 6: 25750.

[55] Cai L, Song AY, Wu P, Hsu PC, Peng Y, Chen J, Liu C, Catrysse PB, Liu Y, Yang A, Zhou C. Warming up human body by nanoporous metallized polyethylene textile. Nature communications. 2017 Sep 19;8(1): 1-8.

[56] Qi J, Motwani P, Gheewala M, Brennan C, Wolfe JC, Shih WC. Surfaceenhanced Raman spectroscopy with monolithic nanoporous gold disk substrates. Nanoscale. 2013;5(10):4105-9

*Potential Application of Nanoporous Materials in Biomedical Field DOI: http://dx.doi.org/10.5772/intechopen.95928*

[57] Cai J, Kimura S, Wada M, Kuga S. Nanoporous cellulose as metal nanoparticles support. Biomacromolecules. 2009 Jan 12;10(1):87-94.

[58] Indira K, Mudali UK, Rajendran N. Corrosion behavior of electrochemically assembled nanoporous titania for biomedical applications. Ceramics International. 2013 Mar 1;39(2):959-67.

[59] Zhao DD, Bao SJ, Zhou WJ, Li HL. Preparation of hexagonal nanoporous nickel hydroxide film and its application for electrochemical capacitor. Electrochemistry communications. 2007 May 1;9(5):869-74.

[60] Fujita T, Chen MW. Characteristic length scale of bicontinuous nanoporous structure by fast fourier transform. Japanese Journal of Applied Physics. 2008 Feb 15;47(2R):1161.

[61] Chen Y, Fitz Gerald J, Chadderton LT, Chaffron L. Nanoporous carbon produced by ball milling. Applied physics letters. 1999 May 10;74(19):2782-4.

[62] Ravikovitch PI, Neimark AV. Characterization of nanoporous materials from adsorption and desorption isotherms. Colloids and Surfaces A: Physicochemical and Engineering Aspects. 2001 Aug 31;187:11-21.

[63] Han J. In: Di Ventra M, Evoy S, Heflin JR eds. *Introduction to Nanoscale Science and Technology*. New York: Springer; 2004.36

[64] Ghosh R. *Protein Bioseparation Using Ultrafiltration: Theory, Applications andNew Developments*. London: Imperial College Press; 2002.

[65] Fissell WH,HumesaHD, Fleischmanb AJ, Roy S.Dialysis and nanotechnology: now, 10 years, or never? *Blood Purif* 2007, 25(1):12-17.38. [66] Nishizawa M, Menon VP, Martin CR. Metal nanotubule membranes with electrochemically switchable ion-transport selectivity. *Science* 1995, 268:700-702.39

[67] Li Q, Luo G, Feng J, Zhou Q, Zhang L, et al. Amperometric detection of glucose with glucose oxidase absorbed on porous nanocrystalline TiO2 film. *Electroanalysis* 2001, 13(5):413-416.40

[68] Joo S, Park S, Chung TD, Kim HC. Integration of a nanoporous platinum thin film into a microfluidic system for non-enzymatic electrochemical glucose sensing. *Anal Sci* 2007, 23:277-281.

[69] Bayley H, Cremer BS. Stochastic sensors inspired by biology. *Nature* 2001, 413:226-230.

[70] Tsujino I, Ako J, Honda Y, Fitzgera PJ. Drug delivery via nano-, micro and macroporous coronary stent surfaces. *Expert Opin Drug Deliv* 2007, 4(3):287-295.

[71] Desai TA, Sharma S, Walczak RJ, Boiarski A, CohenM, Shapiro J, West T, Melnik K, Cosentino C, Sinha PM, Ferrari M. Nanoporous implants for controlled drug delivery. In: Desai TA, Bhatia S eds. *BioMEMS and Biomedical Nanotechnology Volume III Therapeutic Micro/Nanotechnology*. New York: Springer, 2007

[72] Hu K, Lan D, Li X, Zhang S. Electrochemical DNA biosensor based on nanoporous gold electrode and multifunctional encoded DNA− Au bio bar codes. Analytical chemistry. 2008 Dec 1;80(23):9124-30.

[73] Poh HL, Pumera M. Nanoporous carbon materials for electrochemical sensing. Chemistry–An Asian Journal. 2012 Feb 6;7(2):412-6.

[74] Adiga SP, Curtiss LA, Elam JW, Pellin MJ, Shih CC, Shih CM, Lin SJ, Su YY, Gittard SD, Zhang J, Narayan RJ. Nanoporous materials for biomedical devices. Jom. 2008 Mar 1;60(3):26-32.

[75] Xu Q, editor. Nanoporous materials: synthesis and applications. CRC press; 2013 Jan 4.

#### **Chapter 3**

## Biosensors: Design, Development and Applications

*Phumlani Tetyana, Poslet Morgan Shumbula and Zikhona Njengele-Tetyana*

#### **Abstract**

The ability to detect even the slightest physiological change in the human body with high sensitivity and accurately monitor processes that impact human nature and their surroundings has led to an immense improvement in the quality of life. Biosensors continue to play a critical role across a myriad of fields including biomedical diagnosis, monitoring of treatment and disease progression, drug discovery, food control and environmental monitoring. These novel analytical tools are small devices that use a biological recognition system to investigate or detect molecules. This chapter covers the design and development of biosensors, beginning with a brief historical overview. The working principle and important characteristics or attributes of biosensors will also be addressed. Furthermore, the basic types of biosensors and the general applications of these biosensors in various fields will be discussed.

**Keywords:** bio-receptor, transducer, bio-sensing, analyze

#### **1. Introduction**

The importance of monitoring vital processes and parameters in various industries has led to the discovery of small analytical devices known as biosensors. The emergence of these devices has provided solutions to various applications including drug discovery, disease diagnosis, biomedicine, food safety and processing, environmental monitoring, defence, and security [1, 2] as depicted. Biosensors are analytical devices used to investigate the presence of an analyte of interest in a sample. By definition, these are self-sufficient integrated devices that provide qualitative and semi-quantitative analytical data through the use of a biological recognition element that is coupled to a transduction element. The sole purpose of these analytical devices is to rapidly provide accurate and reliable information about an analyte of interest in real time [3–6].

Generally, biosensors are composed of three main components as depicted in **Figure 1**. These include a biological sensing element, physicochemical detector or transducer and a signal processing system [8]. Biological sensing elements are used to interact with the analyte of interest to generate a signal. Sensing elements normally include materials such as tissues, microorganisms, organelles, cell receptors, enzymes, antibodies, and nucleic acids. The signal generated through the interaction of the sensing element and the analyte of interest is then transformed to a measurable and quantifiable electrical signal via the transducer. The signal

**Figure 1.**

*Basic scheme of a biosensor. Picture adapted from Korotkaya [7] with modifications.*

processing system therefore amplifies the electrical signal and conveys it to a data processor that produces a measurable signal in the form of a digital display, print out or color change [9, 10].

The concept of a biosensor is an ancient phenomenon. The first reported concept of a biosensor dates back to 1906 when Cremer [11] discovered that the concentration of an acid suspended in an aqueous solution is equivalent to the electric potential generated between sections of the solution when separated by a glass membrane. This led to the development of the concept of pH by Soren Peder Lauritz Sorensen in 1909, which was followed by the development of an electrode to measure this pH in 1922 by Hughes [12]. This paved way for the development of what is known as a "true biosensor" in 1959 by Leland C. Clark, Jr., who is affectionately known as the "father of biosensors". Clark developed a sensor for detecting glucose in biological samples, using a glucose oxidase electrode that detects the presence of either oxygen or hydrogen peroxide. Since then, great strides have been made in developing highly sensitive and selective biosensing devices [13, 14]. The emphasis of this chapter is on the design, development and applications of biosensors. Various components that constitute a biosensor as well as the working principle of biosensors will be presented. Moreover, various types of biosensors will be highlighted and various fields where these devices are used will also be discussed.

#### **2. Biosensor design**

A successful biosensor is composed of two main components, mainly a biological receptor or sensor element and a transducer. A signal processing unit that usually contains a display or printer is normally used in conjunction to a biosensor as depicted in **Figure 2**.

*Biosensors: Design, Development and Applications DOI: http://dx.doi.org/10.5772/intechopen.97576*

**Figure 2.**

*Biosensor design showing the various components necessary for generating a signal. Picture adapted from [6].*

#### **2.1 Biological receptor**

This component is also known as a sensor or detector element and is responsible for sensing or detecting the presence and/or the concentration of the target analyte or substance. This is a biological component, which serves as a biochemical receptor that specifically recognizes the target analyte [15]. When the biological receptor interacts with a target analyte, it generates a signal in the form of light, heat, pH, charge or mass change [11]. This material should be highly specific, stable under storage conditions and must be immobilized. Furthermore, the biological receptor should be capable of selectively detecting the target compound or analyte in the test sample. According to Paddle [16], the biological receptor determines the sensitivity of the entire device through the generation of the physicochemical signal that is monitored by the transducer [16, 17].

This component can be a tissue, microorganism, organelle, cell receptor, enzyme, antibody or nucleic acid etc. These can be grouped into two categories, namely catalytic and non-catalytic receptors [18]. The catalytic group of biological receptors are used in devices intended for continuous monitoring of substances at millimolar or micromollar concentrations. These include enzymes, tissues and microorganisms. The non-catalytic group is used mainly in biosensor devices that measure analytes such as steroids, drugs, and toxins etc. which usually occur at very low concentrations (micro to picomollar range). These are non-reusable devices which can only be used once and discarded thereafter. Such receptors include antibodies, antigens, nucleic acids etc. [17, 19, 20].

#### **2.2 Transducer**

A transducer forms the second main component in the design of a biosensor. Generally, a transducer is a material that is capable of converting one form of energy to another [11]. In a biosensor, a transducer is responsible for converting the biochemical signal received from the biological receptor, which is a result of the interaction between the target analyte and the biological receptor, into a measurable and quantifiable signal which can be piezo-electrical, optical, electrochemical etc. The transducer detects and measures the change that occurs during biological receptor – analyte interaction [21]. An example of a transducer is a pH sensor in a glucose biosensor. An enzyme, known as glucose oxidase, is used as a biological receptor which binds glucose and converts it to gluconic acid in the presence of oxygen. The pH sensor (transducer) then detects the change in pH (due to

production of gluconic acid) and converts it into a voltage change [22, 23]. The following features are recommended when a transducer is designed; specificity to the target analyte, analyte concentration range, response time and suitability for practical applications. Ideally, a transducer should be highly specific to the analyte, give measurement at the lowest analyte concentration within the shortest time possible [24].

#### **3. Working principle of a biosensor**

As indicated in the aforementioned sections, a biosensor comprises of a biological receptor coupled with a transducer and signal processing unit, and thus operate on the basis of signal transduction. The combination of these components is designed to convert the biological response into a corresponding electrical response and ultimately a measurable output. In simpler terms, biosensors are responsible for the quantitative analysis of a molecule by relating its biological action into a measurable signal [25]. Initially, the molecule of interest in the test sample binds or interacts specifically with the biological receptor, resulting in a physiological change. This further alters the physicochemical properties of the transducer that is in close proximity to the biological receptor. This further leads to a change in the optical or electronic properties of the transducer which is further converted into an electrical signal which is detectable [26].

The signal generated by the transducer can either be a current or voltage, depending on the type of biological receptor. If the output from the transducer is in the form of a current, then this will be converted into an equivalent voltage. Also, the output voltage is usually very low and masked by a high frequency noise signal, which then requires further alterations, processing and amplification through various filters within the signal processing unit. Finally, the output generated from the signal processing unit should be comparable to the biological quantity being measured [27].

#### **4. Important characteristics of biosensors**

Owing to the nature of the applications in which biosensors are used in, several characteristics or parameters have to be met when a biosensor is designed. These characteristics define the performance and usefulness of a biosensor.

#### **4.1 Sensitivity**

This is considered as the most important characteristic of a biosensor. The sensitivity of a biosensor is defined as the relationship between the change in analyte concentration and the intensity of the signal generated from the transducer. Ideally, a biosensor should generate a signal in response to small fluctuations in the concentration of the target analyte. Depending on the application, biosensors are required to detect analytes in the ng/ml or fg/ml concentration ranges. This is usually important for medical applications and environmental monitoring purposes [28, 29].

#### **4.2 Selectivity**

This refers to the ability of the biosensor to selectively bind and respond only to the desired analyte, in the presence of other molecules or substances. When a signal or response is generated from interactions with an analyte that is different from the target analyte such is termed a false positive result. This is common in biosensors with poor selectivity, thus failing in clinical applications. Selectivity is a very important feature especially in medical applications where the test sample or sample matrix, usually blood or urine, contains numerous molecules that are quite similar to the target analyte and compete for binding to the biological receptor [22, 30].

