**Kinetics of Nanomaterials**

[17] Alberico E, Lennox AJJ, Vogt LK, Jiao H, Baumann W, Drexler H-J, Nielsen M, Spannenberg A, Checinski MP, Junge H, Beller M. Unravelling the mechanism of basic aqueous methanol dehydrogenation catalyzed by Ru-PNP pincer complexes. Journal of the American Chemical Society. 2016;**138**(45):14890-14904. DOI: 10.1021/jacs.6b05692

[18] Friedrich A, Drees M, Schmedt auf der Günne J, Schneider S. Highly stereoselective proton/hydride exchange: Assistance of hydrogen bonding for the heterolytic splitting of H<sup>2</sup>

[19] Monney A, Barsch E, Sponholz P, Junge H, Ludwig R, Beller M. Base-free hydrogen generation from methanol using a bi-catalytic system. Chemical Communications. 2014;

[20] Rodríguez-Lugo RE, Trincado M, Vogt M, Tewes F, Santiso-Quinones G, Grützmacher H. A homogeneous transition metal complex for clean hydrogen production from methanol–water mixtures. Nature Chemistry. 2013;**5**(4):342-347. DOI: 10.1038/nchem.1595

[21] Hu P, Diskin-Posner Y, Ben-David Y, Milstein D. Reusable homogeneous catalytic system for hydrogen production from methanol and water. ACS Catalysis. 2014;**4**(8):2649-

[22] Milstein D. Discovery of environmentally benign catalytic reactions of alcohols catalyzed by pyridine-based pincer Ru complexes, based on metal-ligand cooperation. Topics in

[23] Van de Watering F, Lutz M, Dzik W, de Bruin B, Reek JNH. Reactivity of a ruthenium-carbonyl complex in the methanol dehydrogenation reaction. ChemCatChem.

[24] Alberico E, Sponholz P, Cordes C, Nielsen M, Drexler H-J, Baumann W, Junge H, Beller M. Selective hydrogen production from methanol with a defined iron pincer catalyst under mild conditions. Angewandte Chemie, International Edition. 2013;**52**(52):14162-14166.

[25] Andérez-Fernández M, Vogt LK, Fischer S, Zhou W, Jiao H, Garbe M, Elangovan S, Junge K, Junge H, Ludwig R, Beller M. A stable manganese pincer catalyst for the selective dehydrogenation of methanol. Angewandte Chemie, International Edition.

[26] Fujita K, Kawahara R, Aikawa T, Yamaguchi R. Hydrogen production from a methanolwater solution catalyzed by an anionic iridium complex bearing a functional bipyridonate ligand under weakly basic conditions. Angewandte Chemie, International Edition.

[27] Campos J, Sharninghausen LS, Manas MG, Crabtree RH. Methanol dehydrogenation by iridium N-heterocyclic carbene complexes. Inorganic Chemistry. 2015;**54**(11):5079-5084.

[28] Prichatz C, Alberico E, Baumann W, Junge H, Beller M.Iridium-PNP pincer complexes for methanol dehydrogenation at low base concentration. ChemCatChem. 2017;**9**(11):1891-

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.

**Chapter 7**

Provisional chapter

**Oxidation of Glycerol to Lactic Acid by Gold on**

Thabang A. Ntho, Pumeza Gqogqa and

Thabang A. Ntho, Pumeza Gqogqa and

http://dx.doi.org/10.5772/intechopen.70485

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

Alumina: A Kinetic and DFT Case Study

James L. Aluha

James L. Aluha

Abstract

kinetics, DFT

1. Introduction

**Acidified Alumina: A Kinetic and DFT Case Study**

Oxidation of Glycerol to Lactic Acid by Gold on Acidified

DOI: 10.5772/intechopen.70485

The aim of this chapter is to present proposed kinetic and density functional theory (DFT) models for the selective oxidation of glycerol to various hydroxy-acids over an acidified Au/γ-Al2O3 catalyst. Glycerol oxidation over gold-based catalysts to valueadded chemicals continues to attract attention worldwide. Both the kinetics and theoretical mechanisms of this reaction have been reported in the past. However, some of the reported kinetic data was possibly collected under mass transfer limitations. In this case study we demonstrate that if mass transfer is eliminated, a pseudo zero-order model can be fitted to the experimental data with a high degree of correlation. Furthermore, we propose a plausible mechanism of pyruvaldehyde (PA) isomerisation to lactic acid (LAC) over supported molybdenum Lewis acid sites as investigated with density functional theory (DFT) approach. A proposed DFT model suggested that the rate-limiting step in the isomerisation of PA to LAC, catalysed by a Mo Lewis acid-site, could be the dissociation of a proton from an adsorbed water molecule – the protonation step.

Keywords: gold, catalyst, alumina, support-acidity, glycerol-oxidation, lactic acid,

Lactic acid (LAC), as noted by Wee et al. [1], is one of the most valuable chemicals in industry today and is widely used in the food, cosmetic, pharmaceutical, and chemical industries. In the food industry, for example, it may be used as a preservative, an acidulant, or for flavouring, while in the textile, pharmaceutical and chemical industry it is used as a raw material for the production of lactate ester, propylene glycol, 2,3-pentanedione, propanoic acid, acrylic acid,

> © The Author(s). Licensee InTech. 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 eproduction in any medium, provided the original work is properly cited.

© 2018 The Author(s). Licensee InTech. 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.

Provisional chapter

### **Oxidation of Glycerol to Lactic Acid by Gold on Acidified Alumina: A Kinetic and DFT Case Study** Oxidation of Glycerol to Lactic Acid by Gold on Acidified

DOI: 10.5772/intechopen.70485

Thabang A. Ntho, Pumeza Gqogqa and James L. Aluha Thabang A. Ntho, Pumeza Gqogqa and

Additional information is available at the end of the chapter James L. Aluha Additional information is available at the end of the chapter

Alumina: A Kinetic and DFT Case Study

http://dx.doi.org/10.5772/intechopen.70485

#### Abstract

The aim of this chapter is to present proposed kinetic and density functional theory (DFT) models for the selective oxidation of glycerol to various hydroxy-acids over an acidified Au/γ-Al2O3 catalyst. Glycerol oxidation over gold-based catalysts to valueadded chemicals continues to attract attention worldwide. Both the kinetics and theoretical mechanisms of this reaction have been reported in the past. However, some of the reported kinetic data was possibly collected under mass transfer limitations. In this case study we demonstrate that if mass transfer is eliminated, a pseudo zero-order model can be fitted to the experimental data with a high degree of correlation. Furthermore, we propose a plausible mechanism of pyruvaldehyde (PA) isomerisation to lactic acid (LAC) over supported molybdenum Lewis acid sites as investigated with density functional theory (DFT) approach. A proposed DFT model suggested that the rate-limiting step in the isomerisation of PA to LAC, catalysed by a Mo Lewis acid-site, could be the dissociation of a proton from an adsorbed water molecule – the protonation step.

Keywords: gold, catalyst, alumina, support-acidity, glycerol-oxidation, lactic acid, kinetics, DFT

### 1. Introduction

Lactic acid (LAC), as noted by Wee et al. [1], is one of the most valuable chemicals in industry today and is widely used in the food, cosmetic, pharmaceutical, and chemical industries. In the food industry, for example, it may be used as a preservative, an acidulant, or for flavouring, while in the textile, pharmaceutical and chemical industry it is used as a raw material for the production of lactate ester, propylene glycol, 2,3-pentanedione, propanoic acid, acrylic acid,

© 2018 The Author(s). Licensee InTech. 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.

© The Author(s). Licensee InTech. 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 eproduction in any medium, provided the original work is properly cited.

acetaldehyde and dilactide. In fact, LAC continues to receive increased attention for its potential use as a monomer in the production of biodegradable poly lactic acid. It can be produced by either biotechnological fermentation or chemical synthesis, but the former route is receiving considerable interest due to environmental concerns and the limited nature of petrochemical feedstocks. However, fermentation is inherently a slow process. An alternative route to LAC is by processing a 'renewable' resource such as glycerol by means of heterogeneous catalysis. Haruta [2] has reported that gold with particle diameters below 10 nm are surprisingly active for many reactions, such as CO oxidation and propylene epoxidation.

thereby anchoring it to the alumina support. Gold was loaded onto the supports as described

Oxidation of Glycerol to Lactic Acid by Gold on Acidified Alumina: A Kinetic and DFT Case Study

http://dx.doi.org/10.5772/intechopen.70485

115

Catalyst testing for glycerol oxidation was performed at 90C (with temperature optimised at 60 and 90C) and oxygen pressure kept at 8.5 bar using a glass-lined Parr reactor (model 4563), in batch mode under agitation with stirrer speed kept constant at 1000 rpm, using 0.5 g of catalyst for 10 g of glycerol dissolved in 90 g of de-ionized water. To this solution, NaOH pellets were added such that the mole ratio of glycerol to the base was always 1:2. In-depth

HRTEM analysis was conducted on a field emission microscope, the JEM2100F electron microscope from JEOL Ltd., fitted with energy-dispersive X-ray spectroscopy (EDX), wavelength dispersive spectroscopy (WDS) and electron beam backscattered diffraction (EBSD) operating on Oxford Instruments software. The instrument was operated at an accelerating electron beam of 200 kV and images captured in the bright field mode. The Nano-measurer 1.2 'Scion

The acidity of the materials was qualitatively measured by temperature programmed desorption (TPD) of NH3 on a micromeritics automated catalyst characterisation system: model AutoChem II 2920 chemisorption analyser. NH3-TPD studies were performed by loading 0.25 g catalyst in a U-tube reactor and cleaning the sample in a gas stream of helium at 120C for an hour at a ramping rate of 10C min<sup>1</sup> to remove moisture and other adsorbed species. A mixture of 10% NH3 balanced in He was flushed over the sample isothermally at 120C. After adsorption was achieved at 120C, the NH3 desorption measurements ensued at 120C using the thermoconductivity detector (TCD) and data collected up to 500C at a ramping rate of 15C min<sup>1</sup>

The regression analysis of the experimental data was performed by use of Easy Regression Analysis (ERA 3.0) software [15, 16]. The software uses the sum of the square of residual deviations as the objective function. All the kinetic parameters were estimated at a 95%

Unless otherwise stated, all electronic energies of reactants, products and transition states were determined by density functional theory (DFT) using the DMol<sup>3</sup> code [17, 18] within the

confidence limit using a modified adaptive random search algorithm.

.

elsewhere [14].

2.3. Catalyst testing conditions

details are provided elsewhere [14].

2.4.1. High resolution transmission electron microscopy (HRTEM)

Imager' software was used for particle size analysis.

2.4.2. Temperature programmed desorption (TPD)

2.5. Models and computational methods

2.5.1. Kinetic parameter estimation

2.5.2. DFT methodology

2.4. Catalyst characterisation

Many aspects of glycerol oxidation by Au have been studied. Ketchie et al. [3] have looked at the effect of Au particle size, particularly on supports such as carbon [4] and titania [5], while Wang et al. [6] have examined the effect of particle shape, and Villa et al. [7] have investigated the role of stabilizers in gold sols as catalysts in the liquid-phase oxidation of glycerol. In addition, Demirel et al. [8] have probed the promotional effect of Pt on Au/C catalysts, and Royker et al. [9] have investigated the promotional effect of Pt on Au/Al2O3 catalysts, while other authors have studied the effect of base in the reaction. For example, Chornaja et al. [10] examined the oxidation of glycerol to glyceric acid using Pd catalysts that worked in alkaline media, and Ketchie et al. [5] reported the promotional effect of hydroxyl ions over Au catalysts, while Carretin et al. [11] have analysed the effect of base as a reaction initiator, proving that for Au/C catalysts, the presence of OH was mandatory for any meaningful glycerol oxidation to occur. However, there was seemingly very limited study on the effect of surface acidity for this reaction using alumina supports, for which this work is dedicated.

### 2. Experimental procedures

#### 2.1. Chemical reagents and materials

Commercial γ-Al2O3 support (denoted as Degussa 2010, BET specific surface area of 260 m2 g<sup>1</sup> ), ammonium molybdate (NH4)6Mo7O244H2O from Associated Chemical Enterprises (ACE), chloroauric acid HAuCl43H2O from Rand Refinery (South Africa), NaOH (98%) and nitric acid (65%) from ACE, and glycerol (99.5%) from Rochelle Chemicals were used.

### 2.2. Preparation of MoO3/γ-Al2O3 support

A mass of 4.6 g of γ-Al2O3 support with a measured BET specific surface area of 245 m2 g<sup>1</sup> was weighed and placed in a beaker. About 100 ml solution of 0.1 M ammonium molybdate salt was measured, enough to form MoO3 monolayer coverage at surface concentration of 5 atoms of metal nm<sup>2</sup> or 0.2 nm2 atom<sup>1</sup> according to Stobbe-Kreemers et al. [12] and Raubenheimer and Cronje [13]. The pH of the solution was then adjusted to a value below 1 by addition of dilute (0.25 M) HNO3 acid, with agitation to ensure equal distribution of the acid to a stable pH. The support was then added to the ammonium molybdate solution and left to stand for 8 h, after which, it was filtered and left to oven dry in air at 120C for 16 h. The dried catalyst precursor was then calcined in air at a flow rate of 300 SCCM at 500C for 4 h to decompose any residual ammonium and nitrate ions from the support, effectively reducing the molybdate ion to MoO3,

thereby anchoring it to the alumina support. Gold was loaded onto the supports as described elsewhere [14].