#### **4.3 Stability**

Stability of the biosensor is a very important characteristic especially for biosensors used for continuous monitoring. This feature determines the ability of the biosensor device to resist change in its performance over a period of time in response to interruptions arising from external factors. These can be in the form of temperature, humidity or other environmental conditions. Such interruptions have the potential to induce inaccuracies in the output signal during measurement, thereby affecting the precision and accuracy of the biosensor device [11]. This is because transducers and other electronic components that comprise the biosensor device are mostly temperature sensitive and this can greatly influence their stability. Also, temperature can affect the integrity of the biological receptor as this component tends to degrade with fluctuations in temperature [22].

#### **4.4 Detection limit**

A detection limit is defined as the lowest concentration of the target that is able to elicit a measurable signal or response. Ideally, a biosensor should have the lowest detection limit, especially if it is to be used in medical applications where the target analyte might be present at very low concentrations [22].

#### **4.5 Reproducibility**

This is also one of the most important features in biosensing, and refers to the ability of the biosensor device to produce matching output signals or results in duplicate experimental runs. The capability of the biosensor to meet this criteria relies on the transducer which is required to perform in a precise and accurate manner [11].

#### **4.6 Response time**

This property determines the time it takes for the biosensor to generate a signal or response following the interaction of the biological receptor with the target analyte [26, 27].

#### **4.7 Range or linearity**

Biosensor linearity determines the accuracy of the signal obtained, in response to a set of measurements with differing concentrations. This attribute gives insight into the resolution of the biosensor, defined as the minimal change in the target analyte concentration that will elicit a response from the biosensor. This is a very important attribute for a biosensor since most applications require a biosensor to measure a target analyte over wide concentration ranges [11, 22].

### **5. Considerations for biosensor design**

The first step in developing a biosensing device involves investigating the target analyte and understanding how this analyte interacts with certain biological molecules. Once this has been established, the following tasks are critical:


### **6. Classification of biosensors**

Biosensors are classified according to their biological receptors or transducer elements. **Figure 3** displays a flowchart illustrating the different types of biosensors based on the biological receptors and transducer elements [36]. Some of the biosensors shown in the figure will be discussed further in subsequent sections.

#### **Figure 3.**

*Flowchart showing the various types of biosensors classified based on their transducing elements and biological recognition elements [35].*

#### **6.1 Classification based on biological receptors**

#### *6.1.1 Enzyme based biosensors*

These type of biosensors form the most researched and reported biosensors based on biological receptors [37, 38]. Enzyme biosensors, useful tools for monitoring rapid changes in metabolite levels in real-time, include pure enzyme preparations or biological processes. They have been derived on immobilization processes such as van der Waals forces, ionic or covalent bonding. In 1967, Updike and Hicks [39] successfully developed a working electrode for the detection of glucose levels and this is considered the first biosensor in the world. The well-known enzymatic biosensors today are glucose and urea biosensors. However, glucose biosensors are most popular among researchers and are reportedly the mostly commercialized biosensors. The glucose biosensor, which was developed by Clark, is made up of glucose oxidase immobilized within a dialysis membrane which is integrated inside oxygen electrodes. Enzymatic biosensors are known for their prolonged use and reusability due to the fact that enzymes used as biological receptors cannot be consumed. Thus, the detection limit and the lifetime of enzyme based biosensors is greatly enhanced by the stability of the enzyme [40].

#### *6.1.2 DNA based biosensors*

Another group of biosensors based on a biological receptor is DNA biosensors. The most attractive feature of biosensors is the high selectivity of biosensors for their target analytes in a matrix of chemical or biological elements. DNA biosensors, which use nucleic acids as their biological receptors, detect proteins and non-macromolecular compounds that interact with certain DNA fragments known as DNA probes or DNA primers. The interaction observed stems from the formation of stable hydrogen bonds between the double helix nucleic acid strands [41]. To develop DNA biosensors, immobilization of the probe becomes the most crucial step. The strong pairing of lined up nucleotide strands between bases in their complementary parts influences biosensors based on DNA, RNA, and peptide nucleotide acids to be the most sensitive tool [42]. Lucarelli *et al.* reported that probes, which are short oligonucleotides capable of hybridization with individual areas of the target nucleotide sequence, together with various chemical composition and conformational arrangements, were employed in the development of DNA biosensors. Extremely high sensibility and selectivity is needed to maximize the hybridization efficiency and minimize non-specific binding [43].

#### **6.2 Biosensors based on transduction element**

The most commonly applied classification of biosensors is based on the type of transduction element used in the sensor. These biosensors are grouped into three main categories, known as electrochemical biosensors, mass-based biosensors and optical-based biosensors. The working principles of each of the three biosensors are different and can thus be implemented in a variety of applications. Below is a brief description of the different types of biosensors and their working mechanisms. Some of the subclasses under the types of biosensors will also be explained.

#### *6.2.1 Electrochemical biosensors*

Electrochemical biosensors, which are the best in the detection of hybridized DNA, DNA binding drugs, glucose concentration, etc., measure the electrical

potential difference caused by an interaction between an analyte and the membrane/sensor surface. There is proportionality between the electrical potential difference and the logarithm of the electrochemically active concentration of the material. The current flowing through the system or the potential difference between the electrodes as a result of the redox reactions involving the analyte are employed for its quantification in the sample. Electrochemical biosensors have gained popularity as compared to optical biosensors in the sense that they do not suffer from the many disadvantages optical biosensors experience. They have a more stable output, high sensitivity, fast response and are not prone to interferences. Electrochemical measurements are mostly preferred for sensing applications [44–47]. Electrochemical biosensors can further be classified into various types based on the measuring electrical parameters. These include conductimetric, amperometric, potentiometric and impedimetric sensors [48].

#### *6.2.1.1 Conductometric biosensors*

Conductometric biosensors measure the electrical conductivity of the solution in the course of a biochemical reaction. When electrochemical reactions produce ions or electrons, the overall conductivity or resistivity of the solution changes. Due to poor signal-to-noise ratio, they are less commonly used in biosensing applications, particularly when the biological receptor used is an enzyme. However, these biosensors remain useful in the detection of affine interactions [49, 50].

#### *6.2.1.2 Potentiometric biosensors*

Potentiometric biosensors measure changes in pH and ion concentrations resulting from antigen/antibody interactions. Although potentiometric biosensors are the least common of all biosensors, different strategies for the development of these biosensors are found. The working principle relies on the fact that when a voltage is applied to an electrode in solution, a current flow occurs because of electrochemical reactions. The voltage at which these reactions occur indicates a particular reaction and particular analyte. Some of the known potentiometric biosensors include those used for the detection of *Neisseria meningitides*, *Brucella melitensis* and *Francisella tularensis* species [51, 52]. Similarly, Hu *et al.* included a light-addressable potentiometric sensor in a microfluidic system to monitor the metabolism of human breast cancer cells in real time [53].

#### *6.2.1.3 Amperometric biosensors*

This is perhaps the most common electrochemical detection method used in biosensors. This high sensitivity biosensor can detect electroactive species present in biological test samples [54]. Amperometric-based biosensors detect the difference in current potentials during redox reactions when antigen/antibody pairing occurs. The most common amperometric biosensors use the Clark oxygen electrode. Amperometric biosensors have been developed for the indirect detection of *E. coli* by Nakamura and co-workers [55]. Another amperometric biosensor for the detection of Salmonella Species was developed by Brookes and colleagues [56].

#### *6.2.1.4 Impedimetric biosensors*

Impedimetric-based biosensors monitor changes in impedances upon antigen/ antibody interaction. Impedance, which usually employs a circuit bridge as a measurement tool, is well suited for detection of bacteria in clinical specimens,

to monitor quality and to detect specific food pathogens. Moreover, these biosensors are useful in controlling industrial microbial processes [57].

#### *6.2.2 Mass based biosensors*

Piezoelectric biosensors are a group of analytical devices working on a principle of affinity interaction recording. A piezoelectric platform or piezoelectric crystal is a sensor part working on the principle of change in oscillations due to mass bound on the piezoelectric crystal surface. Piezoelectric biosensors, which are considered as mass-based biosensors, produce an electrical signal when a mechanical force is applied. An example of piezoelectric biosensor is the quartz crystal microbalance (QCM) model. The working principle of QCM is depicted in **Figure 4**. Quartz crystal microbalance (QCM) is a very popular tool that is used extensively in the electronic industry. Currently, these tools are used as attenuators in electronic devices and they have a typically fundamental mode frequency of 1–20 MHz. Though higher frequencies provide good opportunities for a sensitive assay, QCM with high frequencies have been reported to exhibit several drawbacks such as their fragility and also the technologically demanding equipment needed for their manufacture [58]. The basic material used in the development of the QCM sensor consists of quartz crystal, which is equipped with metal electrodes. A sensitive coating material on the sensor surface is used to enable detection of the target analyte in the environment. An appropriate electronic circuit is necessary to make conversion of the measured quantity to an electrical signal [59].

#### *6.2.3 Optical biosensor*

Optical biosensors are based on the interaction of a sensing element with electromagnetic radiation. They consist of a light source, as well as numerous optical components to generate a light beam with specific characteristics and to beeline this light to a modulating agent, a modified sensing head along with a photodetector. An optical surface plasmon resonance (SPR) biosensor can detect the refractive index changes on the surface of sensor chips, label-free and in real-time. Although different optical methods such as absorption, fluorescence,

**Figure 4.** *Basic working principle of Quartz Crystal Microbalance (QCM) sensor [59].*

luminescence, internal reflection, surface plasmon resonance, or light scattering spectroscopy utilized herein are becoming popular, fluorescence and surface plasmon resonance enabled spectroscopies still remain the most and widely researched and applied methods [60, 61].

#### *6.2.3.1 Surface plasmon resonance based biosensors*

Over the last two decades, surface plasmon resonance (SPR) based biosensors have emerged as important and useful tools due to their unique features for real-time and label-free detection of biomolecular interactions [62, 63]. SPR technology has opened a new avenue for many important applications in the field of sensing due to their attractive sensing capabilities, light weight, compactness and easy implementation [64–67]. The SPR phenomenon has been widely used in biosensing, chemical sensing and environmental sensing applications such as protein–protein hybridization [68, 69], enzyme detection [70, 71] and protein-DNA hybridization. Surface plasmon resonance (SPR), as a physical phenomenon, is not restricted only to events occurring in thin planar metal films. A broad spectrum of differently nanostructured surfaces as well as noble metal nanoparticles are frequently employed for fabrication of SPR-based assays [72–75].

However, conventional commercial SPR-based biosensors and experimental devices are often represented by instruments, which utilize Kretschmann's scheme of plasmon excitation [65]. SPR-based biosensors can be employed to characterize interactions between biomolecules immobilized onto the metal film sensor surface and their counterparts in liquid sample in real time and without labelling. Indeed, these biosensors are actively used to measure binding constants, kinetics of biomolecular interactions and to perform concentration measurements [66]. In turn, these applications make SPR-based biosensors very useful in pharmacological, biomedical, environmental and food studies.

The first practical sensing application of SPR sensors for biomolecular detection was reported by Liedberg and Nylander in 1983 [67]. Since then, SPR biosensors have experienced rapid development in the last two decades and have become a valuable platform for qualitative and quantitative measurements of biomolecular interactions with the advantages of high sensitivity, versatile target molecule selection, and real-time detection. For this reason, SPR sensors are now widely adopted for meeting the needs of biology, food quality and safety analysis, and medical diagnostics.

Over the past decade, many SPR sensors have been reported in applications such as biomolecular interaction analysis, medical diagnostics, environmental monitoring, and food safety [69, 71, 73]. Traditional SPR devices generally require expensive equipment, complicated optics, and precise alignment of the components [74, 75], features that hinder the development of a portable device. Current portable SPR devices still require a portable computer to run the instrument and are about the size of a lunch box.

#### **7. Applications of biosensors**

Conventional 'off-site' analysis requires the samples to be sent to a laboratory for testing. These methods allow the highest accuracy of quantification and the lowest detection limits, but are expensive, time consuming and require the use of highly trained personnel. Due to the above drawbacks, there has been a great interest in the technology of biosensors. There has been a phenomenal growth in the field of biosensor development in recent years with emerging applications in a wide range

of disciplines. These include environmental monitoring, disease detection, food safety, defence, drug discovery and many more as depicted in **Figure 5** below. A summary of the few and selected representatives and examples of developed applications of biosensors is given below.