### 2.3. Catalyst testing conditions

acetaldehyde and dilactide. In fact, LAC continues to receive increased attention for its potential use as a monomer in the production of biodegradable poly lactic acid. It can be produced by either biotechnological fermentation or chemical synthesis, but the former route is receiving considerable interest due to environmental concerns and the limited nature of petrochemical feedstocks. However, fermentation is inherently a slow process. An alternative route to LAC is by processing a 'renewable' resource such as glycerol by means of heterogeneous catalysis. Haruta [2] has reported that gold with particle diameters below 10 nm are surprisingly active

Many aspects of glycerol oxidation by Au have been studied. Ketchie et al. [3] have looked at the effect of Au particle size, particularly on supports such as carbon [4] and titania [5], while Wang et al. [6] have examined the effect of particle shape, and Villa et al. [7] have investigated the role of stabilizers in gold sols as catalysts in the liquid-phase oxidation of glycerol. In addition, Demirel et al. [8] have probed the promotional effect of Pt on Au/C catalysts, and Royker et al. [9] have investigated the promotional effect of Pt on Au/Al2O3 catalysts, while other authors have studied the effect of base in the reaction. For example, Chornaja et al. [10] examined the oxidation of glycerol to glyceric acid using Pd catalysts that worked in alkaline media, and Ketchie et al. [5] reported the promotional effect of hydroxyl ions over Au catalysts, while Carretin et al. [11] have analysed the effect of base as a reaction initiator, proving that for Au/C catalysts, the presence of OH was mandatory for any meaningful glycerol oxidation to occur. However, there was seemingly very limited study on the effect of surface

acidity for this reaction using alumina supports, for which this work is dedicated.

(65%) from ACE, and glycerol (99.5%) from Rochelle Chemicals were used.

Commercial γ-Al2O3 support (denoted as Degussa 2010, BET specific surface area of 260 m2 g<sup>1</sup>

ammonium molybdate (NH4)6Mo7O244H2O from Associated Chemical Enterprises (ACE), chloroauric acid HAuCl43H2O from Rand Refinery (South Africa), NaOH (98%) and nitric acid

A mass of 4.6 g of γ-Al2O3 support with a measured BET specific surface area of 245 m2 g<sup>1</sup> was weighed and placed in a beaker. About 100 ml solution of 0.1 M ammonium molybdate salt was measured, enough to form MoO3 monolayer coverage at surface concentration of 5 atoms of metal nm<sup>2</sup> or 0.2 nm2 atom<sup>1</sup> according to Stobbe-Kreemers et al. [12] and Raubenheimer and Cronje [13]. The pH of the solution was then adjusted to a value below 1 by addition of dilute (0.25 M) HNO3 acid, with agitation to ensure equal distribution of the acid to a stable pH. The support was then added to the ammonium molybdate solution and left to stand for 8 h, after which, it was filtered and left to oven dry in air at 120C for 16 h. The dried catalyst precursor was then calcined in air at a flow rate of 300 SCCM at 500C for 4 h to decompose any residual ammonium and nitrate ions from the support, effectively reducing the molybdate ion to MoO3,

),

2. Experimental procedures

114 Advanced Chemical Kinetics

2.1. Chemical reagents and materials

2.2. Preparation of MoO3/γ-Al2O3 support

for many reactions, such as CO oxidation and propylene epoxidation.

Catalyst testing for glycerol oxidation was performed at 90C (with temperature optimised at 60 and 90C) and oxygen pressure kept at 8.5 bar using a glass-lined Parr reactor (model 4563), in batch mode under agitation with stirrer speed kept constant at 1000 rpm, using 0.5 g of catalyst for 10 g of glycerol dissolved in 90 g of de-ionized water. To this solution, NaOH pellets were added such that the mole ratio of glycerol to the base was always 1:2. In-depth details are provided elsewhere [14].

### 2.4. Catalyst characterisation

#### 2.4.1. High resolution transmission electron microscopy (HRTEM)

HRTEM analysis was conducted on a field emission microscope, the JEM2100F electron microscope from JEOL Ltd., fitted with energy-dispersive X-ray spectroscopy (EDX), wavelength dispersive spectroscopy (WDS) and electron beam backscattered diffraction (EBSD) operating on Oxford Instruments software. The instrument was operated at an accelerating electron beam of 200 kV and images captured in the bright field mode. The Nano-measurer 1.2 'Scion Imager' software was used for particle size analysis.

### 2.4.2. Temperature programmed desorption (TPD)

The acidity of the materials was qualitatively measured by temperature programmed desorption (TPD) of NH3 on a micromeritics automated catalyst characterisation system: model AutoChem II 2920 chemisorption analyser. NH3-TPD studies were performed by loading 0.25 g catalyst in a U-tube reactor and cleaning the sample in a gas stream of helium at 120C for an hour at a ramping rate of 10C min<sup>1</sup> to remove moisture and other adsorbed species. A mixture of 10% NH3 balanced in He was flushed over the sample isothermally at 120C. After adsorption was achieved at 120C, the NH3 desorption measurements ensued at 120C using the thermoconductivity detector (TCD) and data collected up to 500C at a ramping rate of 15C min<sup>1</sup> .

#### 2.5. Models and computational methods

#### 2.5.1. Kinetic parameter estimation

The regression analysis of the experimental data was performed by use of Easy Regression Analysis (ERA 3.0) software [15, 16]. The software uses the sum of the square of residual deviations as the objective function. All the kinetic parameters were estimated at a 95% confidence limit using a modified adaptive random search algorithm.

#### 2.5.2. DFT methodology

Unless otherwise stated, all electronic energies of reactants, products and transition states were determined by density functional theory (DFT) using the DMol<sup>3</sup> code [17, 18] within the BIOVIA Materials Studio 2016 environment using the generalised gradient approximation (GGA), with a double numerical basis set (DNP) and the Perdew-Becker-Ernzerhof (PBE) exchange-correlation functional. All electrons were included in the calculations with unrestricted spin-polarization. A fine integration grid was used together with a Fermi smearing of 0.005 Hartree (Ha). The energy convergence tolerance was set to 1.0 <sup>10</sup><sup>5</sup> Ha; the maximum force was 0.002 Ha/Å and maximum displacement was set at 0.005 Å. The selfconsistent field (SCF) density convergence was set 1.0e 6.

The complete linear synchronous transit and quadratic synchronous transit (LST/QST) method [19] was used to locate the transition state structures according to the optimised structures of reactants and products. The nudged elastic band (NEB) method [20], as implemented in DMol<sup>3</sup> , was used to confirm that the transition state structures lead to the expected reactant and product molecular structures. Frequency calculations were performed to confirm the nature of all stationary points as either minima or transition states (TSs).

When investigating a reaction that takes place on the surface of a heterogeneous catalyst by quantum chemical methods, one of the main difficulties is modelling an infinite catalyst system as highlighted by Handzlik and Ogonowski [21], and a viable approach with the capacity of solving this problem is by the application of cluster models. Song et al. [22] claim that, ideally, cluster models are appropriate if a suitable boundary condition is obtained such that charges are in reasonable distribution on the surface. In this study, we chose a Al3MoO7H cluster to represent an active site of Mo on MoO3/γ-Al2O3. Assuming that the oxidation states of the elements in the model are distributed as follows: Al = 3+ , Mo = 4<sup>+</sup> ,H=1+ and O = 2; then the overall charge of the cluster would be zero. From this point of view it can be assumed that when the substrate adsorbs on Al3MoO7H, it occupies the vacant sites on Mo to form a cluster model in which the Mo is in an approximate octahedral environment with a 6+ oxidation state. This adsorption mode is consistent with the work of Kong et al. [23] who indicated how LAC could be formed from adsorbed intermediates such as pyruvaldehyde (PA).

recorded the absence of Brønsted acid sites in similar alumina systems, results which were further confirmed by their infrared studies, for example, by Lianecki et al. [24] and by XRD studies by Heracleous et al. [25]. It has been proposed by Gong et al. [26] that as long as the loading of MoO3 on γ-Al2O3 is less than 16% (w/w), the nature of surface acid-base sites that

Oxidation of Glycerol to Lactic Acid by Gold on Acidified Alumina: A Kinetic and DFT Case Study

http://dx.doi.org/10.5772/intechopen.70485

117

Catalyst testing commenced with investigating the effect of NaOH as a reaction initiator on the kinetics of glycerol oxidation using Mintek's 0.9-wt% Au/γ-Al2O3 (AUROliteTM) commercial catalyst. Figure 2 displays a plot depicting glycerol conversion as a function of time indicating that higher base concentrations led to greater glycerol conversions thereby shortening reaction time. It has indeed been previously reported that the base acts an initiator for this reaction [5].

In order to optimise the reaction conditions for mass transfer, a number of influencing parameters, e.g. stirring speed, oxygen partial pressure, amount of catalyst and the initial

exist on the surface would be predominantly of the Lewis type.

Figure 1. Qualitative analysis of the catalyst's acidity by the NH3-TPD method.

3.2. Reaction control: kinetic studies

3.2.2. Mass transfer limitations

3.2.1. The effect of base as a reaction initiator

### 3. Results

#### 3.1. Catalyst characterisation

The sample of the NH3-TPD profiles is displayed in Figure 1 shows that the Au-MoO3/γ-Al2O3 catalyst was more acidic than the original γ-Al2O3 support. All the materials displayed noticeable Lewis acidity (that is, electron accepting sites as opposed to the Brønsted acidity, which are regarded as proton donating sites) since the ammonia desorption occurred at the lower temperatures (below 300C). The γ-Al2O3 support indicated Lewis acidity having different strengths with the weaker sites desorbing NH3 at about 180C while the stronger sites desorbed NH3 at about 300C.

On the addition of gold, the Au/γ-Al2O3 catalyst showed a shift in the two peaks to the higher temperatures, that is, 220 and 450C, respectively. However, the addition of MoO3 on γ-Al2O3 support exhibited only the (weaker) Lewis acid sites that desorbed NH3 at the lower temperatures, peaking at 220C. This finding is in agreement with a number of researchers who have

Oxidation of Glycerol to Lactic Acid by Gold on Acidified Alumina: A Kinetic and DFT Case Study http://dx.doi.org/10.5772/intechopen.70485 117

Figure 1. Qualitative analysis of the catalyst's acidity by the NH3-TPD method.

recorded the absence of Brønsted acid sites in similar alumina systems, results which were further confirmed by their infrared studies, for example, by Lianecki et al. [24] and by XRD studies by Heracleous et al. [25]. It has been proposed by Gong et al. [26] that as long as the loading of MoO3 on γ-Al2O3 is less than 16% (w/w), the nature of surface acid-base sites that exist on the surface would be predominantly of the Lewis type.

#### 3.2. Reaction control: kinetic studies

BIOVIA Materials Studio 2016 environment using the generalised gradient approximation (GGA), with a double numerical basis set (DNP) and the Perdew-Becker-Ernzerhof (PBE) exchange-correlation functional. All electrons were included in the calculations with unrestricted spin-polarization. A fine integration grid was used together with a Fermi smearing of 0.005 Hartree (Ha). The energy convergence tolerance was set to 1.0 <sup>10</sup><sup>5</sup> Ha; the maximum force was 0.002 Ha/Å and maximum displacement was set at 0.005 Å. The self-

The complete linear synchronous transit and quadratic synchronous transit (LST/QST) method [19] was used to locate the transition state structures according to the optimised structures of reactants and products. The nudged elastic band (NEB) method [20], as

expected reactant and product molecular structures. Frequency calculations were performed to confirm the nature of all stationary points as either minima or transition states (TSs).

When investigating a reaction that takes place on the surface of a heterogeneous catalyst by quantum chemical methods, one of the main difficulties is modelling an infinite catalyst system as highlighted by Handzlik and Ogonowski [21], and a viable approach with the capacity of solving this problem is by the application of cluster models. Song et al. [22] claim that, ideally, cluster models are appropriate if a suitable boundary condition is obtained such that charges are in reasonable distribution on the surface. In this study, we chose a Al3MoO7H cluster to represent an active site of Mo on MoO3/γ-Al2O3. Assuming that the oxidation states

the overall charge of the cluster would be zero. From this point of view it can be assumed that when the substrate adsorbs on Al3MoO7H, it occupies the vacant sites on Mo to form a cluster model in which the Mo is in an approximate octahedral environment with a 6+ oxidation state. This adsorption mode is consistent with the work of Kong et al. [23] who indicated how LAC

The sample of the NH3-TPD profiles is displayed in Figure 1 shows that the Au-MoO3/γ-Al2O3 catalyst was more acidic than the original γ-Al2O3 support. All the materials displayed noticeable Lewis acidity (that is, electron accepting sites as opposed to the Brønsted acidity, which are regarded as proton donating sites) since the ammonia desorption occurred at the lower temperatures (below 300C). The γ-Al2O3 support indicated Lewis acidity having different strengths with the weaker sites desorbing NH3 at about 180C while the stronger sites desorbed NH3 at

On the addition of gold, the Au/γ-Al2O3 catalyst showed a shift in the two peaks to the higher temperatures, that is, 220 and 450C, respectively. However, the addition of MoO3 on γ-Al2O3 support exhibited only the (weaker) Lewis acid sites that desorbed NH3 at the lower temperatures, peaking at 220C. This finding is in agreement with a number of researchers who have

, was used to confirm that the transition state structures lead to the

, Mo = 4<sup>+</sup>

,H=1+ and O = 2; then

consistent field (SCF) density convergence was set 1.0e 6.

of the elements in the model are distributed as follows: Al = 3+

could be formed from adsorbed intermediates such as pyruvaldehyde (PA).

implemented in DMol<sup>3</sup>

116 Advanced Chemical Kinetics

3. Results

about 300C.

3.1. Catalyst characterisation

#### 3.2.1. The effect of base as a reaction initiator

Catalyst testing commenced with investigating the effect of NaOH as a reaction initiator on the kinetics of glycerol oxidation using Mintek's 0.9-wt% Au/γ-Al2O3 (AUROliteTM) commercial catalyst. Figure 2 displays a plot depicting glycerol conversion as a function of time indicating that higher base concentrations led to greater glycerol conversions thereby shortening reaction time. It has indeed been previously reported that the base acts an initiator for this reaction [5].

#### 3.2.2. Mass transfer limitations

In order to optimise the reaction conditions for mass transfer, a number of influencing parameters, e.g. stirring speed, oxygen partial pressure, amount of catalyst and the initial

Figure 2. The effect of base concentration as a reaction initiator on glycerol oxidation using 0.5 g of 0.9-wt% Au/γ-Al2O3 catalyst at 90�C and O2 pressure of 8.5 bar.

educt concentrations, were varied to arrive at the kinetic regime. The commercial 0.9-wt% Au/γ-Al2O3 (AuroliteTM) catalyst was used to establish the mass transfer regime. The stirring rate was fixed at 1000 rpm and the amount of catalyst varied as shown in Figure 3. In theory, if the rate doubles with the doubling of the weight of the catalyst, then the reaction is controlled by kinetics; if this is not the case, then the reaction is controlled by mass transfer. The curve in Figure 3 indicates that, under the defined experimental conditions, the ideal amount of catalyst necessary to achieve kinetic control was between 0.5 and 1.2 g. This 'reaction-limited' situation was ideal for the determination of intrinsic reaction kinetic parameters.

#### 3.2.3. The effect of temperature on activation energy

In this work, the activation energy for the oxidation of glycerol over Au/γ-Al2O3 catalyst was experimentally determined. For a zero-order reaction, it can be shown that fractional conversion is linearly dependent on time and temperature through the relationships shown in Eq. (1) and Eq. (2):

$$\mathbf{X}\_{\rm A} = \left(\frac{\mathbf{k}}{\mathbf{C}\_{\rm Ao}}\right) \cdot \mathbf{t} \tag{1}$$

CA0 is the initial concentration of A,

and that, k is dependent on temperature,

EA is the activation energy of the reaction, R is the gas constant 8.314 J mol�<sup>1</sup> K�<sup>1</sup> and

NaOH/glycerol = 2:1, at 60�C, under 8.5-bar O2 pressure.

T is the temperature in Kelvin.

concentration of the reactant.

t is time in minutes,

k is the rate constant with units as mol L�<sup>1</sup> min�<sup>1</sup> and

where k is the rate constant with units as mol L�<sup>1</sup> h�<sup>1</sup>

A is the pre-exponential factor, specific to this reaction

<sup>k</sup> <sup>¼</sup> <sup>A</sup>:e� EA

Figure 4 shows the plot of glycerol conversion as a function of time for experiments that were carried out at 60 and 90�C. Usually, k is regarded as the rate coefficient of the overall reaction, which is some measure of catalyst activity, but in essence, as shown by Eqs. (1) and (2), k is temperature-dependent, as well as concentration-dependent, usually dependent on the initial

Figure 3. Initial rate as a function of catalyst mass for glycerol oxidation over 0.9-wt% Au/γ-Al2O3 (106–150 mμ): 1000 rpm,

RT

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(2)

119

where XA is the fractional conversion of reactant A,

CA0 is the initial concentration of A,

k is the rate constant with units as mol L�<sup>1</sup> min�<sup>1</sup> and

t is time in minutes,

and that, k is dependent on temperature,

$$\mathbf{k} = \mathbf{A}. \mathbf{e}^{-\begin{pmatrix} \mathbf{E} \\ \hline \end{pmatrix}} \tag{2}$$

where k is the rate constant with units as mol L�<sup>1</sup> h�<sup>1</sup>

A is the pre-exponential factor, specific to this reaction

EA is the activation energy of the reaction,

R is the gas constant 8.314 J mol�<sup>1</sup> K�<sup>1</sup> and

T is the temperature in Kelvin.

educt concentrations, were varied to arrive at the kinetic regime. The commercial 0.9-wt% Au/γ-Al2O3 (AuroliteTM) catalyst was used to establish the mass transfer regime. The stirring rate was fixed at 1000 rpm and the amount of catalyst varied as shown in Figure 3. In theory, if the rate doubles with the doubling of the weight of the catalyst, then the reaction is controlled by kinetics; if this is not the case, then the reaction is controlled by mass transfer. The curve in Figure 3 indicates that, under the defined experimental conditions, the ideal amount of catalyst necessary to achieve kinetic control was between 0.5 and 1.2 g. This 'reaction-limited' situation was ideal for the determination of intrinsic reaction kinetic

Figure 2. The effect of base concentration as a reaction initiator on glycerol oxidation using 0.5 g of 0.9-wt% Au/γ-Al2O3

In this work, the activation energy for the oxidation of glycerol over Au/γ-Al2O3 catalyst was experimentally determined. For a zero-order reaction, it can be shown that fractional conversion is linearly dependent on time and temperature through the relationships shown in Eq. (1)

XA <sup>¼</sup> <sup>k</sup>

CAo 

� t (1)

parameters.

and Eq. (2):

3.2.3. The effect of temperature on activation energy

catalyst at 90�C and O2 pressure of 8.5 bar.

118 Advanced Chemical Kinetics

where XA is the fractional conversion of reactant A,

Figure 4 shows the plot of glycerol conversion as a function of time for experiments that were carried out at 60 and 90�C. Usually, k is regarded as the rate coefficient of the overall reaction, which is some measure of catalyst activity, but in essence, as shown by Eqs. (1) and (2), k is temperature-dependent, as well as concentration-dependent, usually dependent on the initial concentration of the reactant.

Figure 3. Initial rate as a function of catalyst mass for glycerol oxidation over 0.9-wt% Au/γ-Al2O3 (106–150 mμ): 1000 rpm, NaOH/glycerol = 2:1, at 60�C, under 8.5-bar O2 pressure.

Figure 4. Conversion of glycerol over time by 0.9-wt% Au/γ-Al2O3 (106�150 mμ) catalyst; 1000 rpm, NaOH/glycerol = 2:1, at 60 and 90�C, under an O2 pressure of 8.5 bar.

The rate constants, k, were estimated by non-linear regression of the model shown in Eq. (2) against experimental data and the results summarised in Table 1, showing the apparent EA determined from the estimated rate constants using a two-point Arrhenius equation, thus:

$$E\_A = \frac{T\_1 \times T\_2 \times R}{T\_2 - T\_2} \ln\left(\frac{k\_2}{k\_1}\right) \tag{3}$$

The experimentally obtained EA in this work, as shown in Table 1, is in good agreement with the 38 kJ mol�<sup>1</sup> value reported by Wörz et al. [27] for glycerol oxidation, although their work was based on a Pt-Bi/C catalyst. Demirel et al. [28] also reported activation energies of between 40 and 50 kJ mol�<sup>1</sup> for the Au/C catalysed glycerol oxidation, which is a result not far from our own. Finally, Chornaja et al. [10] also reported an apparent EA of about 39 � 3 kJ mol�<sup>1</sup> for

Table 1. Regression analysis of conversion vs. time data for the 0.9-wt% Au/γ-Al2O3 catalyst at different temperatures.

� <sup>t</sup> <sup>k</sup> <sup>60</sup>�<sup>C</sup> <sup>90</sup>�<sup>C</sup>

EA Value Confidence limits

Value Confidence limits Value Confidence limits 0.0059 0.0058 0.0061 0.018 0.017 0.019

.

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37.4 36.1 38.1

Oxidation of Glycerol to Lactic Acid by Gold on Acidified Alumina: A Kinetic and DFT Case Study

As a control, both the bulk γ-Al2O3 and MoO3/γ-Al2O3 supports did not show any activity

The effect of Au particle size on the kinetics of glycerol conversion was also investigated. Figure 5 shows TEM images of three Au/γ-Al2O3 catalysts with different Au particle sizes. When screened for glycerol oxidation under the same reaction conditions, the catalysts surprisingly revealed that the kinetics of this reaction strongly depend on the metal particle size, as shown in Figure 6. Big Au nanoparticles, ca 20 nm, exhibit first-order kinetics while the data for smaller Au nanoparticles, ca 4 nm, does not fit this model, instead showing zero-order kinetics as it has already been discussed. More details of this phenomenon have already been

So far we have only concentrated on the depletion kinetics of the reactant. In this section, we explore the global kinetics of the reaction, i.e. we set-up a kinetic model that takes into account the full mass balance of the reaction. At full substrate penetration and surface coverage, conversion is not limited by mass transfer; it is a fixed quantity set by the zero-order kinetics. Accordingly, mass transfer terms have not been explicitly expressed in the kinetic model used in this study since kinetic data was collected under the kinetic control regime. Therefore, Figure 7 presents the reaction network on which the kinetic modelling was based. The concentrations of all the compounds in the figure were taken into account in the calculations. Since the partial pressure (hence concentration) of O2 was maintained high in excess, its surface coverage

glycerol oxidation over Pd/Al2O3, which is also consistent with our findings.

Parameter values estimated at 95% confidence level; k = mol L�<sup>1</sup> min�<sup>1</sup> and EA = kJ mol�<sup>1</sup>

towards glycerol oxidation at 90�C.

.

Model# Parameter Temperature

XA <sup>¼</sup> <sup>k</sup> CA<sup>0</sup>

EA <sup>¼</sup> <sup>T</sup>1�T2�<sup>R</sup> <sup>T</sup>2�T<sup>2</sup> ln <sup>k</sup><sup>2</sup> k1

R = 8.314 J K�<sup>1</sup> mol�<sup>1</sup>

#

3.2.4. The effect of Au nanoparticle size

3.3. Global kinetic model prediction

reported elsewhere [14].

By the use of a two-point Arrhenius equation with catalyst activity being measured at 60 and 90�C, the pre-exponential factor, A, was determined to be equal to 274 695 mol dm�<sup>3</sup> h�<sup>1</sup> under the reaction conditions employed. In addition, the k values for the various catalysts were determined experimentally using Eq. (2). Then, since <sup>k</sup> <sup>¼</sup> 274 695:e�EA=RT, and in substituting the values for A and k in the Arrhenius equation, the EA per catalyst were found to be in very close proximity, with the least active catalyst (Au/γ-Al2O3) having the highest EA = 37.4 kJ mol�<sup>1</sup> , followed by the Au-MoO3/γ-Al2O3 with EA = 35.4 kJ mol�<sup>1</sup> . The rate constants (k) of the catalysts for overall glycerol conversion, calculated from experimental results were observed to be 2.22 and 1.14 mol dm� <sup>3</sup> h� <sup>1</sup> for the Au-MoO3/γ-Al2O3 and Au/γ-Al2O3, respectively, per gram of catalyst. Alternatively, when normalised to the amount of Au in the catalyst, the rate constants were found to be 642 mol dm�<sup>3</sup> h�<sup>1</sup> g�<sup>1</sup> Au for Au-MoO3/γ-Al2O3 catalyst and 252 moldm�<sup>3</sup> <sup>h</sup>�<sup>1</sup> <sup>g</sup>�<sup>1</sup> Au for Au/γ-Al2O3 catalyst.


Parameter values estimated at 95% confidence level; k = mol L�<sup>1</sup> min�<sup>1</sup> and EA = kJ mol�<sup>1</sup> . # R = 8.314 J K�<sup>1</sup> mol�<sup>1</sup> .

Table 1. Regression analysis of conversion vs. time data for the 0.9-wt% Au/γ-Al2O3 catalyst at different temperatures.

The experimentally obtained EA in this work, as shown in Table 1, is in good agreement with the 38 kJ mol�<sup>1</sup> value reported by Wörz et al. [27] for glycerol oxidation, although their work was based on a Pt-Bi/C catalyst. Demirel et al. [28] also reported activation energies of between 40 and 50 kJ mol�<sup>1</sup> for the Au/C catalysed glycerol oxidation, which is a result not far from our own. Finally, Chornaja et al. [10] also reported an apparent EA of about 39 � 3 kJ mol�<sup>1</sup> for glycerol oxidation over Pd/Al2O3, which is also consistent with our findings.

As a control, both the bulk γ-Al2O3 and MoO3/γ-Al2O3 supports did not show any activity towards glycerol oxidation at 90�C.

#### 3.2.4. The effect of Au nanoparticle size

The rate constants, k, were estimated by non-linear regression of the model shown in Eq. (2) against experimental data and the results summarised in Table 1, showing the apparent EA determined from the estimated rate constants using a two-point Arrhenius equation, thus:

Figure 4. Conversion of glycerol over time by 0.9-wt% Au/γ-Al2O3 (106�150 mμ) catalyst; 1000 rpm, NaOH/glycerol = 2:1,

By the use of a two-point Arrhenius equation with catalyst activity being measured at 60 and 90�C, the pre-exponential factor, A, was determined to be equal to 274 695 mol dm�<sup>3</sup> h�<sup>1</sup> under the reaction conditions employed. In addition, the k values for the various catalysts were determined experimentally using Eq. (2). Then, since <sup>k</sup> <sup>¼</sup> 274 695:e�EA=RT, and in substituting the values for A and k in the Arrhenius equation, the EA per catalyst were found to be in very close proximity, with the least active catalyst (Au/γ-Al2O3) having the highest EA = 37.4 kJ mol�<sup>1</sup>

for overall glycerol conversion, calculated from experimental results were observed to be 2.22 and 1.14 mol dm� <sup>3</sup> h� <sup>1</sup> for the Au-MoO3/γ-Al2O3 and Au/γ-Al2O3, respectively, per gram of catalyst. Alternatively, when normalised to the amount of Au in the catalyst, the rate constants

ln <sup>k</sup><sup>2</sup> k1 

(3)

,

Au

. The rate constants (k) of the catalysts

Au for Au-MoO3/γ-Al2O3 catalyst and 252 moldm�<sup>3</sup> <sup>h</sup>�<sup>1</sup> <sup>g</sup>�<sup>1</sup>

EA <sup>¼</sup> <sup>T</sup><sup>1</sup> � <sup>T</sup><sup>2</sup> � <sup>R</sup> T<sup>2</sup> � T<sup>2</sup>

followed by the Au-MoO3/γ-Al2O3 with EA = 35.4 kJ mol�<sup>1</sup>

were found to be 642 mol dm�<sup>3</sup> h�<sup>1</sup> g�<sup>1</sup>

at 60 and 90�C, under an O2 pressure of 8.5 bar.