#### **7.1 Food industry**

Biosensors have been used extensively in the food industry for quality control and assurance purposes. These include applications in the agricultural field during crop production and also during food processing. Quality control remains a major part of food production and is responsible for the production of healthy food with a prolonged shelf life and also complies with regulations. Biosensors have been used as on-line or at-line quality sensors that make it possible for quality sorting, automation and reduction of production cost and production time. Also, biosensors have been developed to detect particular compounds in foods. These devices detect chemicals or biological agents that contaminate food or might indicate the presence of unwanted substances in food. Moreover, biosensors have been developed for monitoring and estimating cross-contamination of surfaces and food products [77–80].

#### **7.2 Environment**

Environmental pollution has an impact on human health and can therefore compromise the quality of life. Depending on the purpose, sensitive and selective methods are needed for both quantitative and qualitative determination of target analytes. Biosensors have found widespread use in environmental monitoring for the detection of chemical agents, organic pollutants, potentially toxic elements and pathogens that might pose a health hazard. Biosensors such as immunosensors, aptasensors, genosensors and enzymatic biosensors are amongst the most preferred

**Figure 5.** *Various applications where biosensors have been used. Picture adapted from [76].*

for environmental monitoring. These are known to use antibodies, aptamers, nucleic acids and enzymes as biological receptors. For example, a biosensor was developed to detect pesticides such as organophosphate and carbamate and also monitor their effects on the environment. Biosensors detect pollutants by measuring colour, light, fluorescence or electric current [81–84].

#### **7.3 Medical**

Most of the biosensors reported in the past years are found to be based on the phenomena of molecular interactions which are essentially employed in various forms at different scales. In the discipline of medical science, the applications of biosensors are growing rapidly. Some of the applications that have benefited from the emergence of biosensors include cancer detection and monitoring, cardiovascular disease monitoring, and diabetes control. Cancer diagnosis and treatment are of great interest due to the widespread occurrence of the diseases, high death rate, and recurrence after treatment. In medicine, biosensors can be used to monitor blood glucose levels in diabetics, detect pathogens, and diagnose and monitor cancer progression [85]. The use of emerging biosensor technology could be instrumental in early detection of cancer for effective treatment administration [86]. By measuring levels of certain proteins expressed and/or secreted by tumor cells, biosensors can detect presence of a tumor, whether benign or cancerous, and also give information of whether treatment is effective in reducing or eliminating such cancerous cells [87, 88].

Cardiovascular diseases, which are the primary cause of death are still considered as one of the biggest dilemma the world is facing with about one million people suffering from it. The ability to detect such diseases earlier may result in the reduction of mortality cases. Some of the sensing techniques that have been used herein include immunoaffinity column assay, fluorometric assays, and enzymelinked immunosorbent assay [89–91]. However, the above techniques are laborious, and therefore require well trained and qualified personnel and are time consuming. Therefore, biosensors are being used for the detection of cardiac markers and early diagnosis. Biosensors have been reported to offer vast advantages over conventional diagnosis assays since they are established on electrical measurements and also employ biochemical molecular recognition elements which gives a desired selectivity with a particular biomarker of interest [92, 93].

#### **8. Conclusions**

Biosensors continue to offer solutions and control of various processes across a range of applications. As technology advances, new methods that will result in the development of even better biosensors are emerging, and these seek to address all limitations associated with these devices. The development of biosensors revolves around their sensitivity, specificity, cost effectiveness and ability to detect small molecules. This is mostly determined by the right combination of a biological receptor and a transducer element, components which form the basis of a biosensor.

#### **Acknowledgements**

The authors would like to thank the DSI/Mintek Nanotechnology Innovation Centre for financial assistance towards this project.

*Biosensors: Design, Development and Applications DOI: http://dx.doi.org/10.5772/intechopen.97576*

### **Conflict of interest**

Authors report no conflict of interest.

#### **Author details**

Phumlani Tetyana1 \*, Poslet Morgan Shumbula<sup>2</sup> and Zikhona Njengele-Tetyana3

1 Department of Science and Innovation/Mintek Nanotechnology Innovation Centre, Advanced Materials Division, Mintek, Randburg, Johannesburg, South Africa

2 Department of Chemistry, University of Limpopo, Sovenga, South Africa

3 Centre for Metal Based Drug Discovery, Advanced Materials Division, Mintek, Randburg, Johannesburg, South Africa

\*Address all correspondence to: phumlanit@mintek.co.za

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### **References**

[1] Monosik R, Stredansky M, Sturdik E. Biosensors — classification, characterization and new trends. Acta Chimica Slovaca. 2012;5(1);109-120, DOI: 10.2478/v10188-012-0017-z

[2] Turner APF. Biosensors: sense and sensibility. Chem. Soc. Rev., 2013; 42; 3184-3196. DOI:10.1039/c3cs35528d

[3] Mehrotra P. Biosensors and their applications – A review. Journal of Oral Biology and Craniofacial Research. 2016;6;153-159. http://dx.doi. org/10.1016/j.jobcr.2015.12.002

[4] Thevenot D.R., Toth K., Durst R.A., Wilson G.S. Electrochemical biosensors: recommended definitions and classification. Pure Appl Chem. 1999;71:2333-2348.

[5] Damiati S, Schuster B. Electrochemical Biosensors Based on S-Layer Proteins. Sensors. 2020; 20; 1721; doi:10.3390/s20061721

[6] Sabr AKH. Biosensors. American Journal of Biomedical Engineering. 2016; 6(6); 170-179. DOI: 10.5923/j. ajbe.20160606.03

[7] Korotkaya EV. Biosensors: Design, Classification, and Applications in the Food Industry. Foods and Raw Materials. 2014;2 (2);161-171. DOI 10.12737/5476

[8] Malhotra S, Verma A, Tyagi N, Kumar V. Biosensors: principle, types and applications. Int. J. Adv. Res. Innov. Ideas Educ. 2017; 3 (2); 3639-3644

[9] Malik P, Katyal V, Malik V, Asatkar A, Inwati G, Mukherjee TK. Nanobiosensors: Concepts and Variations. International Scholarly Research Notices. 2013; 2013; doi. org/10.1155/2013/327435

[10] Grieshaber D, MacKenzie R, Voros J, Reimhult E. Electrochemical Biosensors - Sensor Principles and Architectures. Sensors. 2008; 8; 1400-1458. DOI: 10.3390/s80314000

[11] Bhalla N, Jolly P, Formisano N, Estrela P. Nikhil Bhalla, Pawan Jolly, Nello Formisano and Pedro Estrela. Essays in Biochemistry. 2016;60;1-8. DOI: 10.1042/EBC20150001

[12] Hughes WS. The potential difference between glass and electrolytes in contact with the glass. Journal of American Chemical Society. 1922; 44; 2860-2867. DOI: 10.1021/ja01433a021.

[13] Clark LC, Lyons C. Electrode systems for continuous monitoring cardiovascular surgery. Annuals of the New York Academy of Sciences. 1962; 102; 29-45.

[14] Li Y-CE, Lee IC. The Current Trends of Biosensors in Tissue Engineering. Biosensors. 2020; 10(88); 1-22. doi:10.3390/bios10080088

[15] Chaubey A, Malhotra BD. Mediated biosensors. Biosensors & Bioelectronics. 2002; 17; 441-456. DOI.org/10.1016/ S0956-5663 (01)00313-X

[16] Paddle BM. Biosensors for chemical and biological agents of defence interest. Biosensors & Bioelectronics. 1996; 11 (11); 1079-1113. DOI: 0956-5663/961515.00

[17] Lowe CR. Biosensors. Trends in Biotechnology. 1984; 2(3); 59-65. doi. org/10.1016/0167-7799 (84)90011-8

[18] Castillo J, Gáspár S, Leth S, Niculescu M, Mortari A, Bontidean I, Soukharev V, Dorneanu SA, Ryabov AD, Csöregi E. Biosensors for life quality Design, development and applications. Sensors and Actuators B. 2004; 102; 179-194. DOI:10.1016/j. snb.2004.04.084

*Biosensors: Design, Development and Applications DOI: http://dx.doi.org/10.5772/intechopen.97576*

[19] Arnold MA, Meyerhoff ME. Recent advances in the development and analytical applications of biosensing probes, C R C Critical Reviews in Analytical Chemistry. 1988; 20; 149-196. doi.org/10.1080/ 00078988808048811

[20] Pearson JE, Gill A, Vadgama P. Analytical aspects of biosensors. Annals of Clinical Biochemistry. 2000; 37; 119-145.

[21] Thevenot DR, Toth K, Durst RA, Wilson GS. Electrochemical biosensors: recommended definitions and classification. Biosensors and Bioelectronics. 2001; 16; 121-131. DOI. org/10.1016/S0956-5663 (01)00115-4

[22] Wilkins E, Atanasov P. Glucose monitoring: state of the art and future possibilities. Medical Engineering and Physics. 1996; 18; 273-288. doi. org/10.1016/1350-4533 (95)00046-1

[23] Ramirez NB, Salgado AM, Valdman B. The evolution and developments of immunosensors for health and environmental monitoring: Problems and perspectives. Brazilian Journal of Chemical Engineering. 2009; 26 (02); 227-249. DOI: 10.1590/ S0104-66322009000200001

[24] Sethi RS. Transducer aspects of biosensors. Biosensors & Bioelectronics. 1994; 9; 243-264. doi.org/10.1016/0956- 5663 (94)80127-4

[25] Soleymani L, Li F. Mechanistic Challenges and Advantages of Biosensor Miniaturization into the Nanoscale. American Chemical Society Sensors 2017;2 (4); 458-467. doi.org/10.1021/ acssensors.7b00069

[26] Njagi JI, Kagwanja SM. The Interface in Biosensing: Improving Selectivity and Sensitivity. In: Helburn R, Vitha MF, editors. Interfaces and interphases in Analytical Chemistry. American Chemical Society; 2011. p. 225-247. DOI: 10.1021/bk-2011- 1062.ch011

[27] Ali J, Najeeb J, Ali MA, Aslam MF, Raza A. Biosensors: Their Fundamentals, Designs, Types and Most Recent Impactful Applications: A Review. Journal of Biosensors & Bioelectronics. 2017;8(1); 1-9. DOI: 10.4172/2155-6210.1000235

[28] Saha K, Agasti SS, Kim C, Li X, Rotello VM. Gold nanoparticles in chemical and biological sensing. Chemical Reviews. 2012; 112; 2739-2779. DOI: 10.1021/cr2001178

[29] Wang Y, Knoll W, Dostalek J. Bacterial pathogen surface plasmon resonance biosensor advanced by long range surface plasmons and magnetic nanoparticle assays. Analytical Chemistry. 2012; 84; 8345-8350. doi. org/10.1021/ac301904x

[30] Polatoğlu I, Aydın L, Nevruz BC, Özer S. A Novel Approach for the Optimal Design of a Biosensor. Analytical Letters. 2020; 1428-1445. DOI:10.1080/00032719.2019.1709075

[31] Morales MA, Halpern JM. Guide to Selecting a Biorecognition Element for Biosensors. Bioconjugate Chemistry. 2018; 29(10); 3231-3239. doi:10.1021/acs. bioconjchem.8b00592

[32] Korotkaya EV. Biosensors: Design, Classification, and Applications in the Food Industry. Foods and Raw Materials. 2014;2 (2);161-171. DOI 10.12737/5476

[33] Sassolas A, Blum LJ, Leca-Bouvier BD. Immobilization strategies to develop enzymatic biosensors. Biotechnology Advances. 2012; 30; 489-511. DOI: 10.1016/j. biotechadv.2011.09.003

[34] Morales MA, Halpern JM. Guide to Selecting a Biorecognition Element for Biosensors. Bioconjugate Chemistry.

2018; 29(10); 3231-3239. doi:10.1021/acs. bioconjchem.8b00592.