120 Advanced Chemical Kinetics

for Au/γ-Al2O3 catalyst.

The effect of Au particle size on the kinetics of glycerol conversion was also investigated. Figure 5 shows TEM images of three Au/γ-Al2O3 catalysts with different Au particle sizes. When screened for glycerol oxidation under the same reaction conditions, the catalysts surprisingly revealed that the kinetics of this reaction strongly depend on the metal particle size, as shown in Figure 6. Big Au nanoparticles, ca 20 nm, exhibit first-order kinetics while the data for smaller Au nanoparticles, ca 4 nm, does not fit this model, instead showing zero-order kinetics as it has already been discussed. More details of this phenomenon have already been reported elsewhere [14].

#### 3.3. Global kinetic model prediction

So far we have only concentrated on the depletion kinetics of the reactant. In this section, we explore the global kinetics of the reaction, i.e. we set-up a kinetic model that takes into account the full mass balance of the reaction. At full substrate penetration and surface coverage, conversion is not limited by mass transfer; it is a fixed quantity set by the zero-order kinetics. Accordingly, mass transfer terms have not been explicitly expressed in the kinetic model used in this study since kinetic data was collected under the kinetic control regime. Therefore, Figure 7 presents the reaction network on which the kinetic modelling was based. The concentrations of all the compounds in the figure were taken into account in the calculations. Since the partial pressure (hence concentration) of O2 was maintained high in excess, its surface coverage

Figure 5. TEM images of Au/γ-Al2O3 catalysts prepared by various reducing agents: (A) reduced with 5% H2 (~4 nm); (B) reduced with THPC (~17 nm); and (C) reduced with PVA–citrate (~21 nm). Catalyst preparation details were outlined elsewhere [14].

was assumed constant and the surface reactions were modelled as pseudo-monomolecular in the tested model.

The complete mass balance, based on Figure 7, is represented by Eqs. (4)–(8). The model is pseudo-zero-order overall and contains five parameters in total.

$$\frac{d\mathbb{C}\_1}{dt} = -(r1 + r3) = -k\_1\tag{4}$$

Each rate constant, ki, is defined as:

ki ¼ Aie

Figure 6. Glycerol consumption plots over Au/γ-Al2O3 catalysts prepared by various reducing agents: (a) Small gold nanoparticles (ca 4 nm) show zero-order kinetic behaviour by linearly fitting conversion as a function of reaction time; (b) big gold nanoparticles (ca 17 and 21 nm) show first-order kinetics by linearly fitting the log of concentration of glycerol as a function of reaction time. The catalysts were reduced with 5% H2 (~4 nm), THPC (~17 nm) and PVA–citrate (~21 nm).

Catalyst preparation details were outlined elsewhere [14].

where Ai is the frequency factor and EAi is the activation energy.

�EAi

Oxidation of Glycerol to Lactic Acid by Gold on Acidified Alumina: A Kinetic and DFT Case Study

RT (9)

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123

$$\frac{d\mathbb{C}\_2}{dt} = r\mathbb{1} - r\mathbb{2} = k\_2 - k\_3\tag{5}$$

$$\frac{d\mathbb{C}\_3}{dt} = r\mathbb{2} = k\_3\tag{6}$$

$$\frac{d\mathbb{C}\_4}{dt} = r\mathbb{S} - r\mathbb{4} = k\_4 - k\_5 \tag{7}$$

$$\frac{d\mathbb{C}\_5}{dt} = r4 = k\_5 \tag{8}$$

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Each rate constant, ki, is defined as:

was assumed constant and the surface reactions were modelled as pseudo-monomolecular in the

Figure 5. TEM images of Au/γ-Al2O3 catalysts prepared by various reducing agents: (A) reduced with 5% H2 (~4 nm); (B) reduced with THPC (~17 nm); and (C) reduced with PVA–citrate (~21 nm). Catalyst preparation details were outlined

**A B** 

The complete mass balance, based on Figure 7, is represented by Eqs. (4)–(8). The model is

dt ¼ �ð Þ¼� <sup>r</sup><sup>1</sup> <sup>þ</sup> <sup>r</sup><sup>3</sup> <sup>k</sup><sup>1</sup> (4)

dt <sup>¼</sup> <sup>r</sup><sup>1</sup> � <sup>r</sup><sup>2</sup> <sup>¼</sup> <sup>k</sup><sup>2</sup> � <sup>k</sup><sup>3</sup> (5)

dt <sup>¼</sup> <sup>r</sup><sup>3</sup> � <sup>r</sup><sup>4</sup> <sup>¼</sup> <sup>k</sup><sup>4</sup> � <sup>k</sup><sup>5</sup> (7)

dt <sup>¼</sup> <sup>r</sup><sup>2</sup> <sup>¼</sup> <sup>k</sup><sup>3</sup> (6)

dt <sup>¼</sup> <sup>r</sup><sup>4</sup> <sup>¼</sup> <sup>k</sup><sup>5</sup> (8)

pseudo-zero-order overall and contains five parameters in total.

**C** 

dC<sup>1</sup>

dC<sup>2</sup>

dC<sup>4</sup>

dC<sup>3</sup>

dC<sup>5</sup>

tested model.

elsewhere [14].

122 Advanced Chemical Kinetics

$$k\_i = A\_i e^{\frac{-k\_{A\_i}}{RT}} \tag{9}$$

where Ai is the frequency factor and EAi is the activation energy.

Figure 6. Glycerol consumption plots over Au/γ-Al2O3 catalysts prepared by various reducing agents: (a) Small gold nanoparticles (ca 4 nm) show zero-order kinetic behaviour by linearly fitting conversion as a function of reaction time; (b) big gold nanoparticles (ca 17 and 21 nm) show first-order kinetics by linearly fitting the log of concentration of glycerol as a function of reaction time. The catalysts were reduced with 5% H2 (~4 nm), THPC (~17 nm) and PVA–citrate (~21 nm). Catalyst preparation details were outlined elsewhere [14].

Figure 7. Reaction network used for the kinetic modelling of the glycerol oxidation. FOP\* = further oxidation products (tartronic, oxalic, glycolic and formic acids).

The concentrations Ci were allocated as follows: C1 = glycerol; C2 = glyceric acid (GA); C3 = FOP\* (further oxidation products—FOP—were lumped together as tartronic acid, oxalic acid, glycolic acid and formic acid); C4 = LAC and C5 = acetic acid. The reason FOP were lumped together is that the study was only concerned with the apparent competition between the rate of formation of LAC and that of GA from glycerol and the possible effect of Lewis acidity on the rate of LAC formation. Generally, there was a good fit between the fitted pseudo-zeroorder model and experiment for both tested catalysts. The results of the regression analyses of the model against experimental data showed a good fit as visually seen in Figure 8; the rate constants are summarised in Table 2 for both Au/γ-Al2O3 and Au-MoO3/γ-Al2O3, respectively. The estimated kinetic parameters were statistically significant.

formation of LAC, as evidenced in Eq. (10) by the ratio of the rate constants of formation of

Au/γ-Al2O3 Au/MoO3-γ-Al2O3

k1 0.019 0.018 0.02 0.035 0.032 0.038 k2 0.021 0.019 0.023 0.023 0.018 0.028 k3 0.008 0.007 0.01 0.009 0.006 0.013 k4 0.004 0.002 0.006 0.023 0.019 0.028 k5 0.001 0.000 0.003 0.005 0.002 0.008

Value Confidence limits Value Confidence limits

Oxidation of Glycerol to Lactic Acid by Gold on Acidified Alumina: A Kinetic and DFT Case Study

.

As far as we are aware, no formation of LAC from Au-based catalysts (our work included) has been reported at 60�C except when Pd-based catalysts were used, which also gave very low

catalytic performance as argued by Boudart [29]. TOF is regarded as the number of times that the overall catalytic reaction takes place per catalytic site per unit time for a fixed set of reaction conditions. Boudart has asserted that even though it may not be rigorous, a TOF measure leads to values that can be reproduced from one laboratory to another, besides catalysts of different characteristics being likened. We have therefore simplified TOF to mean the number of glycerol moles converted per the total number of moles of Au used per unit time of reaction, in hours, assuming that all the gold present in the catalyst was active. We have also assumed that the reaction occurred at constant temperature (90�C), O2 pressure (8.5 bar), concentration (1.1 M of glycerol at t0), and the ratio of reactants, while the extent of reaction was taken after half an

ffi 6 (10)

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125

) [10]. The TOF is the best measure of comparing

moles of Au : <sup>1</sup>

, compared to that of Au-MoO3/γ-Al2O3 catalyst

time hð Þ (11)

kAu=MoO3�Al2O<sup>3</sup> kAu=Al2O<sup>3</sup>

LAC over the two catalysts.

Parameter\* Catalyst

turnover frequency (TOF) values (~60 h�<sup>1</sup>

\*Parameter values were estimated at 95% confidence level; k = mol L�<sup>1</sup> min�<sup>1</sup>

Table 2. Regression analysis of global kinetic model assuming pseudo-zero-order kinetics.

hour. Thus, TOF was calculated by the equation:

an hour was calculated to be 4.971 h�<sup>1</sup>

(ca 12.800 h�<sup>1</sup>

TOF <sup>¼</sup> ð Þ %conversion :ðinitialmoles glycerol

latter point could be related to gold-support interaction effects.

<sup>100</sup> : <sup>1</sup>

For example, the TOF of the AuroliteTM commercial catalyst (0.9-wt% Au/γ-Al2O3) after half

Mo enhance the selectivity to LAC, but it also drives the forward conversion of glycerol. This

). This result shows that not only does the increased acidity due the presence of

From Table 2, one of the most intriguing results was the 'jump' in the rate of formation of LAC (k4) over the Au-MoO3/γ-Al2O3 catalyst relative to Au/γ-Al2O3. Indeed Eq. (10), which compares the rate of formation of LAC over the two catalysts, paints a clearer picture. It is conceivable that the extra Lewis acidity provided by Mo played a role in the promoted

Figure 8. Comparison of computed and experimental data for glycerol oxidation assuming zero-order kinetics over Au-MoO3/γ-Al2O3 (top) and Au/γ-Al2O3 (bottom); Glycerol ( ), glyceric acid ( ), FOP\* ( ), LAC ( ), acetic acid ( ).


\*Parameter values were estimated at 95% confidence level; k = mol L�<sup>1</sup> min�<sup>1</sup> .

The concentrations Ci were allocated as follows: C1 = glycerol; C2 = glyceric acid (GA); C3 = FOP\* (further oxidation products—FOP—were lumped together as tartronic acid, oxalic acid, glycolic acid and formic acid); C4 = LAC and C5 = acetic acid. The reason FOP were lumped together is that the study was only concerned with the apparent competition between the rate of formation of LAC and that of GA from glycerol and the possible effect of Lewis acidity on the rate of LAC formation. Generally, there was a good fit between the fitted pseudo-zeroorder model and experiment for both tested catalysts. The results of the regression analyses of the model against experimental data showed a good fit as visually seen in Figure 8; the rate constants are summarised in Table 2 for both Au/γ-Al2O3 and Au-MoO3/γ-Al2O3, respectively.

Figure 7. Reaction network used for the kinetic modelling of the glycerol oxidation. FOP\* = further oxidation products

From Table 2, one of the most intriguing results was the 'jump' in the rate of formation of LAC (k4) over the Au-MoO3/γ-Al2O3 catalyst relative to Au/γ-Al2O3. Indeed Eq. (10), which compares the rate of formation of LAC over the two catalysts, paints a clearer picture. It is conceivable that the extra Lewis acidity provided by Mo played a role in the promoted

Figure 8. Comparison of computed and experimental data for glycerol oxidation assuming zero-order kinetics over Au-MoO3/γ-Al2O3 (top) and Au/γ-Al2O3 (bottom); Glycerol ( ), glyceric acid ( ), FOP\* ( ), LAC ( ), acetic acid ( ).

The estimated kinetic parameters were statistically significant.

(tartronic, oxalic, glycolic and formic acids).

124 Advanced Chemical Kinetics

Table 2. Regression analysis of global kinetic model assuming pseudo-zero-order kinetics.

formation of LAC, as evidenced in Eq. (10) by the ratio of the rate constants of formation of LAC over the two catalysts.

$$\frac{k\_{Au/MoO\_3-Al\_2O\_3}}{k\_{Au/Al\_2O\_3}} \cong 6\tag{10}$$

As far as we are aware, no formation of LAC from Au-based catalysts (our work included) has been reported at 60�C except when Pd-based catalysts were used, which also gave very low turnover frequency (TOF) values (~60 h�<sup>1</sup> ) [10]. The TOF is the best measure of comparing catalytic performance as argued by Boudart [29]. TOF is regarded as the number of times that the overall catalytic reaction takes place per catalytic site per unit time for a fixed set of reaction conditions. Boudart has asserted that even though it may not be rigorous, a TOF measure leads to values that can be reproduced from one laboratory to another, besides catalysts of different characteristics being likened. We have therefore simplified TOF to mean the number of glycerol moles converted per the total number of moles of Au used per unit time of reaction, in hours, assuming that all the gold present in the catalyst was active. We have also assumed that the reaction occurred at constant temperature (90�C), O2 pressure (8.5 bar), concentration (1.1 M of glycerol at t0), and the ratio of reactants, while the extent of reaction was taken after half an hour. Thus, TOF was calculated by the equation:

$$\text{TOF} = \left[ \frac{(\% \text{conversion}) . (\text{initial moles} \,\text{(glycerol)}}{100} \right] . \left[ \frac{1}{\text{moles of Au}} \right] . \left[ \frac{1}{\text{time (h)}} \right] \tag{11}$$

For example, the TOF of the AuroliteTM commercial catalyst (0.9-wt% Au/γ-Al2O3) after half an hour was calculated to be 4.971 h�<sup>1</sup> , compared to that of Au-MoO3/γ-Al2O3 catalyst (ca 12.800 h�<sup>1</sup> ). This result shows that not only does the increased acidity due the presence of Mo enhance the selectivity to LAC, but it also drives the forward conversion of glycerol. This latter point could be related to gold-support interaction effects.