[35] Najeeb MA, Ahmad Z, Shakoor RA, Mohamed AMA, Kahraman R. A novel classification of prostate specific antigen (PSA) biosensors based on transducing elements. Talanta. 2017; 168; 52-61. DOI: 10.1016/j.talanta.2017.03.022

[36] Mungroo NA, Neethirajan S. Biosensors for the Detection of Antibiotics in Poultry Industry. A Review. Biosensors. 2014; 4, 472-493. DOI:10.3390/bios4040472

[37] Ferri S, Kojima K, Sode K. Review of glucose oxidase and glucose dehydrogenases. Journal of diabetes science and Technology. 2011; 5; 1068-1076. DOI: 10.1177/ 193229681100500507

[38] Ali SMU, Nur O, Willander M, Danielson B. A fast and sensitive potentiometric glucose microsensor based on glucose oxidase coated ZnO nanowires grown on a thin layer wire. Sensors and Actuators B: Chemical. 2010; 145; 869-874. DOI:10.1016/j. snb.2009.12.072

[39] Updike S, Hicks G. The enzymatic electrode. Nature. 1967; 214; 986-988

[40] Marquette CA. State of the art and research advances in immunoanalytical systems. Biosensors and Bioelectronics. 2005; 21; 1424-1433. DOI: 10.1016/j. bios.2004.09.037

[41] Wang J. DNA biosensors based on peptide nucleic acid (PNA) recognition layers - A review. Biosensors and Bioelectronics. 1998; 13 (7-8); 757-762. DOI: 10.1016/s0956-5663(98)00039-6.

[42] Monošík R, Streďanský M, Šturdík E. Biosensors-classification, characterization and new trends. Acta Chimica Slovaca. 2012; 5; 109-120. DOI: https://doi.org/10.2478/v10188- 012-0017-z.

[43] Lucarelli F, Tombelli S, Minnuni M, Marazza G, Mascini M. Electrochemical and piezoelectric DNA biosensors for hybridisation detection. Analytica Chimica Acta. 2008; 609; 139-159. DOI: 10.1016/j.aca.2007.12.035

[44] Koyun A, Ahlatcolu E, Koca Y. Biosensors and their principles. In A Roadmap of Biomedical Engineers and Milestones; Kara, S., Ed.; InTech: Rijeka, Croatia, 2012

[45] Mungroo NA, Neethirajan S. Biosensors for the Detection of Antibiotics in Poultry Industry. A Review. Biosensors. 2014; 4, 472-493. DOI: 10.3390/bios4040472

[46] Lazcka O, Del Campo FJ, Munoz FX. Pathogen detection: A perspective of traditional methods and biosensors. Biosensors and Bioelectronics. 2007; 22; 1205-1217. DOI: 10.1016/j.bios.2006.06.036

[47] Wang J, Rivas G, Cai X, Palecek E, Nielsen P, Shiraishi H, Dontha N, Luo D, Parrado C, Chicharro M, Farias P, Valera FS. DNA electrochemical biosensors for environmental monitoring: a review. Analytical Chimica Acta. 1997; 347; 1-8. DOI: 10.1016/S0003-2670(96)00598-3.

[48] Huet AC, Fodey T, Haughey SA, Weigel S, Elliott C, Delahaut P. Advances in biosensor based analysis for antimicrobial residues in foods. Trends in Analytical Chemistry. 2010; 29; 1281-1294. DOI: 10.1016/j. trac.2010.07.017.

[49] Karyakin AA, Ulasova EA, Vagin MY, Karyakina, EE. Sensor (Sensor), 2002, no. 1, pp. 16-24

[50] Korotkaya EV. Biosensors: design, classification, and applications in the food industry. Foods and raw materials. 2014; 2(2); 161-171. DOI: 10.12737/5476.

[51] Lee WE, Thomson HG, Hall JG, Fulton RE, Wong JP. Rapid

*Biosensors: Design, Development and Applications DOI: http://dx.doi.org/10.5772/intechopen.97576*

immunofiltration assay of Newcastle disease virus using a silicon sensor. Journal of Immunological Methods. 1993; 166; 123-131. DOI: 10.1016/0022-1759(93)90336-6.

[52] Thompson HG, Lee WE. Rapid immunofiltration assay of Francisella tularensis. Defence Research Establishment Suffield. 1992; 1376: 1-17.

[53] Hu N, Wu C, Ha D, Wang T, Liu Q, Wang P. A novel microphysiometer based on high sensitivity LAPS and micro-fluidic system for cellular metabolism study and rapid drug screening. Biosensors and Bioelectronics. 2013; 40(1); 167-173. DOI: 10.1016/j.bios.2012.07.010.

[54] Reza KD, Azadeh A, Maryam N, Golnaz R, Morteza AA. Biosensors: Functions and Applications. Journal of Biology and Today's World. 2013; 2 (1); 20-23. DOI: 10.15412/J.JBTW.01020105.

[55] Nakamura N, Shigematsu A, Matsunaga T. Electrochemical detection of viable bacteria in urine and antibiotic selection. Biosensors and Bioelectronics. 1991; 6; 575-580. DOI: 10.1016/ 0956-5663(91)80022-p.

[56] Brooks JL, Mirhabibollahi B, Kroll RG. Experimental enzyme-linked amperometric immunosensors for the detection of Salmonella in foods. Journal of Applied Bacteriology. 1992; 73; 189-196. DOI: 10.1111/j.1365-2672.1992. tb02977.x

[57] Silley P, Forsythe S. Impedance microbiology: a rapid change for microbiologists Journal of Applied Bacteriology. 1996; 80; 233-243. DOI: 10.1111/j.1365-2672.1996.tb03215.x.

[58] Miroslav P. The Piezoelectric Biosensors: Principles and applications. A review. International Journal of Electrochemical Science. 2017; 12; 496-506. DOI: 10.20964/2017.01.44

[59] Yuwono AS, Lammers PS. Odor Pollution in the Environment and the Detection Instrumentation. Agricultural Engineering International: the CIGR Journal of Scientific Research and Development. Invited Overview Paper, 5

[60] Leatherbarrow RJ, Edwards PR. Analysis of molecular recognition using optical biosensors. Current Opinions in Chemical Biology. 1999; 3; 544-547. DOI: 10.1016/s1367-5931(99)00006-x

[61] Bănică, F-G. (2012). What are chemical sensors? In: Chemical sensors and biosensors. Chichester: Wiley, 1-20

[62] Handrigan JP. Rapid Detection of Food-Borne Pathogens. 2010. http:// www.johnpaulhandrigan.net/ wp-content/uploads/2012/01/ John-Paul-Handrigan

[63] Formisano N, Jolly P, Bhalla N, Cromhout M, Flanagan SP, Fogel R, Limson JL, Estrela P. Optimisation of an electrochemical impedance spectroscopyaptasensor by exploiting quartz crystal microbalance with dissipation signals. Sensors and Actuators B. 2015; 220; 369-375. DOI: 10.1016/j.snb.2015.05.049

[64] Miroslav P. The Piezoelectric Biosensors: Principles and applications. A review. International Journal of Electrochemical Science. 2017; 12; 496-506. DOI: 10.20964/2017.01.44

[65] Kretschmann E. Determination of optical constants of metals by excitation of surface plasmons. Zeitschrift für Physik A Hadrons and nuclei. 1971; 241; 313-324

[66] Schasfoort RBM, Tudos AJ. (2008). How to construct an SPR assay? In Hand book of Surface Plasmon Resonance; RSC Publishing: Cambridge, UK, 2008; 3-9

[67] Liedberg B, Nylander C, Lundstrum I. Surface plasmon resonance for gas detection and biosensing. Sensors and Actuators B. 1983; 4; 299-304. DOI: 10.1016/0250-6874(82)80008-5

[68] Mungroo NA, Neethirajan S. Biosensors for the Detection of Antibiotics in Poultry Industry. A Review. Biosensors. 2014; 4, 472-493. DOI: 10.3390/bios4040472

[69] Inamor K, Kyo M, Nishiya Y, Inoue Y, Sonoda T, Kinoshita E, Koike T, Katayama Y. Detection and quantification of on-chip phosphorylated peptides by surface plasmon resonance imaging techniques using a phosphate capture molecule. Analytical Chemistry. 2005; 77; 3979- 3985. DOI: 10.1021/ac050135t

[70] Ali SMU, Nur O, Willander M, Danielson B. A fast and sensitive potentiometric glucose microsensor based on glucose oxidase coated ZnO nanowires grown on a thin layer wire. Sensors and Actuators B: Chemical. 2010; 145; 869-874. DOI:10.1016/j. snb.2009.12.072

[71] Kanoh N, Kyo M, Inamori K, Ando A, Asami A, Nakao A, Osada H. SPR imaging of photo-cross-linked small-molecule arrays on gold. Analytical Chemistry. 2006; 78; 2226- 2230. DOI: 10.1021/ac051777j.

[72] Hu N, Wu C, Ha D, Wang T, Liu Q, Wang P. A novel microphysiometer based on high sensitivity LAPS and micro-fluidic system for cellular metabolism study and rapid drug screening. Biosensors and Bioelectronics, 2013; 40 (1); 167-173. DOI: 10.1016/j.bios.2012.07.010

[73] Li Y, Liu X, Lin Z. Recent developments and applications of surface plasmon resonance biosensors for the detection of mycotoxins in foodstuffs. Food Chemistry.132, 1549- 1554. DOI: 10.1016/j. foodchem.2011.10.109

[74] Thiel AJ, Frutos AG, Jordan CE, Corn RM, Smith LM. In situ surface plasmon resonance imaging detection of DNA hybridization to oligonucleotide arrays on gold surfaces. Analytical Chemistry. 69, 4948-4956. DOI: 10.1021/ac0010431.

[75] Jordan CE, Corn RM. Surface Plasmon Resonance Imaging Measurements of Electrostatic Biopolymer Adsorption onto Chemically Modified Gold Surfaces. Analytical Chemistry. 1997; 69; 1449-1456. DOI: 10.1021/ac961012z

[76] Singh S, Kumar V, Dhanjal DS, Datta S, Prasad R, Singh J. Biological Biosensors for Monitoring and Diagnosis. In: Singh J, Vyas A, Wang S, Prasad R, editors. Microbial Biotechnology: Basic Research and Applications. Environmental and Microbial Biotechnology. Springer; 2020. p. 317-335.DOI:10.1007/978- 981-15-2817-0\_14

[77] Manikandan R, Charumathe N, Fariha BA. Applications of biosensors. Bulletin of Scientific Research. 2019; 1(1); 34-40. DOI: 10.34256/bsr1915

[78] Wei N, Xin X, Du J, Li J. A novel hydrogen peroxide biosensor based on the immobilization of hemoglobin on three-dimensionally ordered macroporous (3DOM) goldnanoparticle-doped titanium dioxide (GTD) film. Biosensors and Bioelectronics. 2011; 26; 3602-3607. DOI: 10.1016/j.bios.2011.02.010

[79] Villalonga R, Díez P, Yáñez-Sedeño P, Pingarrón JM. Wiring horseradish peroxidase on gold nanoparticles-based nanostructured polymeric network for the construction of mediatorless hydrogen peroxide biosensor. Electrochimica Acta, 56, 4672-4677. DOI:10.1016/J. ELECTACTA.2011.02.108

[80] Rana JS, Jindal J, Beniwal V, Chhokar V. Utility Biosensors for *Biosensors: Design, Development and Applications DOI: http://dx.doi.org/10.5772/intechopen.97576*

applications in Agriculture – A Review. Journal of American Science. 2010; 6(9); 353-375.

[81] Justino CIL, Duarte AC, Rocha-Santos TAP. Recent Progress in Biosensors for Environmental Monitoring: A Review. Sensors. 2017; 17; 2918-2943. DOI:10.3390/s17122918

[82] Atkinson AL, Haggett BGD. Whole Cell Biosensors for Environmental Monitoring. Sensor Review. 1993; 13(4); 19 - 22. DOI.org/10.1108/eb007917

[83] Nigam VK, Shukla P. Enzyme Based Biosensors for Detection of Environmental Pollutants - A Review. Journal of Microbiology and Biotechnology. 2015; 25(11); 1773-1781. https://doi.org/10.4014/jmb.1504.04010

[84] Tortolini C, Mazzei F. Electrochemical biosensors for environmental monitoring. International Journal of Environment and Health. 2012; 6(2); 93-110. https:// doi.org/10.1039/B403975K.

[85] Tothill IE. Biosensors for cancer markers diagnosis. Seminars in Cell & Developmental Biology. 2009; 20; 55-62. DOI: 10.1016/j.semcdb.2009.01.015

[86] Bohunicky B, Mousa SA. Biosensors: the new wave in cancer diagnosis. Nanotechnology, Science and Applications. 2011; 4; 1-10. DOI: 10.2147/NSA.S13465

[87] Bohunicky B, Mousa SA. Biosensors: the new wave in cancer diagnosis. Nanotechnology, Science and Applications. 2011; 4; 1-10. DOI: 10.2147/NSA.S13465

[88] Tothill IE. Biosensors for cancer markers diagnosis. Seminars in Cell & Developmental Biology. 2009; 20; 55-62. DOI: 10.1016/j.semcdb.2009.01.015

[89] Ooi KGJ, Galatowicz G, Towler HMA, Lightman SL, Calder VL. Multiplex cytokine detection versus

ELISA for aqueous humor: IL-5, IL-10, and IFN profiles in uveitis. Investigative Ophthalmology and Visual Science. 2006; 47; 272-277. DOI: 10.1167/ iovs.05-0790.