#### 3.4. Proposed role of Mon+ in lactic acid formation

It is generally accepted that LAC is formed from glycerol (GLY) via the intermediates as depicted in Figure 9 [5, 30–32]. Under the reaction conditions employed in this study, dihydroxyacetone (DHA) was formed at 60�C and could be isolated; however, at 90�C, LAC was formed instead.

It is plausible that at the latter temperature, DHA still forms but reacts further with LAC, thus assuming the role of an (unstable) intermediate. In the presence of base, DHA can form from glycerol via the isomerisation of GLA [31]. Assary et al. [33] have reported that a Lewis acidbase pair catalyses this isomerisation reaction and it is conceivable that the enhanced formation of LAC over Au-MoO3/γ-Al2O3 could have been a direct consequence of the increased Lewis acid-base pair sites on the catalyst. In this section, we apply transition state theory principles [34–36] via DFT simulations to extract thermodynamic and kinetic parameters for this isomerisation reaction. Experimentally, Rasrendra et al. [37] suggested that, under catalytic conditions, GLA can be successfully isomerised to LAC. The rest of this chapter discusses the potential role played by Mo in the formation of LAC over supported bi-functional Au catalysts at low temperatures, assuming the reaction occurs according to Eq. (12).

$$\text{LGLY} \xrightarrow{\text{Au}} \text{GLA} \xrightarrow{\text{Mo}-\text{OH}} \text{LAC} \tag{12}$$

complete the isomerisation and form a LAC molecule. Similar mechanisms have been proposed by numerous authors [5, 30, 33, 39–40], although none of these studies have modelled the mechanism at the DFT level of theory. The DFT predicted kinetic and thermodynamic parameters are summarised in Table 3. The reaction kinetics tool within BIOVIA Materials

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Figure 10. Possible Lewis acid-base pair dual site involved in the isomerisation of PA to LAC.

)

TS1 (hydration) 59.0 57.7 2.7 57.7 TS2 (1,2 proton shift) 74.7 57.0 131.7 57.0 TS3 (protonation) 229.7 25.5 257.8 25.5

Table 3. DFT predicted kinetic and thermodynamic parameters for the Mo–OH catalysed isomerisation of PA to LAC.

The direction of normal mode of vibration of the transition state is shown by the pointed arrow.

Forward Reverse

Ea ΔH Ea ΔH

Transition state Parameters (kJ mol<sup>1</sup>

DFT calculations have been done only for the second part of the reaction, since the calculations for GLY to GLA over Au have been discussed in detail elsewhere [31, 38]. The mechanism shown in Figure 10 proposes that a crucial part of the isomerisation of GLA to LAC could be an adsorbed pyruvaldehyde (PA) molecule on the molybdenum Lewis acid site forming a five membered ring C–C–O–Mo–O. The adsorbed PA is then hydrated by a surface hydroxyl, as advanced by Kong et al. [23]. The intermediate product then undergoes a hydride shift rearrangement. Finally, a proton is then transferred from a water molecule to

Figure 9. Proposed intermediates in the conversion of glycerol to LAC.

complete the isomerisation and form a LAC molecule. Similar mechanisms have been proposed by numerous authors [5, 30, 33, 39–40], although none of these studies have modelled the mechanism at the DFT level of theory. The DFT predicted kinetic and thermodynamic parameters are summarised in Table 3. The reaction kinetics tool within BIOVIA Materials

3.4. Proposed role of Mon+ in lactic acid formation

126 Advanced Chemical Kinetics

It is generally accepted that LAC is formed from glycerol (GLY) via the intermediates as depicted in Figure 9 [5, 30–32]. Under the reaction conditions employed in this study, dihydroxyacetone (DHA) was formed at 60�C and could be isolated; however, at 90�C, LAC was formed instead. It is plausible that at the latter temperature, DHA still forms but reacts further with LAC, thus assuming the role of an (unstable) intermediate. In the presence of base, DHA can form from glycerol via the isomerisation of GLA [31]. Assary et al. [33] have reported that a Lewis acidbase pair catalyses this isomerisation reaction and it is conceivable that the enhanced formation of LAC over Au-MoO3/γ-Al2O3 could have been a direct consequence of the increased Lewis acid-base pair sites on the catalyst. In this section, we apply transition state theory principles [34–36] via DFT simulations to extract thermodynamic and kinetic parameters for this isomerisation reaction. Experimentally, Rasrendra et al. [37] suggested that, under catalytic conditions, GLA can be successfully isomerised to LAC. The rest of this chapter discusses the potential role played by Mo in the formation of LAC over supported bi-functional Au catalysts

at low temperatures, assuming the reaction occurs according to Eq. (12).

Figure 9. Proposed intermediates in the conversion of glycerol to LAC.

GLY !

DFT calculations have been done only for the second part of the reaction, since the calculations for GLY to GLA over Au have been discussed in detail elsewhere [31, 38]. The mechanism shown in Figure 10 proposes that a crucial part of the isomerisation of GLA to LAC could be an adsorbed pyruvaldehyde (PA) molecule on the molybdenum Lewis acid site forming a five membered ring C–C–O–Mo–O. The adsorbed PA is then hydrated by a surface hydroxyl, as advanced by Kong et al. [23]. The intermediate product then undergoes a hydride shift rearrangement. Finally, a proton is then transferred from a water molecule to

Au GLA ! Mo�OH LAC (12)

Figure 10. Possible Lewis acid-base pair dual site involved in the isomerisation of PA to LAC.


Table 3. DFT predicted kinetic and thermodynamic parameters for the Mo–OH catalysed isomerisation of PA to LAC. The direction of normal mode of vibration of the transition state is shown by the pointed arrow.

Studio 2016 was used to automate the calculations of all the parameters. Tunnelling corrections were included in all calculations. The protonation step is thermodynamically downhill, but has the highest activation barrier (229 kJ mol<sup>1</sup> ) for the forward reaction as shown in the mentioned table. The magnitude of this barrier is in the order of the bond-dissociation energy of HO–H bond of a water molecule (H2O) which requires about 268 kJ mol<sup>1</sup> at 298 K. Assuming that the reaction is controlled by kinetics, this step is the rate-limiting step. The high energy barrier for the rate-limiting step probably explains why LAC forms at 90C under the reaction conditions employed, but none was observed at 60C. A higher temperature is needed to overcome the barrier (Ea/R) in order to get appreciable rates of the formation of the final product.

[2] Haruta M. Catalysis of gold nanoparticles deposited on metal oxides. CATTECH. 2002;6(3):

Oxidation of Glycerol to Lactic Acid by Gold on Acidified Alumina: A Kinetic and DFT Case Study

http://dx.doi.org/10.5772/intechopen.70485

129

[3] Ketchie WC, Fang Y, Wong MS, Murayama M, Davies RJ. Influence of gold particle size on the aqueous phase oxidation of carbon monoxide and glycerol. Journal of Catalysis.

[4] Ketchie WC, Murayama M, Davies RJ. Selective oxidation of glycerol over carbon

[5] Ketchie WC, Murayama M, Davies RJ. Promotional effect of hydroxyl on the aqueous phase oxidation of carbon monoxide and glycerol over supported Au catalysts. Topics in

[6] Wang D, Villa A, Su D, Prati L, Schlogl R. Carbon supported gold nanocatalysts: Shape

[7] Villa A, Wang D, Su DS, Prati L. Gold sols as catalysts for glycerol oxidation: The role of

[8] Demirel S, Lucas M, Lehnert K, Claus P. Use of renewables for the production of chemicals: Glycerol oxidation over carbon supported gold catalysts. Applied Catalysis

[9] Royker M, Case J, van Steen E. Platinum promotion of Au/Al2O3 catalysts for glycerol oxidation: Activity, selectivity, and deactivation. The Journal of Southern African Institute

[10] Chornaja S, Dubencov K, Kampars V, Stepanova O, Zhizhkun S, Serga V, et al. Oxidation of glycerol with oxygen in alkaline aqueous solutions in the presence of supported palladium catalysts prepared by extractive pyrolytic method. Reaction Kinetic Mecha-

[11] Carretin S, McMorn P, Johnston P, Griffin K, Hutchings GJ. Oxidation of glycerol using supported Pt, Pd and Au catalysts. Physical Chemistry Chemical Physics. 2003;5:1329-1336

[12] Stobbe-Kreemers AW, Vanleerdam GCV, Jacobs JP, Brogersma HH, Scholten JJF. Characterization of γ-alumina-supported vanadium oxide monolayers. Journal of Catalysis.

[13] Raubenheimer HG, Cronje S. Progress in Chemistry, Biochemistry and Biotechnology.

[14] Ntho T, Aluha J, Gqogqa P, Raphulu M, Pattrick G. Au/γ-Al2O3 catalysts for glycerol oxidation: The effect of support acidity and gold particle size. Reaction Kinetic Mecha-

[15] Belohlav Z, Zamostny P, Kluson P, Volf J. Application of random-search algorithm for regression analysis of catalytic hydrogenations. Canadian Journal of Chemical Engineer-

effect in the selective glycerol oxidation. ChemCatChem. 2017;5(9):2717-2723

supported AuPd Catalysts. Journal of Catalysis. 2007;250:264-273

stabilizer. ChemCatChem Catalysis. 2009;1:510-514

B: Environmental. 2007;70(1-4):637-643

of Mining and Metallurgy. 2012;7A:577-581

Chichester: John Wiley & Sons; 1999. 573-576

nism and Catalysis. 2013;109(1):133-148

nism Catalysis. 2013;108:341-357

1995;152:130-136

ing. 1997;75:735-742

102-115

2007;250:94-101

Catalysis. 2007;44(1–2):307-317

### 4. Conclusions

Both Au/γ-Al2O3 and Au-MoO3/γ-Al2O3 showed zero-order kinetics under kinetic controlled glycerol oxidation. The apparent Ea of glycerol oxidation under these conditions was experimentally determined to be approximately 36 kJ mol<sup>1</sup> . Under the same reaction conditions, the presence of MoO3 increased the formation of LAC sixfold over Au-MoO3/γ-Al2O3 relative to Au/γ-Al2O3. A proposed DFT model suggested that protonation by an adsorbed water molecule might be the rate-limiting step in the isomerisation of PA to LAC catalysed by a Mo–OH Lewis acid-base pair.

### Acknowledgements

The authors would like to thank both Mintek and Anglo-gold Ashanti through Project AuTek for granting the permission to publish this work and for financial support. In addition, we express gratitude to the South African Centre for High Performance Computing (CHPC) for their support in availing to us the infrastructure used in DFT modelling.

### Author details

Thabang A. Ntho\*, Pumeza Gqogqa and James L. Aluha \*Address all correspondence to: thabang.ntho@mintek.co.za

Mintek, Advanced Materials Division, Johannesburg, RSA

### References

[1] Wee Y-J, Kim J-N, Ryu H-W. Biotechnological production of lactic acid and its recent applications. Food Technology Biotechnology. 2006;44(2):163-172

[2] Haruta M. Catalysis of gold nanoparticles deposited on metal oxides. CATTECH. 2002;6(3): 102-115

Studio 2016 was used to automate the calculations of all the parameters. Tunnelling corrections were included in all calculations. The protonation step is thermodynamically downhill,

mentioned table. The magnitude of this barrier is in the order of the bond-dissociation energy of HO–H bond of a water molecule (H2O) which requires about 268 kJ mol<sup>1</sup> at 298 K. Assuming that the reaction is controlled by kinetics, this step is the rate-limiting step. The high energy barrier for the rate-limiting step probably explains why LAC forms at 90C under the reaction conditions employed, but none was observed at 60C. A higher temperature is needed to overcome the barrier (Ea/R) in order to get appreciable rates of the

Both Au/γ-Al2O3 and Au-MoO3/γ-Al2O3 showed zero-order kinetics under kinetic controlled glycerol oxidation. The apparent Ea of glycerol oxidation under these conditions was experi-

presence of MoO3 increased the formation of LAC sixfold over Au-MoO3/γ-Al2O3 relative to Au/γ-Al2O3. A proposed DFT model suggested that protonation by an adsorbed water molecule might be the rate-limiting step in the isomerisation of PA to LAC catalysed by a Mo–OH

The authors would like to thank both Mintek and Anglo-gold Ashanti through Project AuTek for granting the permission to publish this work and for financial support. In addition, we express gratitude to the South African Centre for High Performance Computing (CHPC) for

[1] Wee Y-J, Kim J-N, Ryu H-W. Biotechnological production of lactic acid and its recent

applications. Food Technology Biotechnology. 2006;44(2):163-172

their support in availing to us the infrastructure used in DFT modelling.