[90] Caruso R, Trunfio S, Milazzo F, Campolo J, De Maria R, Colombo T, Parolini M, Cannata A, Russo C, Paino R, Frigerio M, Martinelli L, Parodi O. Early expression of proand anti-inflammatory cytokines in left ventricular assist device recipients with multiple organ failure syndrome. American Society of Artificial Internal Organs. 2010; 56; 313-318

[91] Caruso R, Verde A, Cabiati M, Milazzo F, Boroni C, Del Ry S, Parolini M, Vittori C, Paino R, Martinelli L, Giannessi D, Frigerio M, Parodi O. Association of preoperative interleukin-6 levels with interagency registry for mechanically assisted circulatory support profiles and intensive care unit stay in left ventricular assist device patients. J Heart Lung Transplant. 2012; 31(6); 625-633. DOI: 10.1016/j.healun.2012.02.006

[92] Watson CJ, Ledwidge MT, Phelan D, Collier P, Byrne JC, Dunn MJ, McDonald KM, Baugh JA. Proteomic analysis of coronary sinus serum reveals leucine-rich 2-glycoprotein as a novel biomarker of ventricular dysfunction and heart failure. Circulation Heart Failure. 2011; 4; 188-197. DOI: 10.1161/ CIRCHEARTFAILURE.110.952200

[93] Maurer M, Burri S, de Marchi S, Hullin R, Martinelli M, Mohacsi P, Hess OM. Plasma homocysteine and cardiovascular risk in heart failure with and without cardiorenal syndrome. International Journal of Cardiology. 2010; 141; 32-38. DOI: 10.1016/j. ijcard.2008.11.131

#### **Chapter 4**

## Plasmonic Nanopores: Optofluidic Separation of Nano-Bioparticles via Negative Depletion

*Xiangchao Zhu, Ahmet Cicek, Yixiang Li and Ahmet Ali Yanik*

#### **Abstract**

In this chapter, we review a novel "optofluidic" nanopore device enabling label-free sorting of nano-bioparticles [e.g., exosomes, viruses] based-on size or chemical composition. By employing a broadband objective-free light focusing mechanism through extraordinary light transmission effect, our plasmonic nanopore device eliminates sophisticated instrumentation requirements for precise alignment of optical scattering and fluidic drag forces, a fundamental shortcoming of the conventional optical chromatography techniques. Using concurrent optical gradient and radial fluidic drag forces, it achieves self-collimation of nanobioparticles with inherently minimized spatial dispersion against the fluidic flow. This scheme enables size-based fractionation through negative depletion and refractive-index based separation of nano-bioparticles from similar size particles that have different chemical composition. Most remarkably, its small (4 μm 4 μm) footprint facilitates on-chip, multiplexed, high-throughput nano-bioparticle sorting using low-cost incoherent light sources.

**Keywords:** plasmonic nanopore, optical tweezers, optofluidics, extraordinary light transmission, nano-bioparticle sorting

#### **1. Introduction**

Optical chromatography (OC) is an increasingly adapted technique for labelfree sorting and analysis of bioparticles including cells, bacteria, fungi [1–4]. It exploits a lightly focused Gaussian laser beam within a microfluidic channel to create opposing optical scattering and fluidic drag forces. One can leverage these controllable forces to realize selective fractionation of bioparticles in a heterogeneous mixture based on size, morphology or chemical composition (i.e., refractive index variation) [5, 6]. OC technique was first implemented in size-based fractionation of inorganic materials such as polystyrene beads. Later, researchers employed this technique for size-based fractionation and sorting of organic particles including human blood constituents including erythrocytes, monocytes, granulocytes, and lymphocytes [2, 5]. Subsequently, differentiation of micronscale bioparticles with subtle differences [4, 7], including those with size differences as small as 70 nm [8], are shown. In addition to size-based separation, OC technique also offers refractive index-based fractionation capability, allowing separation of bioparticles with

minuscule differences in chemical composition, such as *Bacillus anthracis* and *Bacillus thuringiensis* [4] and cells with single gene modifications [3]. Most recently, precise separation capability of OC technique is utilized in realization of multi-stage fractionation approaches enabling network-based microfluidic purification [9, 10]. On the other hand, conventional OC technique suffers from powerful laser beam requirements to create sufficiently strong optical scattering forces [2], as well as multiple off-chip and bulky optical multi-axis positioners that are needed to realize well-controlled laser beam profiles precisely aligned against the fluidic flow [5]. Furthermore, separate sets of light sources and optical components are needed for each processing channels, preventing multiplexed high-throughput operation [10].

In a recent publication, we introduced a novel plasmonic nanopore device that eliminates the shortcomings of the conventional OC technique [11]. Here, we review this hybrid Optofluidic PlasmonIC (OPtIC) device merging light focusing and fluidic flow through a tiny (4 μm 4 μm footprint) plasmonic microlens housing an integrated nanopore channel. Based on a subwavelength-thick ( 200 nm) suspended device structure, our optofluidic approach opens the door to practical, scalable, and high-throughput on-chip particle sorting.

#### **2. OPtIC microlens design**

In **Figure 1a**, an OPtIC device that consists of a periodic nanohole array (NHA) defined in a suspended multilayer membrane is shown. The mechanically robust membrane consists of a free-standing 100 nm thick silicon nitride (Si3N4) substrate coated with 100 nm thick gold (Au) and a 5 nm thick titanium (Ti) adhesion layer. The total thickness of the microlens is *h* = *t*Au + *t*Ti + *t*Si3N4 = 205 nm, whereas the lateral dimension of the finite size NHA is 4 μm 4 μm. Recent research findings suggest that (quasi)periodic arrays of nanoplasmonic apertures behave as microconvex lenses focusing broadband incoherent light beams to spot sizes comparable to wavelength of light [11–13]. Such tight light focusing capability can be harnessed to realize sufficiently strong optical scattering forces suitable for OC using collimated broadband light sources [14, 15]. In addition, the finite-size plasmonic NHAs can focus light over a broad wavelength range with focusing characteristics dictated by the lateral dimension of the array and nearly insensitive to sub-structural imperfections [13]. In this respect, our plasmonic nanopore device provides a distinct nanofluidic integration capability through small modifications in the NHA design without degrading its light focusing characteristics. The periodic NHA shown in **Figure 1a** consists of *d* = 150 nm diameter openings with a periodicity of *a* = 380 nm. Enhanced light transmission through the periodic nanohole around this center nanoaperture occurs through the extraordinary optical transmission (EOT) effect [16–19]. The enlarged central nanopore with *dc* = 500 nm exhibits orders of magnitude smaller fluidic resistance with respect to the neighboring nanoholes, enabling efficient nanofluidic flow through it. The OPtIC device uses inlet and outlet fluidic ports that are on the opposite sides of the NHA [20, 21], as depicted in **Figure 1b**. This design facilitates microfluidic access from either side of the membrane [22]. In our simulations, 50 μm distance in between of the inlet and outlet fluidic ports is chosen to provide a clear path for the focused light beam [20].

**Figure 1b** depicts the cross-sectional view of nanofluidic flow pattern across the OPtIC device calculated using steady-state finite-element method (FEM) simulations (COMSOL Multiphysics). The overall size of the computational domain in **Figure 1b** is 50 μm 50 μm 40 μm. The inlet fluidic flow is directed towards the central aperture, where flow velocity is largest along the optical (*z*) axis in the vicinity of the optical focal point, whereas an almost symmetric behavior is

*Plasmonic Nanopores: Optofluidic Separation of Nano-Bioparticles via Negative Depletion DOI: http://dx.doi.org/10.5772/intechopen.96475*

#### **Figure 1.**

*OPtIC nanopore device enabling selective sorting of bioparticles: (a) top view of OPtIC microlens consisting of a 9 9 NHA with enlarged central aperture. (b) Nanofluidic flow pattern across the OPtIC device with 1.3 μm/ s flow rate at the focal point. (c) Conceptual illustration of the selective separation mechanism for nanobioparticles through counter acting forces at the focal point. Copyright 2020 nature publishing group adapted with permission [11].*

observed towards the outlet port. The observed fluidic flow pattern can be understood through the Hagen-Poiselle law, where the pressure-driven flow across a cylindrical aperture with hydraulic diameter *r*<sup>H</sup> and thickness *h* occurs with a volumetric flow rate given by *Q* = Δ*p*/*R*<sup>H</sup> (in m<sup>3</sup> s 1 ). Here, Δ*p* is the pressure gradient across the aperture and *R*<sup>H</sup> = 8*μh*/π*r*<sup>H</sup> <sup>4</sup> (in Pa<sup>s</sup> 3 <sup>m</sup><sup>1</sup> with *<sup>μ</sup>* = 8.9 <sup>10</sup><sup>4</sup> Pa<sup>s</sup> being dynamic viscosity of water) is the hydraulic resistance [23]. Since the hydraulic resistance is inversely proportional to the 4th power of hydraulic radius, it is two orders of magnitude smaller across the central aperture with respect to the rest of the holes in the NHA. Hence, convective fluidic flow, which follows the least resistance path, is through the central nanoaperture, as shown in our simulations. In summary, the OPtIC device forces nano-bioparticles to flow towards its focal point, where the dynamic flow trajectories of the particles are aligned with the optical axis of the plasmonic microlens.

A close-up cross-sectional view of the OPtIC device is given in **Figure 1c**, where the fluidic flow is in the -*z* direction within the close vicinity of the focal point (*f*<sup>0</sup> away from microlens top) as explained above. In this configuration, the collimated light incident from bottom along the +*z* direction is focused by the plasmonic microlens along the optical axis. Here, the focusing pattern, the amplitude-squared electric field (|*E*| 2 ), is calculated through finite-difference time-domain (FDTD) simulations for incident light at *λ* = 655 nm. Forces acting on two different size nano-bioparticles within the focal point region are depicted on the right of the **Figure 1c**. Here, the optical scattering force (**Fs**) is inherently aligned against the

fluidic drag force (**Fd**) along the optical axis for both particles. In addition, thermoplasmonic drag force (**Ftp**) caused by electromagnetic heating acts in parallel to **Fs**. This will be explained in detail later. In addition to radial drag forces (**Fd,r**) due to the fluidic flow, the optical gradient forces (**Fg**) collimate particles along the optical axis, thus providing a robust mechanism for their precise alignment along the optical axis.

**Figure 1c** depicts that large particles with diameters above a threshold are driven against the fluid flow (i.e. in the +*z* direction) provided that **Fs** is sufficiently larger than **Fd**. This is also true for particles with larger refractive indices. Thus, particles with larger diameters and/or higher refractive indices are rejected by the OPtIC device. In contrast, particles with smaller diameters and/or lower refractive indices are propelled through the central nanopore and leave the system from the outlet port. This mechanism provides a complete separation capability for smaller nanobioparticles (e.g. exosomes) in a heterogeneous mixture through negative depletion. Clogging of the central aperture is prevented by the microlens itself since it keeps the larger particles away from the surface.

Optical radiation force acting on nano-bioparticles can be divided into scattering **Fs** and gradient **Fg** components, as discussed above, which act along and perpendicular to the optical axis, respectively. While **Fs** acts against **Fd**, **Fg** is directed towards the optical axis. Their magnitudes are given by [14]:

$$F\_{\mathfrak{s}\_{\mathfrak{g}}} = \frac{2n\_m P}{\mathfrak{c}} \mathcal{Q}\_{\mathfrak{s}\_{\mathfrak{g}}} \tag{1}$$

where *P* is incident light power, *n*<sup>m</sup> is surrounding medium's refractive index, *c* is the speed of light and *Q*s,g is a respective dimensionless parameter representing optical pressure transfer efficiency due to reflection/refraction at material interfaces. It can be analytically calculated for simple beam profiles such as lightly focused Gaussian beams acting on a spherical particle. On the other hand, scenarios that use complex beam profiles or target smaller particles with diameters comparable to the optical wavelength (e.g. *d* � 1 μm), the ray optics approximation cannot be used. Instead, a Maxwell stress tensor (MST) approach should be adopted [24, 25].

$$T\_{\vec{\eta}} = e\mathbf{E}\_i\mathbf{E}\_j^\* + \mu\mathbf{H}\_i\mathbf{H}\_j^\* - \frac{\mathbf{1}}{2}\delta\_{\vec{\eta}}\left(e|\mathbf{E}|^2 + \mu|\mathbf{H}|^2\right) \tag{2}$$

where **E** and **H** are electric and magnetic field vectors, *ε* and *μ* are the electric permittivity and magnetic permeability of the medium, whereas *δ*ij is the Kronecker delta symbol. Using MST, the net optical radiation force on a small particle in an arbitrary field profile can be calculated through assuming a bounding box small enough to confine the particle as in [25].

$$F = \oint\_{S} \sum\_{j} \frac{1}{2} \operatorname{Re} \left( T\_{\vec{\eta}} \hat{n}\_{j} \right) \tag{3}$$

with *S* being box surface where *n*^ *<sup>j</sup>* is a unit vector along one of the principal axes.