Thabang A. Ntho\*, Pumeza Gqogqa and James L. Aluha

\*Address all correspondence to: thabang.ntho@mintek.co.za Mintek, Advanced Materials Division, Johannesburg, RSA

) for the forward reaction as shown in the

. Under the same reaction conditions, the

but has the highest activation barrier (229 kJ mol<sup>1</sup>

mentally determined to be approximately 36 kJ mol<sup>1</sup>

formation of the final product.

4. Conclusions

128 Advanced Chemical Kinetics

Lewis acid-base pair.

Author details

References

Acknowledgements


[16] Zamostny P, Belohlav Z. A software for regression analysis. Computers and Chemistry. 1999;23:479-485

[31] Zope BN, Hibbits DD, Neurock M, Davis RJ. Reactivity of the gold/water interface during

Oxidation of Glycerol to Lactic Acid by Gold on Acidified Alumina: A Kinetic and DFT Case Study

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[32] Román-Leshkov Y, Davis ME. Activation of carbonyl containing molecules with solid

[33] Assary RS, Curtiss LA. Theoretical study of 1, 2-hydride shift associated with the isomerisation of glyceraldehyde to dihydroxy acetone by Lewis acid active site models.

[34] Evans MG, Polanyi M. Some applications of the transition state method to the calculation of reaction velocities, especially in solution. Transactions of the Faraday Society.

[35] Eyring H. The activated complex in chemical reactions. Journal of Chemical Physics.

[36] Geng Z, Zhang M, Yu Y. Theoretical investigation on pyrolysis mechanism of glycerol.

[37] Rasrendra CB, Marketihartha IGBN, Adisasmito S, Heeres HJ. Green chemicals from dglucose: Systematic studies on catalytic effects of inorganic salts on the chemo-selectivity

[38] Shang C, Liu Z-P. Origin and activity of gold nanoparticles as aerobic oxidation catalysts in aqueous solution. Journal of American Chemical Society. 2011;133:9938-9947

[39] West RM, Holm MS, Saravanamurugan S, Xiong J, Beversdorf Z, Christensen CH. Zeolite H-USY for the production of lactic acid and methyl lactate from C-3 sugars. Journal of

[40] Rasrendra CB, Fachri BA, Marketihartha IGBN, Adisasmito S, Heers HJ. Catalyic conversion of dihydroxyacetone to lactic acid using metal salts in water. Journal of Sustainable

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[20] Sheppard D, Terrell R, Henkelman G. Optimization methods for finding minimum

[21] Handzlik J, Ogonowski J. Theoretical study on ethene metathesis proceeding on MoVI and MoIV methylidene centres of heterogeneous molybdena-alumina catalyst. Journal of

[22] Song X, Liu G, Yu J, Rodrigues AE. Density functional theoretical study of water molecular adsorption on surface of MoO3 with the cluster model. Journal of Molecular Struc-

[23] Kong L, Li G, Wang H, He W, Ling F. Hydrothermal catalytic conversion of biomass for lactic acid production. Journal of Chemical Technology and Biotechnology. 2008;83:383-388

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**Chapter 8**

Provisional chapter

**Hydrothermal Precipitation of β-FeOOH Nanoparticles**

In this research, synthesis of β-FeOOH nanoparticles was carried out using different alcohol/water mixed solvents. Four different alcohols were mixed with water to form solution of different surface tension. A relationship between particle size and surface tension has been drawn from theoretical analysis. A linear relationship was shown to exist between surface tension and particle size under the reported conditions. Statistically designed experiments were conducted to evaluate the interactions of process parameters on the particle growth. A generic correlation has also been developed empir-

Keywords: β-FeOOH, nanorod, crystal growth, surface tension, generic correlation

Akaganeite, β-FeOOH, a type of iron oxy hydroxide has been studied intensively not only because of its great technological and scientific interest but also for many applications [1]. β-FeOOH is a promising electrode material that has potential in rechargeable batteries due to its hollandite-like crystal structure with tunnel-like cavities [2]. β-FeOOH has also found applications in hydroprocessing of coal, removal of arsenate/arsenite [3] and phosphate from water [4]. Due to these intriguing applications, numerous works have investigated the methods of akaganeite synthesis [2]. Surface tension of solvent plays an important role in the formation of 1D β-FeOOH nanorods. A low surface tension of solvent can promote the growth of β-FeOOH nanorods [5]. Addition of medium that can lower the surface tension of precursor solution can alter the thermodynamic properties of the reaction system and subsequently affect the nucleation kinetics, which would result in various morphology and particle sizes. The application of alcohol/water mixture during the synthesis of different metal oxide nanoparticles

> © The Author(s). Licensee InTech. 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 eproduction in any medium, provided the original work is properly cited.

© 2018 The Author(s). Licensee InTech. 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.

Hydrothermal Precipitation of β-FeOOH Nanoparticles in

DOI: 10.5772/intechopen.70503

**in Mixed Water/Alcohol Solvent**

Mixed Water/Alcohol Solvent

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.70503

ically to predict particle size.

Mahabubur Chowdhury

Mahabubur Chowdhury

Abstract

1. Introduction

Provisional chapter

### **Hydrothermal Precipitation of β-FeOOH Nanoparticles in Mixed Water/Alcohol Solvent** Hydrothermal Precipitation of β-FeOOH Nanoparticles in

DOI: 10.5772/intechopen.70503

Mahabubur Chowdhury

Additional information is available at the end of the chapter Mahabubur Chowdhury

Mixed Water/Alcohol Solvent

http://dx.doi.org/10.5772/intechopen.70503 Additional information is available at the end of the chapter

#### Abstract

In this research, synthesis of β-FeOOH nanoparticles was carried out using different alcohol/water mixed solvents. Four different alcohols were mixed with water to form solution of different surface tension. A relationship between particle size and surface tension has been drawn from theoretical analysis. A linear relationship was shown to exist between surface tension and particle size under the reported conditions. Statistically designed experiments were conducted to evaluate the interactions of process parameters on the particle growth. A generic correlation has also been developed empirically to predict particle size.

Keywords: β-FeOOH, nanorod, crystal growth, surface tension, generic correlation

### 1. Introduction

Akaganeite, β-FeOOH, a type of iron oxy hydroxide has been studied intensively not only because of its great technological and scientific interest but also for many applications [1]. β-FeOOH is a promising electrode material that has potential in rechargeable batteries due to its hollandite-like crystal structure with tunnel-like cavities [2]. β-FeOOH has also found applications in hydroprocessing of coal, removal of arsenate/arsenite [3] and phosphate from water [4]. Due to these intriguing applications, numerous works have investigated the methods of akaganeite synthesis [2]. Surface tension of solvent plays an important role in the formation of 1D β-FeOOH nanorods. A low surface tension of solvent can promote the growth of β-FeOOH nanorods [5]. Addition of medium that can lower the surface tension of precursor solution can alter the thermodynamic properties of the reaction system and subsequently affect the nucleation kinetics, which would result in various morphology and particle sizes. The application of alcohol/water mixture during the synthesis of different metal oxide nanoparticles

© The Author(s). Licensee InTech. 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 eproduction in any medium, provided the original work is properly cited.

can be found in the literature. Submicrometer ZrO2 nanomaterial was synthesised by Hu and Chen [6] using alcohol/water mixture. Fang and Chen [7] used a mixed solvent of water/ n-propanol to synthesise titania powders. ZrO2(Y2O3) nanoparticles were synthesised by Li and Gao [8] using ethanol/water mixture. So far, the effect of mixed solvent properties on the growth of 1D β-FeOOH nanorods were not evaluated despite of its numerical industrial and scientific applications. In our previous work, we have demonstrated that alcohol played an important role in controlling nucleation rate and particle size of 1D β-FeOOH nanoparticles [9, 10]. Previously reported work in the literature considered the dielectric constant, ε, properties of the water/alcohol mixture to be of significance in controlling particle growth, discarding the effect of surface tension, γ. However, it is interesting to note that the Coulomb interaction is very weak in water and solvent with high ε [11] and Coulomb interaction is directly related to ε of the solvent. This simple phenomenon makes the application of the ε of solvent only to relate to particle growths as described in the literature susceptible.

<sup>Δ</sup>μ<sup>o</sup> <sup>¼</sup> <sup>Ζ</sup>þΖ�e<sup>2</sup>

2γ

rkT<sup>ρ</sup> <sup>¼</sup> ln<sup>C</sup> <sup>þ</sup>

where m is the weight of the solute molecule; γ is the interfacial energy in J/m<sup>2</sup>

proposed the below equation:

2. Experimental

2.1. Materials and method

synthesise the particles.

3. Results and discussion

3.1. Correlation between particle size and alcohol surface tension

interfacial energy can also be written as nm�<sup>1</sup>

where ε<sup>o</sup> represents the permittivity in vacuum and ε is dielectric constant of a given solution. r<sup>+</sup> and r� present the radii of ions charged. Based on Eqs. (1) and (2), Chen and Chang [12]

C is the solute concentration. The author linearized Eq. (3) in terms of particle size r(Y) and dielectric constant ε(X). It was assumed that only dielectric constant is significant and other properties are insignificant. However, according to Israelachvili [11], Coulombic interaction is much weakened in water. So, it can be postulated that, for homologous mixture of water and alcohol, the Coulombic interaction will be very weak. Hence, it can also be hypothesised that the surface tension of solvent will directly affect the nucleation and growth of particles.

Analytical-grade FeCl3�6H2O and NH4OH (B & M Scientific, Cape Town, R.S.A) were used as they are without any further purification. Deionised water and alcohol (methanol, ethanol and propanol) were mixed together with different ratios to vary the surface tension of solvent. Ammonium hydroxide, NH4OH, was added drop wise until the mixture pH reached a value of 10. A certain amount of FeCl3�6H2O was added to the solution to make up 0.05 M solution (unless stated otherwise), and the solution was stirred until the iron salt was dissolved. The pH of the final solution (prior to heating) was recorded. The pH was always kept constant at ~2 to isolate the effect of pH on the particle growth in each case. The solution was replaced in a teflon-lined pressure autoclave. The temperature was 100�C. A reaction time of 2 h was used to

Three different alcohols (methanol, ethanol and propanol) were used to tune the surface tension of the solvent. If the hypothesis conceived earlier is true, then there will be a qualitative relationship between particle size, De, and surface tension of solvent, γ. The particles synthesised in this study were rod-shaped particles. The length and diameter of the particles were measured from TEM images. A minimum number of 250 particles was counted for

4πεoεð Þ r<sup>þ</sup> þ r�

<sup>Ζ</sup>þΖ�e<sup>2</sup> 4πεoεKT rð Þ <sup>þ</sup> þ r�

Hydrothermal Precipitation of β-FeOOH Nanoparticles in Mixed Water/Alcohol Solvent

; r is the particle size of a spherical particle and

http://dx.doi.org/10.5772/intechopen.70503

(2)

135

(3)

, the term

The application of mixed solvent is a new approach in the synthesis and processing of materials [12]. However, the role of surface tension is neglected when relating particle growth with solvent properties. Tuning the surface tension of the water/alcohol can affect the colloidal interaction between solid particles. Most of the literature reported on the use of alcohol/water mixture on the precipitation of submicro meter-sized TiO2, ZrO2, SiO2 and CeO2 particles. Published literature provides evidence that the formation of nanoparticles strongly related to the solution pH, precursor salt concentration, time and temperature, etc. However, very few attempts have been made in the literature to describe the interaction between the process parameters from statistically designed experiments. Moreover, only one work was done to describe the effect of process variables on particle size [13]. However, the empirical correlation reported can only predict spherical shape particles and the experiments were not designed statistically to evaluate the actual relationship between process variables.

Development of mathematical relationship that combines fundamental properties and empirical quantities derived from statistical analysis can be very useful in understanding the actual effect of process interactions on the particle growth. In a previous work [9], mathematical relation between solvent surface tension and particle growth was reported. However, the effect of various process parameters on the particle growth was not accounted in that model. Hence, in this chapter, an evaluation of the fundamental relationship between solvent surface tension, precursor concentration, time and β-FeOOH nanorod growth is presented via statistically designed experiments.

According to classical electrostatic model, the chemical potential of two phases are equal in equilibrium and can be written as [11, 12]:

$$
\mu\,\_{s}^{o} + KT\ln\mathsf{C}\_{S} = \mu\,\_{L}^{o} + KT\ln\mathsf{C}\_{L} \tag{1}
$$

where μ<sup>o</sup> is the standard chemical potential, C is the concentration of solute (S and L represent solid and liquid phases, respectively), T is the temperature expressed in Kelvin and K is Boltzmann constant. Eq. (2) also known as Coulombs interaction can be used to express the energy required to separate the charged ions from the solid state [11, 12]:

Hydrothermal Precipitation of β-FeOOH Nanoparticles in Mixed Water/Alcohol Solvent http://dx.doi.org/10.5772/intechopen.70503 135

$$
\Delta \mu^o = \frac{Z\_+ Z\_- e^2}{4 \pi \varepsilon\_o \varepsilon (r\_+ + r\_-)} \tag{2}
$$

where ε<sup>o</sup> represents the permittivity in vacuum and ε is dielectric constant of a given solution. r<sup>+</sup> and r� present the radii of ions charged. Based on Eqs. (1) and (2), Chen and Chang [12] proposed the below equation:

$$\frac{2\gamma}{\pi kT\rho} = \ln \mathbb{C} + \frac{Z\_{+} Z\_{-} \varepsilon^{2}}{4\pi \varepsilon\_{o} \varepsilon \text{KT} (r\_{+} + r\_{-})} \tag{3}$$

where m is the weight of the solute molecule; γ is the interfacial energy in J/m<sup>2</sup> , the term interfacial energy can also be written as nm�<sup>1</sup> ; r is the particle size of a spherical particle and C is the solute concentration. The author linearized Eq. (3) in terms of particle size r(Y) and dielectric constant ε(X). It was assumed that only dielectric constant is significant and other properties are insignificant. However, according to Israelachvili [11], Coulombic interaction is much weakened in water. So, it can be postulated that, for homologous mixture of water and alcohol, the Coulombic interaction will be very weak. Hence, it can also be hypothesised that the surface tension of solvent will directly affect the nucleation and growth of particles.

#### 2. Experimental

can be found in the literature. Submicrometer ZrO2 nanomaterial was synthesised by Hu and Chen [6] using alcohol/water mixture. Fang and Chen [7] used a mixed solvent of water/ n-propanol to synthesise titania powders. ZrO2(Y2O3) nanoparticles were synthesised by Li and Gao [8] using ethanol/water mixture. So far, the effect of mixed solvent properties on the growth of 1D β-FeOOH nanorods were not evaluated despite of its numerical industrial and scientific applications. In our previous work, we have demonstrated that alcohol played an important role in controlling nucleation rate and particle size of 1D β-FeOOH nanoparticles [9, 10]. Previously reported work in the literature considered the dielectric constant, ε, properties of the water/alcohol mixture to be of significance in controlling particle growth, discarding the effect of surface tension, γ. However, it is interesting to note that the Coulomb interaction is very weak in water and solvent with high ε [11] and Coulomb interaction is directly related to ε of the solvent. This simple phenomenon makes the application of the ε of

solvent only to relate to particle growths as described in the literature susceptible.

statistically to evaluate the actual relationship between process variables.

μo

energy required to separate the charged ions from the solid state [11, 12]:

designed experiments.

134 Advanced Chemical Kinetics

equilibrium and can be written as [11, 12]:

The application of mixed solvent is a new approach in the synthesis and processing of materials [12]. However, the role of surface tension is neglected when relating particle growth with solvent properties. Tuning the surface tension of the water/alcohol can affect the colloidal interaction between solid particles. Most of the literature reported on the use of alcohol/water mixture on the precipitation of submicro meter-sized TiO2, ZrO2, SiO2 and CeO2 particles. Published literature provides evidence that the formation of nanoparticles strongly related to the solution pH, precursor salt concentration, time and temperature, etc. However, very few attempts have been made in the literature to describe the interaction between the process parameters from statistically designed experiments. Moreover, only one work was done to describe the effect of process variables on particle size [13]. However, the empirical correlation reported can only predict spherical shape particles and the experiments were not designed

Development of mathematical relationship that combines fundamental properties and empirical quantities derived from statistical analysis can be very useful in understanding the actual effect of process interactions on the particle growth. In a previous work [9], mathematical relation between solvent surface tension and particle growth was reported. However, the effect of various process parameters on the particle growth was not accounted in that model. Hence, in this chapter, an evaluation of the fundamental relationship between solvent surface tension, precursor concentration, time and β-FeOOH nanorod growth is presented via statistically

According to classical electrostatic model, the chemical potential of two phases are equal in

where μ<sup>o</sup> is the standard chemical potential, C is the concentration of solute (S and L represent solid and liquid phases, respectively), T is the temperature expressed in Kelvin and K is Boltzmann constant. Eq. (2) also known as Coulombs interaction can be used to express the

<sup>L</sup> þ KT lnCL (1)

<sup>S</sup> <sup>þ</sup> KT lnCS <sup>¼</sup> <sup>μ</sup><sup>o</sup>

#### 2.1. Materials and method

Analytical-grade FeCl3�6H2O and NH4OH (B & M Scientific, Cape Town, R.S.A) were used as they are without any further purification. Deionised water and alcohol (methanol, ethanol and propanol) were mixed together with different ratios to vary the surface tension of solvent. Ammonium hydroxide, NH4OH, was added drop wise until the mixture pH reached a value of 10. A certain amount of FeCl3�6H2O was added to the solution to make up 0.05 M solution (unless stated otherwise), and the solution was stirred until the iron salt was dissolved. The pH of the final solution (prior to heating) was recorded. The pH was always kept constant at ~2 to isolate the effect of pH on the particle growth in each case. The solution was replaced in a teflon-lined pressure autoclave. The temperature was 100�C. A reaction time of 2 h was used to synthesise the particles.

#### 3. Results and discussion

#### 3.1. Correlation between particle size and alcohol surface tension

Three different alcohols (methanol, ethanol and propanol) were used to tune the surface tension of the solvent. If the hypothesis conceived earlier is true, then there will be a qualitative relationship between particle size, De, and surface tension of solvent, γ. The particles synthesised in this study were rod-shaped particles. The length and diameter of the particles were measured from TEM images. A minimum number of 250 particles was counted for

Figure 1. Correlation between particle size and solvent surface tension.

statistical purpose. The equivalent diameter of the rod-shaped particles was calculated using Huebscher formula to evaluate the role of surface tension on particle size [14]:

$$D\_{\epsilon} = 1.30 \times \left[ \frac{(a \times b)^{0.625}}{(a+b)^{0.25}} \right] \tag{4}$$

were omitted from the factorial trial for simplicity sake. Furthermore, butanol was used as solvent to synthesise β-FeOOH particles to validate the relations between particle growth and solvent surface tension. Table 1 presents the real amount of each parameters that have been used at low and high levels, which is assigned by a positive (+) and negative () sign,

Factors Low level () High level (+)

Hydrothermal Precipitation of β-FeOOH Nanoparticles in Mixed Water/Alcohol Solvent

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137

A: FeCl3 concentration [M] 0.05 0.5 B: % solvent to water ratio 30 90 C: Time (h) 2 12

Table 1. Real amount of each factor used in the factorial trial experiments.

3.3. Evaluation of the effects of factors and the interaction between the factors on particle

Table 2 presents the obtained equivalent diameter at different experimental conditions according to the two level three factor factorial design. A Pareto chart is presented in Figure 2 to assess the interaction between process parameters and obtained equivalent diameter of the particles. The factorial design can cover the main and interaction effects of the parameters within the whole range of selected parameters. Evaluation of the effect of principal factors revealed that these parameters have positive effects on the obtained equivalent diameters of

Based on the significance of effects from Figure 2, a generalised empirical correlation that takes

Samples FeCl3 concentration [M] % alcohol to water ratio used as solvent Time (h) De 0.5 90 2 17 0.05 30 12 17 0.5 30 12 90 0.05 30 2 16 0.5 90 12 43 0.05 90 12 16 0.05 90 2 15 0.50 90 2 7

solvent surface tension, precursor concentration and time into account is proposed:

respectively.

the particles.

Table 2. Results obtained for a two level factorial design.

growth

where a and b are the measured diameter and length of the particles in this study. It can be seen from Figure 1 that there is a linear relationship that holds approximately independent of the nature of the alcohol used to synthesise the particles. This illustration proves the point that the surface tension of the mixed solvent can also be used to relate nucleation and growth.

#### 3.2. A generic correlation to predict particle growth

Statistically designed experiments are effective optimising tools where the process is influenced by various external factors. In this chapter, a two level three factor factorial design was used to evaluate the effect of interaction of various parameters that have been manipulated during the synthesis of β-FeOOH particles. Previous work [9, 10] has shown that the particle phase is very sensitive to reaction temperatures and pH. Hence, reaction temperature and pH


Table 1. Real amount of each factor used in the factorial trial experiments.

were omitted from the factorial trial for simplicity sake. Furthermore, butanol was used as solvent to synthesise β-FeOOH particles to validate the relations between particle growth and solvent surface tension. Table 1 presents the real amount of each parameters that have been used at low and high levels, which is assigned by a positive (+) and negative () sign, respectively.

#### 3.3. Evaluation of the effects of factors and the interaction between the factors on particle growth

Table 2 presents the obtained equivalent diameter at different experimental conditions according to the two level three factor factorial design. A Pareto chart is presented in Figure 2 to assess the interaction between process parameters and obtained equivalent diameter of the particles. The factorial design can cover the main and interaction effects of the parameters within the whole range of selected parameters. Evaluation of the effect of principal factors revealed that these parameters have positive effects on the obtained equivalent diameters of the particles.

Based on the significance of effects from Figure 2, a generalised empirical correlation that takes solvent surface tension, precursor concentration and time into account is proposed:


Table 2. Results obtained for a two level factorial design.

statistical purpose. The equivalent diameter of the rod-shaped particles was calculated using

De <sup>¼</sup> <sup>1</sup>:<sup>30</sup> � ð Þ <sup>a</sup> � <sup>b</sup> <sup>0</sup>:<sup>625</sup>

where a and b are the measured diameter and length of the particles in this study. It can be seen from Figure 1 that there is a linear relationship that holds approximately independent of the nature of the alcohol used to synthesise the particles. This illustration proves the point that the surface tension of the mixed solvent can also be used to relate nucleation and

Statistically designed experiments are effective optimising tools where the process is influenced by various external factors. In this chapter, a two level three factor factorial design was used to evaluate the effect of interaction of various parameters that have been manipulated during the synthesis of β-FeOOH particles. Previous work [9, 10] has shown that the particle phase is very sensitive to reaction temperatures and pH. Hence, reaction temperature and pH

ð Þ <sup>a</sup> <sup>þ</sup> <sup>b</sup> <sup>0</sup>:<sup>25</sup> " #

(4)

Huebscher formula to evaluate the role of surface tension on particle size [14]:

3.2. A generic correlation to predict particle growth

Figure 1. Correlation between particle size and solvent surface tension.

growth.

136 Advanced Chemical Kinetics

Figure 2. Estimated effects of factors on particle aspect ratio using factorial design.

$$Y = \mathfrak{P}\_o \gamma + \sum\_{i=A} \mathfrak{P}\_i \mathcal{X}\_i + \sum\_{i=A} \sum\_{j=A \neq i} \mathfrak{P}\_{ij} \mathcal{X}\_i \mathcal{X}\_j \tag{5}$$

4. Conclusion

and (b) butanol solvents.

Interaction between solvent surface tension and various process parameters on the synthesis of different β-FeOOH morphology has been evaluated for the first time assuming the presence of low Coulombic interaction. A linear relationship was found between particle size and surface tension of the solvent. Statistically designed experiments were performed to evaluate the

Figure 3. Typical comparison between experimental data and predicted value using different β<sup>i</sup> constants for ethanol (a)

Hydrothermal Precipitation of β-FeOOH Nanoparticles in Mixed Water/Alcohol Solvent

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139

where Y is the predicted response (De in this case), Xi is the un-coded or coded values of the factors (FeCl3 concentration denoted by A, % alcohol to water ratio is denoted by B and time is denoted by C), β<sup>o</sup> and β<sup>i</sup> are constant and γ is the surface tension of alcohol used. The corresponding response model for the obtained aspect ratio of the particles, which are valid for un-coded factor, is:

$$\text{Y} = 0.39\text{y} + \text{j} [A] + 0.047[B] - 0.38856[C] - 1.8[A^\*B] + 5.05[A^\*C] + 0.004[B^\*C] \tag{6}$$

Linear regression can be used to obtain corresponding values of βi. Figure 3 presents typical comparison of experimental and predicted values using different β<sup>i</sup> values. It can be seen from Figure 3 that the comparison between experimental and predicted values agrees very well.

Hydrothermal Precipitation of β-FeOOH Nanoparticles in Mixed Water/Alcohol Solvent http://dx.doi.org/10.5772/intechopen.70503 139

Figure 3. Typical comparison between experimental data and predicted value using different β<sup>i</sup> constants for ethanol (a) and (b) butanol solvents.

#### 4. Conclusion

<sup>Y</sup> <sup>¼</sup> <sup>β</sup>o<sup>γ</sup> <sup>þ</sup><sup>X</sup>

Figure 2. Estimated effects of factors on particle aspect ratio using factorial design.

for un-coded factor, is:

138 Advanced Chemical Kinetics

i¼A

<sup>β</sup>iXi <sup>þ</sup><sup>X</sup> i¼A

where Y is the predicted response (De in this case), Xi is the un-coded or coded values of the factors (FeCl3 concentration denoted by A, % alcohol to water ratio is denoted by B and time is denoted by C), β<sup>o</sup> and β<sup>i</sup> are constant and γ is the surface tension of alcohol used. The corresponding response model for the obtained aspect ratio of the particles, which are valid

Linear regression can be used to obtain corresponding values of βi. Figure 3 presents typical comparison of experimental and predicted values using different β<sup>i</sup> values. It can be seen from Figure 3 that the comparison between experimental and predicted values agrees very well.

Y ¼ 0:39γ þ βi A½ �þ 0:047½ �� B 0:38856½ �� C 1:8 A� ½ �þ B 5:05 A� ½ �þ C 0:004 B� ½ � C (6)

X j¼A6¼i

βijXiXj (5)

Interaction between solvent surface tension and various process parameters on the synthesis of different β-FeOOH morphology has been evaluated for the first time assuming the presence of low Coulombic interaction. A linear relationship was found between particle size and surface tension of the solvent. Statistically designed experiments were performed to evaluate the interaction between particle growth and process parameters. A generic correlation has been developed to predict particle growth. The correlation can be extended further to predict particle size of other type of materials. The results obtained in this work clearly indicate that the application of only dielectric constant to relate particle nucleation and growth is not adequate. A combination of surface tension and dielectric constant together will be appropriate.

[5] Shao H-F, Qian X-F, Yin J, Zhu Z-K. Controlled morphology synthesis of β-FeOOH and the phase transition to Fe2O3. Journal of Solid State Chemistry. 2005;178:3130-3136 [6] Hu Y, Chen K. Crystal splitting in the growth of β-FeO(OH). Journal of Crystal Growth.