#### **3. Focusing efficiency of OPtIC microlens**

The central nanopore opening plays a key role in precise alignment of fluidic flow along the optical axis and determining the threshold rejection diameter. On the *Plasmonic Nanopores: Optofluidic Separation of Nano-Bioparticles via Negative Depletion DOI: http://dx.doi.org/10.5772/intechopen.96475*

electromagnetic part, it also controls the focusing characteristics of the OPtIC microlens. Hence, it should be ensured that the focusing behavior does not deteriorate for an admissible *d*<sup>c</sup> range [13]. Focusing patterns of the microlens illuminated by plane waves with *λ* = 655 nm for various *d*<sup>c</sup> values are given in **Figure 2a**. Compared with the cases of no central nanopore (i.e., *d*<sup>c</sup> = 0 nm) and a uniform NHA (where *d*<sup>c</sup> = 150 nm), the enlarged aperture (*d*<sup>c</sup> = 500 nm) has a negligible effect on light focusing behavior, i.e., maximum intensity (|*E*| 2 ), spot size and depth of field (DoF). Moreover, focusing behavior does not significantly degrade for a large *dc* of 800 nm, as seen on the rightmost panel of **Figure 2a**.

The dashed horizontal lines in **Figure 2a**, corresponding to focal point, indicate that the focal length (*f*D) is minimally affected by the change of *d*c, where it is 5.32 μm for *d*<sup>c</sup> up to 500 nm, and slightly increases to 5.56 μm for *d*<sup>c</sup> = 800 nm. Intensity profiles along the focal axis (i.e., *z* = *f*D, dashed lines in **Figure 2a**) are presented in **Figure 2b**. It is clearly seen that the OPtIC microlens brings incident light to a tight focal spot with a full width at half maximum (FWHM) of 1.12 μm for *d*<sup>c</sup> ≤ 150 nm, whereas FWHM tends to slightly increase for *d*<sup>c</sup> ≥ 500 nm, as it becomes 1.24 μm and 1.80 μm for *d*<sup>c</sup> = 500 nm and 800 nm, respectively. Thus, the focusing characteristics of the microlens is remarkably stable for a broad range of *d*c. Variation of optical intensity along the optical axis (z-direction) for different *d*<sup>c</sup> is shown in **Figure 2c**, where almost identical behavior is observed for relatively small size central nanopores (*d*<sup>c</sup> ≤ 150 nm). DoF also shows little variation for *d*<sup>c</sup> up to 500 nm. Only, a slight increase in focal distance is observed when *d*<sup>c</sup> = 800 nm.

#### **Figure 2.**

*Monochromatic light focusing behavior with varying central nanopore dimensions: (a) focusing behavior of OPtIC microlens for* λ *= 655 nm as a function of* d*c, corresponding field profile (b) along the focal axis (horizontal dashed lines in (a)) and (c) optical axis. (d) Transmission spectra for plasmonic nanopore devices with different diameter central nanopore openings. Copyright 2020 nature publishing group adapted with permission [11].*

The light focusing mechanism of OPtIC microlens relies on the periodic arrangement of smaller nanoholes around the central one. The EOT effect occurs when the Bragg condition is met, i.e., **G** = *i***Gx** + *j***Gy,** where *i* and *j* are the corresponding (*i*, *j*) grating orders [16, 18]. The transmission spectra shown in **Figure 2d** is obtained using *E*-field monitors on the focusing side of the microlens. EOT resonance occurs at *λ* = 650 nm (55 nm FWHM) for the (1,0) grating coupled condition. This confirms that the light focusing behavior is due to interference of inphase wave components emanating from the periodic NHA [13]. For the NHA with a large central nanopore (*d*<sup>c</sup> = 500 nm), deviation of the EOT peak compared to the NHA without a central opening (*d*<sup>c</sup> = 0 nm) is relatively small, although a larger background transmission is observed. However, further increase in the central nanopore dimensions (*d*<sup>c</sup> = 800 nm) leads to non-resonant light transmission, manifesting itself as enhanced background signal, as shown in **Figure 2d** (top curve). In the light of the above discussion regarding the fluidic flow around the focal point (see **Figure 1**) and light focusing behavior of NHA, an OPtIC microlens with 9 9 NHA of *d* = 150 nm and *a* = 380 nm, along with a central nanopore opening of *d*<sup>c</sup> = 500 nm is adopted for label-free sorting of nano-bioparticles.

An important observation in **Figure 2a** is the checkerboard-like pattern just above the OPtIC microlens surface, which arises from plasmonic Talbot effect, that is diffractive self-imaging of smaller-diameter nanoholes [13, 26]. On the other hand, intensity right over the central aperture is significantly enhanced for *d*<sup>c</sup> ≥ 500 nm due to diffractive light transmission through it. These two effects are compared in **Figure 3** using near field phase maps where each small nanohole transmits waves with almost identical amplitude and phase, giving rise to in-phase interference around the focal point. Closer inspection of **Figure 3** reveals that the checkerboard pattern is not disrupted when the central aperture is absent (**Figure 3a**) or is larger than the surrounding nanoholes in the array (**Figure 3c**).

#### **Figure 3.**

*Light focusing behavior due to in-phase interactions: Near-field phase maps of the hot intensity spots around the OPtIC nanopore device are presented for varying* d*<sup>c</sup> when illuminated by a monochromatic plane wave (*λ *= 655 nm).* d*<sup>c</sup> is equal to (a) 0 nm (no central nanopore), (b) 150 nm (identical central opening with the NHA pattern) and (c) 500 nm (enlarged central nanopore). Copyright 2020 nature publishing group adapted with permission [11].*

*Plasmonic Nanopores: Optofluidic Separation of Nano-Bioparticles via Negative Depletion DOI: http://dx.doi.org/10.5772/intechopen.96475*

Light intensity around the central nanopore opening increases with increasing *d*c, as seen in **Figure 2a**. This observation is confirmed in **Figure 2c** where a secondary peak in light intensity close to the microlens surface appears. This peak is less intense than the peak around the focal point for smaller size central nanopores (*d*<sup>c</sup> ≤ 150 nm). However, it is significantly enhanced for larger size nanopore (*d*<sup>c</sup> ≥ 500 nm). The high intensity region around the nanopore opening may lead to increased optical scattering force **Fs**, causing undesired rejection of smaller/lowerrefractive index particles that managed to pass the focal region and carried towards the central nanopore. However, in addition to tailoring the central nanopore dimension, one can also take advantage of Stokes flow [1, 9, 11], where the fluidic drag forces scale with the relative velocity of nano-bioparticles (**u**) with respect to the flow rate (**v**) of medium (i.e., **Fd** ∝|**u**-**v**|). As fluidic velocity **v** is approximately three orders of magnitude higher close to the central nanopore opening with respect to that of the focal point (**Figure 1b**), fluidic drag forces **Fd** are significantly larger too. Hence, optical scattering force **Fs** around the nanopore region cannot repel particles that were below the critical diameters. As a result, in the following sections, interplay of forces only around the focal point is considered in the assessment of sorting efficiencies of the OPtIC microlens.

#### **4. Broadband operation of OPtIC microlens**

In the preceding section, we showed that the OPtIC nanopore device can focus collimated monochromatic light at *λ* = 655 nm (close to the EOT resonance peak) into a tight spot. However, broad spectrum operation is also desirable to utilize lowcost broadband incoherent light sources, such as light emitting diodes (LEDs) and halogen bulbs. Hence, development of microlenses that exhibit minimal chromatic aberration is critical [13]. Here, we examine the broadband light focusing behavior of the OPtIC nanopore device with *d*<sup>c</sup> = 500 nm over a wavelength range spanning from 600 nm to 780 nm. **Figure 4a** shows that *f*<sup>D</sup> decreases monotonically with increasing *λ* with a maximum deviation (Δ*z*max) that is below 200 nm (�*λ*/33) between 620 nm and 680 nm, which resides within the FWHM of the EOT peak (**Figure 2d**). Below the short-wavelength tail of the EOT peak, Wood's anomaly [19, 27] leads to longer *f*<sup>D</sup> for *λ* = 600 nm at the transmission minimum (**Figure 2d**).

Optical intensity variation along the focal plane (dashed lines in **Figure 4a**) is shown in **Figure 4b**. Focal point has a FWHM of 1.08 μm, 1.12 μm, 1.24 μm and 1.28 μm at *λ* = 620 nm, 633 nm, 655 nm and 680 nm, respectively. In addition, the DoF calculated from **Figure 4c** shows small variations within the same spectral window (620 nm < *λ* < 680 nm). However, the DoF is considerably larger at the wavelength of 600 nm that resides outside the EOT spectral window. Therefore, light focusing characteristics over a sufficiently broad range of wavelengths hinges on the (1,0) resonance transmission (EOT) peak.

Using the Rayleigh-Sommerfeld (R-S) formula [13, 28, 29], the focal length of the finite-size NHA microlens can be calculated:

$$\frac{\text{dI}}{\text{dz}} = -2I\_0 \frac{\pi \rho^2}{\lambda \text{z}^2} \sin\left(\frac{\pi \rho^2 n}{\lambda \text{z}}\right) = \text{0} \tag{4}$$

where *I* and *I*<sup>0</sup> are the intensity values calculated at a distance above the lens along the optical (*z*) axis and the peak intensity, respectively. Here, *ρ* is the aperture radius and *n* is the refractive index of the surrounding medium. Comparison of the solid black curve obtained from FDTD simulations to the gray dots calculated via the R-S formula Eq. (4) are in very good agreement for *λ* between 620 nm and

#### **Figure 4.**

*Broadband light focusing: (a) simulated light focusing behavior of the optimized OPtIC microlens with* d*<sup>c</sup> = 500 nm for a range of* λ*, cross-sectional intensity variation along (b) the focal and (c) optical axis, as well as (d) variation of focusing characteristics in terms of* f*D, spot size and DoF with* λ*. the gray dots represent values obtained using the Rayleigh-Sommerfeld formula. Copyright 2020 nature publishing group adapted with permission [11].*

680 nm, as seen in **Figure 4d**. The shaded area bounded by the solid blue lines in **Figure 4d** indicates that DoF does not change significantly within the same wavelength range, even though incorporation of an enlarged central aperture breaks the NHA periodicity. Minimal modulation in the focal length and spot size is also shown in **Figure 4d** (the solid black and orange curves, respectively). Thus, the OPtIC microlens exhibits minimal chromatic aberration within the FWHM spread of the EOT peak, offering a well-defined broadband light focusing characteristic.

#### **5. Influence of thermo-plasmonic forces**

As conventional wisdom suggests, surface plasmon generation is accompanied by electromagnetic heating, which evokes heat-induced fluid dynamics. The local temperature elevation in the vicinity of the OPtIC microlens induces a buoyancedriven convective fluid flow (Archimedes force) against the reverse main flow stream, resulting in a thermo-plasmonic drag force that drives particles away from the microlens surface [30, 31]. A comprehensive review of this physical mechanism – thermo-induced fluid motion - can be found elsewhere [32, 33]. In this work, thermo-plasmonic drag forces are calculated using Multiphysics FEM simulations, which incorporate electromagnetic (EM) wave, heat transfer and Navier–Stokes equations. Here, we solve the EM wave Equation [34].

*Plasmonic Nanopores: Optofluidic Separation of Nano-Bioparticles via Negative Depletion DOI: http://dx.doi.org/10.5772/intechopen.96475*

$$\nabla \times (\nabla \times \mathbf{E}) - k\_0^2 \varepsilon(\mathbf{r}) \mathbf{E} = \mathbf{0} \tag{5}$$

where *k*<sup>0</sup> = 2π/*λ*<sup>0</sup> is free-space wavelength and *ε*(**r**) is spatial distribution of *ε* at <sup>λ</sup>0. The calculated **<sup>E</sup>**-field is used to find the heat source density *<sup>q</sup>*(*r*) = 0.5Re[*J*�*E*\* ], which is employed to find the total heat power using *Q* = Ð *q*(*r*)*dv, J* being the induced current density in metal [34]. Solving the heat transfer equation simultaneously with the incompressible Navier–Stokes relations,

$$\nabla \cdot \left[ \rho c\_p T(\mathbf{r}) \mathbf{v}(\mathbf{r}) - \kappa \nabla T(\mathbf{r}) \right] = Q(\mathbf{r}) \tag{6}$$

$$
\rho\_0[\mathbf{v}(\mathbf{r}) \cdot \nabla] \mathbf{v}(\mathbf{r}) + \nabla p(\mathbf{r}) - \eta \nabla^2 \mathbf{v}(\mathbf{r}) = \mathbf{F} \tag{7}
$$

where *ρ*, *K*, *c*<sup>p</sup> and *η* are the density, thermal conductivity, constant pressure specific heat capacity and dynamic viscosity of the fluidic medium, respectively. *T* (*r*) and *v*(*r*) are the temperature and the fluidic velocity where ∇� *v* = 0. Calculations are performed using material parameters that are adopted from the work of Roxworthy et al. [33]. Provided that the EM induced temperature gradient and convective fluid flow distribution are obtained through Eqs. (5)–(7), the volumetric thermo-plasmonic force **Ftp** and **Fd** can be calculated through the Boussinesq approximation [31, 33, 35].

$$\mathbf{F\_{tp}} = \mathbf{g}\rho\_0 \beta(T)[T(\mathbf{r}) - T\_0]\hat{\mathbf{z}}\tag{8}$$

and Stoke's equation

$$\mathbf{F\_d} = -6\pi\eta\mathbf{v}\mathbf{v} \tag{9}$$

where *g* denotes the gravitational acceleration constant and *β* is the thermal expansion coefficient of the water.

Steady-state 2D temperature spatial distributions in the *x*-*y* (**Figure 5a**) and *x*-*z* planes (**Figure 5b**) are calculated using Eqs. (5)–(9). To demonstrate the dynamical

#### **Figure 5.**

*Thermo-plasmonic heating and Rayleigh–Bénard flow: (a) temperature distribution on the OPtIC nanopore device surface under illumination (633 nm wavelength and 20 mW total power). (b) Temperature distribution and heat-induced fluidic flow pattern on a perpendicular plane crossing the optical axis. The arrows represent the velocity vector v. copyright 2020 nature publishing group adapted with permission [11].*

properties of the thermal-induced fluid convection, the temperature distribution is deliberately overlaid on a vertical 2D slice of convection velocity profile within the same *x*-*z* plane (**Figure 5b**). In our FEM simulations, the wavelength and power of the excitation light beam is assumed to be 633 nm and 20 mW, respectively. The ambient temperature is *T*<sup>0</sup> = 20 °C. The ambient temperature near and across the microlens surface is considerably increased due to endogenous heat generation via dissipative losses. Because light transmitting through the central aperture is mostly diffractive in nature and lightly coupled to the surface plasmon polariton (SPP) modes of the NHA, a relatively small temperature increase takes place close to the enlarged aperture region. On the contrary, a significant amount of heat is generated outside the central aperture area, which is attributed to non-radiative damping of SPPs launched on the metal/dielectric interface. Due to the large differences in the heat conductivity of Au and water, heat dissipation occurs slowly along the optical axis of the microlens within the solution environment. This results in reduction of the mass density of ambient water, leading to an upward-directed convective fluidic flow that possesses the features of a toroidal Rayleigh–Bénard flow [33], as represented by the arrows in **Figure 5b**. Here, **v** is along the optical axis in the +*z* direction, exerting a drag force on the suspended nano-bioparticles that directs them away from the microlens surface. Our calculations show that the maximum heat induced convective flow velocity is *v*max = 900 nm/s, whereas the flow velocity is *v* = 360 nm/s at the focal point.

#### **6. Label-free sorting of nano-bioparticles**

OPtIC nanopore device enables both size- and refractive-index based separation of nano-bioparticles by utilizing a delicate balance of counteracting forces, i.e., **Fs**, **Fd**, **Ftp** and *W* (gravitational force). Since these forces act along the optical axis within the focal point region, selective particle elution can be readily achieved by adjusting the net force **Fnet** = **Fs** + **Fd** + **Ftp** + *W* [11]. We calculated **Fnet** for varying spherical bioparticles with a mass density of 1.05 g/cm<sup>3</sup> and refractive index of 1.55. The direction of **Fnet** as a function of distance from the microlens (0 ≤ *z* ≤ 6 μm) and particle diameter (100 nm ≤ *d* ≤ 1.0 μm) is shown in **Figure 6a** and **b**. In both cases, incident light power is 20 mW and wavelength 633 nm, and the fluidic flow velocities at the focal point *v*(*z* = *f*D) are 1.3 μm/s and 3.0 μm/s. The red and blue shaded regions in **Figure 6a** and **b** correspond to the positive (*F*<sup>s</sup> + *F*tp > *F*<sup>d</sup> + *W*, blue shaded region) and negative (*F*<sup>s</sup> + *F*tp < *F*<sup>d</sup> + *W*, red shaded region) net forces, respectively.

*F*net is always negative for *d* ≤ 200 nm, as indicated by the white dashed line on the left in **Figure 6a**. Nano-bioparticles smaller than this threshold diameter, *d* < *dth* = 200 nm can travel a path along the optical axis and pass through the nanopore opening towards the outlet port. Particles with diameters larger than *dth* experience stronger optical scattering and thermo-plasmonic drag forces (*F*<sup>s</sup> + *F*tp) relative to the fluidic drag and gravitational forces (*F*<sup>d</sup> + *W*). Therefore, they are retained in the top chamber. Hence, under the above-stated flow and illumination conditions, small particles (*d* ≤ 200 nm) get separated from relatively large bioparticles. The OPtIC nanopore device offers selective particle fractionation by adjusting either the incident light power or bulk fluidic flow rate. At a fixed incident light power of 20 mW, when *v*(*z* = *fD*) is increased to 3.0 μm/s, the threshold particle diameter *dth* is shifted to 350 nm (**Figure 6b**). By further tuning, relative contributions of acting forces can be tailored for selective separation of nanobioparticles with diameters up to 500 nm, as larger particles cannot physically pass through the nanopore opening (*d*<sup>c</sup> = 500 nm).

*Plasmonic Nanopores: Optofluidic Separation of Nano-Bioparticles via Negative Depletion DOI: http://dx.doi.org/10.5772/intechopen.96475*

#### **Figure 6.**

*Label-free selective sorting of nanoparticles:* F*net as a function of particle diameter and position along the optical axis is shown for a fluidic flow rate of (a) 1.3 μm/s and (b) 3.0 μm/s at the focal point* v*(*z *=* f*D). A monochromatic light source (633 nm) with 20 mW power is assumed. (c) Forces acting on a fixed diameter (*d *= 200 nm) nanoparticle at the focal point as a function of particle refractive index (*n*e) is shown for a fluidic flow velocity of (c)* v*(*z *=* f*D) = 1.9 μm/s under 100 mW illumination. (d) Calculations are repeated for a fluidic flow velocity of* v*(*z *=* f*D) = 0.95 μm/s under 20 mW illumination. The dashed vertical lines in (a) and (b) represent threshold particle diameters, while those in (c) and (d) denote threshold particle refractive indices* n*e. The lines in (c) and (d) are first-order polynomial fits to the numerical data. Copyright 2020 nature publishing group adapted with permission [11].*

Size-based separation is not adequate when similar size bioparticles of different origins need to be separated. As indicated in Eq. (1), the optical radiation force acting on particles is a function of both particle radius and refractive index. In this respect, particles comparable dimensions can be separated based on their refractive indices [4, 7]. In general, refractive index is intimately linked to the internal structure and chemical makeup of the nano-bioparticles [e.g., exosomes, viruses]. A recent research study has shown that implementation of optical chromatography based on refractive index differences yield successful differentiation of cells with single gene modifications [3]. We calculated forces (*F*s, *F*tp, *F*d, *W*) acting on the nanoparticles (*d* = 200 nm) as a function of refractive index (1.33 < *n*<sup>e</sup> < 1.6) at the focal point (*z* = *f*<sup>D</sup> = 5.32 μm). A fluidic flow rate of *v*(*f*D) = 1.9 μm/s and 100 mW monochromatic light illumination at 633 nm is assumed. Solid red and black curves in **Figure 6c** depicts optical scattering *F*<sup>s</sup> and the net drag (i.e., *F*nd = *F*<sup>d</sup> - *F*tp) forces, respectively. The dashed curves represent contribution of the gravitational force (*W*). In our calculations, *n*<sup>e</sup> is varied from *n*water = 1.33 to *n*ps = 1.6 (polystyrene beads). As depicted in **Figure 6c**, at the flow rate (1.9 μm/s), the magnitude of *F*<sup>s</sup> increases with *n*<sup>e</sup> and *F*<sup>s</sup> balances *F*nd when *n*<sup>e</sup> = 1.46 (indicated by the vertical dashed line). For smaller *n*e, drag force originating from the primary fluidic flow dominates the opposing forces (*F*<sup>s</sup> + *F*tp). Thus, the OPtIC microlens can be

employed for selective separation of nano-bioparticles with a threshold of *n*<sup>e</sup> = 1.46, corresponding to the refractive index of phospholipids and proteins.

It is known that exosomes (nanovesicles composed mostly of water enclosed by a thin phospholipid membrane) have lower refractive indices *n*<sup>e</sup> in the range of 1.37–1.39 [36–38], which is closer to *n*<sup>e</sup> = 1.33 of water. In contrast, virions are tight assemblies of nucleic acids, proteins and lipids with higher *n*<sup>e</sup> around 1.48 [39]. For an exosome-like bioparticle (*d* = 200 nm) with *n*<sup>e</sup> 1.38, *F*<sup>s</sup> can be as small as 4 aN, which is two orders of magnitude smaller than the corresponding value for *n*<sup>e</sup> = 1.48 (400 aN) for a similar size virion. Hence, our OPtIC nanopore device can selectively separate exosomes from similar size virions with high efficiencies.

The threshold *n*<sup>e</sup> can be readily tuned, as in the case of particles size, by adjusting the fluidic flow velocity and/or light power. **Figure 6d** shows that the threshold refractive index can be tuned to *n*<sup>e</sup> = 1.54 when the fluidic flow rate is halved to 0.95 μm/s and light power is reduced to 20 mW. Since OPtIC nanopore devices can be operated by directly incident light using an objective-free focusing mechanism, a number of them can be implemented on a planar chip. One can combine multiple OPtIC devices to achieve multi-stage sequential fractionation of nano-bioparticles to realize highly specific size and refractive index-based separation.

#### **7. Radial lining-up of nano-bioparticles**

A major limitation of conventional OC is the difficulty of aligning fluidic flow against a lightly focused Gaussian beam in a precise manner [6]. Our OPtIC nanopore device employs a self-collimation mechanism effortlessly aligning fluidic flow along the optical axis of the microlens. This self-collimation capability, liningup particles against the scattering force, is demonstrated in **Figure 7**. We calculated radial components of the optical gradient (*F***g-r**), fluidic drag (*F***d-r**) and thermoplasmonic (*F***tp-r**) forces at the focal point *z* = *f*D. We analyzed 200 nm (**Figure 7a**) and 600 nm (**Figure 7b**) diameter particles, assuming a fluidic flow velocity of *v* (*z* = *f*D) = 1.3 μm/s at the focal point and a 20 mW monochromatic (633 nm wavelength) light source. As shown in **Figure 7a**, these radial forces act like a

#### **Figure 7.**

*Self-collimating radial forces along the optical axis: The radial components of Fg, Fd and Ftp in the direction perpendicular to the optical axis is shown for (a) 200 nm and (b) 600 nm particles. The operation conditions are 20 mW light power at 633 nm and a fluidic flow velocity 1.3 μm/s at the focal point. Copyright 2020 nature publishing group adapted with permission [11].*

#### *Plasmonic Nanopores: Optofluidic Separation of Nano-Bioparticles via Negative Depletion DOI: http://dx.doi.org/10.5772/intechopen.96475*

restoring mechanism (*F* ∝ *x*) within 1 μm away from the optical axis. Nanobioparticles that deviate from the optical axis are pushed back towards it (*x* = 0) by these radial restoring forces. This leads to minimal spatial dispersion of the nanobioparticles in the radial direction. As shown in **Figure 7b**, larger particles (d = 600 nm) experience at least an order of magnitude larger optical gradient forces. This enables precise alignment of larger particles against the optical scattering force at the focal point, a critical requirement for selective rejection of particles above a threshold diameter.

As shown in **Figure 7**, nanoparticles in the focal are mainly retained along the optical axis by the optical gradient force *F*g-r, which is significantly stronger than *F*d-r. Optical gradient force *F*g-r is relatively stable and readily tuned using light intensity. Hence, self-collimation mechanism employed by our OPtIC nanopore device is robust against fluctuations in the fluidic flow rate.

#### **8. Conclusion**

In this chapter, we reviewed a facile optofluidic nanopore platform for the purposes of optical chromatography of nano-bioparticles based on their size and/or refractive index (chemical composition). Consisting of a finite-size periodic plasmonic nanohole array on a suspended membrane, this OPtIC nanopore device with an enlarged central aperture facilitates precise alignment of optical scattering, thermo-plasmonic drag, and fluidic drag forces against each other for the purposes of OC. Its self-collimation mechanism eliminates the need for sophisticated and bulky optic components (e.g., lasers, microscope objectives, multi-axis stages, etc.) that are commonly used in conventional OC techniques. Furthermore, our plasmonic microlens opens the door to use of incoherent light source, such as LEDs, for the purposes of OC by readily focusing collimated broadband light into a tight spot. This lensing mechanism provides a robust separation capability that is insensitive to structural variations of the central nanopore. We demonstrated size-based selective sorting of nano-bioparticles, such as exosomes, with a tunable threshold diameter using incident light power or fluidic flow rate. In addition, refractiveindex based separation of identical size nano-bioparticles are shown. Similar to sizebased separation, the refractive-index (material composition) based separation mechanism is readily tunable through incident light power and fluidic flow rate.

#### **Acknowledgements**

A. A. Yanik acknowledges support from National Science Foundation [ECCS-1611290], Gordon and Betty Moore Foundation [GBMF #5263.06], and National Science Foundation CAREER Award [ECCS- 1847733]. X. Zhu was supported by a University of California Chancellor's Dissertation Year Fellowship. We acknowledge Dr. Tom Yuzvinsky for assistance with device fabrication and the W.M. Keck Center for Nanoscale Optofluidics for use of the FEI Quanta 3D.

#### **Conflict of interest**

The authors declare no conflict of interest.

*Nanopores*

#### **Author details**

Xiangchao Zhu1 , Ahmet Cicek<sup>2</sup> , Yixiang Li<sup>1</sup> and Ahmet Ali Yanik1,3\*

1 Department of Electrical Engineering, Jack Baskin School of Engineering, University of California Santa Cruz, Santa Cruz, CA, USA

2 Department of Nanoscience and Nanotechnology, Faculty of Arts and Science, Burdur Mehmet Akif Ersoy University, Burdur, Turkey

3 California Institute for Quantitative Biosciences (QB3), University of California Santa Cruz, Santa Cruz, CA, USA

\*Address all correspondence to: yanik@ucsc.edu

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Plasmonic Nanopores: Optofluidic Separation of Nano-Bioparticles via Negative Depletion DOI: http://dx.doi.org/10.5772/intechopen.96475*

#### **References**

[1] Imasaka T, Kawabata Y, Kaneta T, Ishidzu Y. Optical chromatography. Analytical Chemistry. 1995;67:1763– 1765. DOI: 10.1021/ac00107a003

[2] Hebert CG, Terray A, Hart SJ. Toward Label-Free Optical Fractionation of Blood-Optical Force Measurements of Blood Cells. Analytical Chemistry. 2011;83: 5666–5672. DOI: 10.1021/ac200834u

[3] Ma Z, Burg KJL, Wei Y, Yuan X-C, Peng X, Gao BZ. Laser-guidance based detection of cells with single-gene modification. Applied Physics Letters. 2008;92:213902. DOI: 10.1063/ 1.2938020

[4] Hart SJ, Terray A, Leski TA, Arnold J, Stroud R. Discovery of a Significant Optical Chromatographic Difference between Spores of *Bacillus anthracis* and Its Close Relative, *Bacillus thuringiensis*. Analytical Chemistry. 2006;78:3221–3225. DOI: 10.1021/ ac052221z

[5] Kaneta T, Ishidzu Y, Mishima N, Imasaka T. Theory of optical chromatography. Analytical Chemistry. 1997;69:2701–2710. DOI: 10.1021/ ac970079z

[6] Makihara J, Kaneta T, Imasaka T. Optical chromatography: Size determination by eluting particles. Talanta. 1999;48:551–557. DOI: 10.1016/ S0039-9140(98)00272-0

[7] Hart SJ, Terray AV. Refractiveindex-driven separation of colloidal polymer particles using optical chromatography. Applied Physics Letters. 2003;83:5316–5318. DOI: 10.1063/1.1635984

[8] Taylor JD, Terray A, Hart SJ. Analytical particle measurements in an optical microflume. Analytica Chimica Acta. 2010;670:78–83. DOI: 10.1016/j. aca.2010.04.062

[9] Terray A, Hebert CG, Hart SJ. Optical chromatographic sample separation of hydrodynamically focused mixtures. Biomicrofluidics. 2014;8: 064102. DOI: 10.1063/1.4901824

[10] Terray A, Taylor JD, Hart SJ. Cascade optical chromatography for sample fractionation. Biomicrofluidics. 2009;3:044106. DOI: 10.1063/1.3262415

[11] Zhu X, Cicek A, Li Y, Yanik AA. Plasmofluidic microlenses for label-free optical sorting of exosomes. Sci Rep. 2019;9:8593. DOI:10.1038/ s41598-019-44801-3

[12] Verslegers L, Catrysse PB, Yu Z, White JS, Barnard ES, Brongersma ML, Fan S. Planar lenses based on nanoscale slit arrays in a metallic film. Nano Letters. 2008;9:235–238. DOI: 10.1021/ nl802830y

[13] Gao H, Hyun JK, Lee MH, Yang JC, Lauhon LJ, Odom TW. Broadband plasmonic microlenses based on patches of nanoholes. Nano Letters. 201;10: 4111–4116. DOI: 10.1021/nl1022892

[14] Ashkin A. Acceleration and trapping of particles by radiation pressure. Physical Review Letters. 1970;24:156– 159. DOI: 10.1103/PhysRevLett.24.156

[15] Ashkin A, Dziedzic J. Optical trapping and manipulation of viruses and bacteria. Science. 1987;235:1517– 1520. DOI: 10.1126/science.3547653

[16] Ebbesen TW, Lezec HJ, Ghaemi HF, Thio T, Wolff PA. Extraordinary optical transmission through sub-wavelength hole arrays. Nature. 1998;391:667–669. DOI: 10.1038/35570

[17] Martin-Moreno L, Garcia-Vidal FJ, Lezec HJ, Pellerin KM, Thio T, Pendry JB, Ebbesen TW. Theory of extraordinary optical transmission through subwavelength hole arrays.

Physical Review Letters. 2001;86:1114– 1117. DOI: 10.1103/PhysRevLett.86.1114

[18] Genet C, Ebbesen TW. Light in tiny holes. Nature. 2007;445:39–46. DOI: 10.1038/nature05350

[19] Yanik AA, Wang X, Erramilli S, Hong MK, Altug H. Extraordinary midinfrared transmission of rectangular coaxial nanoaperture arrays. Applied Physics Letters. 2008;93:081104. DOI: 10.1063/1.2973165

[20] Yanik AA, Huang M, Artar A, Chang T-Y, Altug H. Integrated nanoplasmonic-nanofluidic biosensors with targeted delivery of analytes. Applied Physics Letters. 2010;96: 021101. DOI: 10.1063/1.3290633

[21] Huang M, Yanik AA, Chang T-Y, Altug H. Sub-wavelength nanofluidics in photonic crystal sensors. Optics Express. 2009;17:24224–24233. DOI: 10.1364/OE.17.024224

[22] Yanik AA, Cetin AE, Huang M, Artar A, Mousavi SH, Khanikaev A, Connor JH, Shvets G, Altug H. Seeing protein monolayers with naked eye through plasmonic Fano resonances. Proceedings of the National Academy of Sciences of the United States of America. 2011;108:11784–11789. DOI: 10.1073/pnas.1101910108

[23] Oh KW, Lee K, Ahn B, Furlani EP. Design of pressure-driven microfluidic networks using electric circuit analogy. Lab on a Chip. 2012;12:515–545. DOI: 10.1039/C2LC20799K

[24] Okamoto K, Kawata S. Radiation force exerted on subwavelength particles near a nanoaperture. Physical Review Letters. 1999; 83:4534–4537. DOI: 10.1103/PhysRevLett.83.4534

[25] Wang X, Wang X-B, Gascoyne PR. General expressions for dielectrophoretic force and electrorotational torque derived using the Maxwell stress tensor

method. Journal of Electrostatics. 1997; 39:277–295. DOI: 10.1016/S0304-3886 (97)00126-5

[26] Dennis MR, Zheludev NI, de Abajo FJG. The plasmon Talbot effect. Optics Express. 2007;15:9692–9700. DOI: 10.1364/OE.15.009692

[27] Ghaemi HF, Thio T, Grupp DE, Ebbesen TW, Lezec HJ. Surface plasmons enhance optical transmission through subwavelength holes. Physical Review B. 1998;58:6779–6782. DOI: 10.1103/PhysRevB.58.6779

[28] Ruffieux P, Scharf T, Herzig HP, Völkel R, Weible KJ. On the chromatic aberration of microlenses. Optics Express. 2006;14:4687–4694. DOI: 10.1364/OE.14.004687

[29] Saxena S, Chaudhary RP, Singh A, Awasthi S, Shukla S. Plasmonic Micro Lens for Extraordinary Transmission of Broadband Light. Scientific Reports 2014;4:5586. DOI: 10.1038/srep05586

[30] Baffou G, Girard C, Quidant R. Mapping Heat Origin in Plasmonic Structures. Physical Review Letters. 2010;104:136805. DOI: 10.1103/ PhysRevLett.104.136805

[31] Donner JS, Baffou G, McCloskey D, Quidant R. Plasmon-Assisted Optofluidics. ACS Nano. 2011;5:5457– 5462. DOI: 10.1021/nn200590u

[32] Kim J. Joining plasmonics with microfluidics: from convenience to inevitability. Lab on a Chip. 2012;12: 3611–3623. DOI: 10.1039/C2LC40498B

[33] Roxworthy BJ, Bhuiya AM, Vanka SP, Toussaint Jr KC. Understanding and controlling plasmon-induced convection. Nature Communications. 2014;5:3173, DOI: 10.1038/ncomms4173

[34] Jackson JD. Classical Electrodynamics. 3rd ed. New York: *Plasmonic Nanopores: Optofluidic Separation of Nano-Bioparticles via Negative Depletion DOI: http://dx.doi.org/10.5772/intechopen.96475*

John Wiley and Sons; 1999. 832 pp. ISBN: 978–0–471-30932-1

[35] Ndukaife JC, Kildishev AV, Agwu Nnanna AG, Shalaev VM, Wereley ST, Boltasseva A. Long-range and rapid transport of individual nano-objects by a hybrid electrothermoplasmonic nanotweezer. Nature Nanotechnology. 2016;11:53–59. DOI:10.1038/ nnano.2015.248

[36] van der Pol E, de Rond L, Coumans FAW, Gool EL, Böing AN, Sturk A, Nieuwland R, van Leeuwen TG. Absolute sizing and labelfree identification of extracellular vesicles by flow cytometry. Nanomedicine. 2018;14:801–810. DOI: 10.1016/j.nano.2017.12.012

[37] van der Pol E, Coumans F, Varga Z, Krumrey M, Nieuwland R. Innovation in detection of microparticles and exosomes. Journal of Thrombosis and Haemostasis. 2013;11:36–45. DOI: 10.1111/jth.12254

[38] Gardiner C, Shaw M, Hole P, Smith J, Tannetta D, Redman CW, Sargent IL. Measurement of refractive index by nanoparticle tracking analysis reveals heterogeneity in extracellular vesicles. Journal of Extracellular Vesicles. 2014;3:25361, DOI: 10.3402/ jev.v3.25361

[39] Wang S, Shan X, Patel U, Huang X, Lu J, Li J, Tao N. Label-free imaging, detection, and mass measurement of single viruses by surface plasmon resonance. Proceedings of the National Academy of Sciences of the United States of America. 2010;107:16028– 16032. DOI: 10.1073/pnas.1005264107

#### **Chapter 5**