Hydrothermal Precipitation of β-FeOOH Nanoparticles in Mixed Water/Alcohol Solvent

http://dx.doi.org/10.5772/intechopen.70503

141

[7] Fang C-S, Chen Y-W. Preparation of titania particles by thermal hydrolysis of TiCl4 in

[8] Li W, Gao L. Nano ZrO2 (Y2O3) particles processing by heating of ethanol–aqueous salt

[9] Chowdhury M, Fester V, Kale G. Growth kinetics evaluation of hydrothermally synthe-

[10] Chowdhury M, Fester V, Kale G, Cespedes O. Hydrothermal precipitation of β-FeOOH nanostructure(s) in mixed solvent: Study of their morphological and structural evolution.

[11] Israelachvili JN. 3—Strong Intermolecular Forces: Covalent and Coulomb Interactions, Intermolecular and Surface Forces. 3rd ed. San Diego: Academic Press; 2011. pp. 53-70

[12] Chen H-I, Chang H-Y. Homogeneous precipitation of cerium dioxide nanoparticles in alcohol/water mixed solvents. Colloids and Surfaces A: Physicochemical and Engineering

[13] Chiu C-A, Hristovski KD, Dockery R, Doudrick K, Westerhoff P. Modeling temperature and reaction time impacts on hematite nanoparticle size during forced hydrolysis of ferric

[14] Yuan Q, Aryanti N, Hou R, Williams RA. Performance of slotted pores in particle manufacture using rotating membrane emulsification. Particuology. 2009;7:114-120

n-propanol solution. Materials Chemistry and Physics. 2003;78:739-745

sized β-FeOOH nanorods. Journal of Crystal Growth. 2014;387:57-65

solutions. Ceramics International. 2001;27:543-546

Journal of Nanoparticle Research. 2014;16:1-11

chloride. Chemical Engineering Journal. 2012;210:357-362

2007;308:185-188

Aspects. 2004;242:61-69

### Acknowledgements

The author would like to thank National Research Foundation of South Africa (Grant no: 88220) for financial support.

### Conflicts of interest

The author declares no conflicts of interest.

### Author details

Mahabubur Chowdhury1,2\*

\*Address all correspondence to: chowdhurym@cput.ac.za

1 Flow Process and Rheology Centre, Cape Peninsula University of Technology, Cape Town, South Africa

2 Department of Chemical Engineering, Cape Peninsula University of Technology, Cape Town, South Africa

### References


[5] Shao H-F, Qian X-F, Yin J, Zhu Z-K. Controlled morphology synthesis of β-FeOOH and the phase transition to Fe2O3. Journal of Solid State Chemistry. 2005;178:3130-3136

interaction between particle growth and process parameters. A generic correlation has been developed to predict particle growth. The correlation can be extended further to predict particle size of other type of materials. The results obtained in this work clearly indicate that the application of only dielectric constant to relate particle nucleation and growth is not adequate.

The author would like to thank National Research Foundation of South Africa (Grant no:

1 Flow Process and Rheology Centre, Cape Peninsula University of Technology, Cape Town,

[1] Wei C, Nan Z. Effects of experimental conditions on one-dimensional single-crystal nanostructure of β-FeOOH. Materials Chemistry and Physics. 2011;127:220-226

[2] Chen M, Jiang J, Zhou X, Diao G. Preparation of akaganeite nanorods and their transformation to sphere shape hematite. Journal of Nanoscience and Nanotechnology. 2008;8:

[3] Chen L, Yang X, Chen J, Liu J, Wu H, Zhan H, Liang C, Wu M. Continuous shape- and spectroscopy-tuning of hematite nanocrystals. Inorganic Chemistry. 2010;49:8411-8420 [4] Kuang D, Xu A, Fang Y, Liu H, Frommen C, Fenske D. Surfactant-assisted growth of novel PbS dendritic nanostructures via facile hydrothermal process. Advanced Materials.

2 Department of Chemical Engineering, Cape Peninsula University of Technology,

A combination of surface tension and dielectric constant together will be appropriate.

Acknowledgements

140 Advanced Chemical Kinetics

88220) for financial support.

Conflicts of interest

Mahabubur Chowdhury1,2\*

Cape Town, South Africa

Author details

South Africa

References

3942-3948

2003;15:1747-1750

The author declares no conflicts of interest.

\*Address all correspondence to: chowdhurym@cput.ac.za


**Chapter 9**

Provisional chapter

**Adsorption, Kinetics and Photoactivity of ZnO-**

DOI: 10.5772/intechopen.70504

Nanocomposites have been attracting more attention in various fields. In this chapter, ZnO-supported fly ash-sepiolite (ZnO-FA-Sep) was prepared as a ternary composite for the evaluation of adsorption capacities and photocatalytic activities. Characterization studies supplied information about the surface morphology variation before and after ZnO loading within the FA-Sep environment. Strong dark adsorption capacities of the supported catalysts improved their photocatalytic performances, in terms of methyl orange (MO) decolorization and degradation processes. This study not only provided important inspirations for developing support materials but also opened new features to

Keywords: supported catalyst, methyl orange, adsorption, kinetics, photocatalysis

Adsorption has been used extensively in industrial processes for separation and purification. Recent research has been focused on the development of low cost adsorbents. Among many alternatives, fly ash cost-effectively improves the performance of products it is added to [1]. Although, significant quantities are being used in a range of applications, it mainly works in tandem with cement in the production of concrete products. However, there is still large amount of fly ash production. An efficient usage of fly ash creates positive environmental impacts. Fly ash use conserves natural resources and avoids landfill disposal of ash products. By making concrete more durable, life cycle costs of roads and structures are reduced. Furthermore, fly ash use partially displaces production of other concrete ingredients, resulting in significant energy

Sepiolite is a natural hydrated magnesium silicate fibrous clay with a composition of Si12Mg8 O30(OH)4(OH2)48H2O. It exhibits high surface area, porosity, good chemical stability and

> © The Author(s). Licensee InTech. 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 eproduction in any medium, provided the original work is properly cited.

© 2018 The Author(s). Licensee InTech. 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.

savings and reductions in water consumption and greenhouse gas emissions.

Adsorption, Kinetics and Photoactivity of ZnO-

**Supported Fly Ash-Sepiolite Ternary Catalyst**

Supported Fly Ash-Sepiolite Ternary Catalyst

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

facilitate the photocatalyts' performances.

http://dx.doi.org/10.5772/intechopen.70504

Ayşe Neren Ökte

Ayşe Neren Ökte

Abstract

1. Introduction

#### **Adsorption, Kinetics and Photoactivity of ZnO-Supported Fly Ash-Sepiolite Ternary Catalyst** Adsorption, Kinetics and Photoactivity of ZnO-Supported Fly Ash-Sepiolite Ternary Catalyst

DOI: 10.5772/intechopen.70504

#### Ayşe Neren Ökte Ayşe Neren Ökte

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.70504

#### Abstract

Nanocomposites have been attracting more attention in various fields. In this chapter, ZnO-supported fly ash-sepiolite (ZnO-FA-Sep) was prepared as a ternary composite for the evaluation of adsorption capacities and photocatalytic activities. Characterization studies supplied information about the surface morphology variation before and after ZnO loading within the FA-Sep environment. Strong dark adsorption capacities of the supported catalysts improved their photocatalytic performances, in terms of methyl orange (MO) decolorization and degradation processes. This study not only provided important inspirations for developing support materials but also opened new features to facilitate the photocatalyts' performances.

Keywords: supported catalyst, methyl orange, adsorption, kinetics, photocatalysis

### 1. Introduction

Adsorption has been used extensively in industrial processes for separation and purification. Recent research has been focused on the development of low cost adsorbents. Among many alternatives, fly ash cost-effectively improves the performance of products it is added to [1]. Although, significant quantities are being used in a range of applications, it mainly works in tandem with cement in the production of concrete products. However, there is still large amount of fly ash production. An efficient usage of fly ash creates positive environmental impacts. Fly ash use conserves natural resources and avoids landfill disposal of ash products. By making concrete more durable, life cycle costs of roads and structures are reduced. Furthermore, fly ash use partially displaces production of other concrete ingredients, resulting in significant energy savings and reductions in water consumption and greenhouse gas emissions.

Sepiolite is a natural hydrated magnesium silicate fibrous clay with a composition of Si12Mg8 O30(OH)4(OH2)48H2O. It exhibits high surface area, porosity, good chemical stability and

Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited.

mechanical behavior [2, 3]. Its applications focused on the use as additives and adsorbents. The crystalline structure is composed of alternating silicate blocks and cavities. The presence of silanol groups (Si-OH) makes use of sepiolite as a support for metals and metal oxide nanoparticles [4].

Na2CO3 solution under vigorous stirring for 2 h at room temperature. The resulting product was collected by centrifugation, washed with deionized water several times, dried at 100�C overnight and calcined at 500�C. Finally, the samples were designated as 0.125 M ZnO, 0.25 M

Adsorption, Kinetics and Photoactivity of ZnO-Supported Fly Ash-Sepiolite Ternary Catalyst

http://dx.doi.org/10.5772/intechopen.70504

145

Raw Sep and FA used as supports in this study were obtained from Eskişehir-region of Anatolia and Soma (Turkey), respectively. They were characterized by X-ray diffraction and SEM-EDX analyses [18, 19]. Supported catalysts were prepared with the addition of FA-Sep dispersions (1:1 w/w, stirred about 12 h) into the above-mentioned ZnO solutions. The resulting product was collected by centrifugation, washed with deionized water for several times, dried at 100�C overnight and calcined at 500�C. Finally, the catalysts were designated as

X-ray diffraction patterns were recorded on an X-ray diffractometer (Rigaku-D/MAX-Ultimadiffractometer, 40 kV, and 40 mA) equipped with graphite monochromatized Cu-Kα1 radiation

pores size were determined from the nitrogen adsorption apparatus (Quantachrome Nova 2200e) at 77 K. Prior to the measurements, the samples were pretreated in a vacuum at 473 K for 24 h. The morphology of the products was investigated by scanning electron microscopy (ESEM-FEG/EDAX Philips XL-30) running at an accelerating voltage of 20 kV. The elemental composition of the composites was determined by energy dispersive X-ray spectroscopy (EDS). X-ray photoelectron spectroscopy (XPS) data were recorded with a Thermo Scientific K-Alpha Photoelectron Spectrometer using Al Kα (12.5 kV) X-ray source. Calibration of the instrument was done via carbon peak [21, 22]. UV-visible (UV-vis) absorption spectra were recorded with a Shimadzu UV-2450. Diffuse reflectance measurements (DRS) were recorded by using an inte-

The photodegradation of methyl orange (MO)-probe molecule in this study was carried out at room temperature in a homemade photocatalytic reactor under UV light (Philips TL 15 W/

system included 0.2 g of a catalyst and 200 mL of a known concentration of MO. The suspension was stirred in the dark for 30 min. Thereafter, irradiation was started and UV-vis absorption spectra were recorded to monitor both degradation and decolorization processes. The decrease of the band at 274 nm indicated degradation of MO's aromatic moiety while the one at 464 nm was followed for the decolorization of MO solution. All experiments were performed at room temperature and at pH = 8 (3.27 mg L�<sup>1</sup> MO in the presence of 0.5 M ZnO-FA-Sep) without concerning the degradation intermediates. Also, measurements were conducted at least twice and the average value was recorded. The degradation and decolorization rate percentages of

Degradation or decolorization ð Þ% <sup>¼</sup> C0 � <sup>C</sup>

where C0 was the initial concentration of MO and C was the concentration of MO after "t"

C0

. Brunauer-Emmett-Teller (BET)-specific surface area and

) [12, 18]. A typical reaction

� 100 (1)

0.125 M ZnO-FA-Sep, 0.25 M ZnO-FA-Sep and 0.5 M ZnO-FA-Sep.

grated sphere reflectance accessory with BaSO4 reference.

MO were calculated by the following equation:

minutes irradiation.

5BLB, <sup>λ</sup> = 365 nm, an incident photon flux of 4.7 � <sup>10</sup><sup>15</sup> photons s�<sup>1</sup>

ZnO and 0.5 M ZnO.

(λ = 1.54 Å) at a scan rate of 2� min�<sup>1</sup>

ZnO is one of the most promising photocatalysts under the ultraviolet radiation to protect the environment by degradation of organic pollutants in water and air. In general, a photocatalytic reaction starts with the generation of electrons and holes by photoexcitation. Then, these charge carriers migrate to the surface of the photocatalyst and react with adsorbed electron acceptors and donors, respectively. Thus, an efficient photocatalyst requires a suitable band-gap, facile separation and transportation of electrons and holes for the feasibility of potential redox reactions. ZnO with its high photo sensitivity and large bandgap plays a significant role for reduction and oxidation processes. However, usage of ZnO nanoparticles in catalytic slurries alone creates fast charge carrier recombination and requires long-time centrifugation for the removal process. An effective way to overcome these difficulties is to immobilize the ZnO nanoparticles on the inner and outer surfaces of inorganic porous supports with the formation of nanocomposite materials [5, 6]. These materials induce high surface area, large pore volume, good dispersion and strong adsorptivity. A synergetic effect is expected in the coexistence of ZnO and a support which eventually transfer species from the support to ZnO or vice versa by the interface created between two phases. Hence, an increase in reaction rates is expected and ZnO/support composites have been postulated as suitable alternative photocatalysts in environmental applications.

The adsorption on the cenospheres and/or plerospheres of fly ashes makes use of them as ideal support materials. Synthesis, characterization, adsorption property and photoactivity of ZnO- or TiO2-loaded fly ash composites are recently examined for anti-corrosion in coatings and also degradation of inorganic and organic pollutants to provide additional way to utilize the waste fly ash [7–13]. Photoactive ZnO nanoparticles supported on sepiolite are also reported for applications in decontamination of pollutants [14–19]. The immobilization of ZnO nanoparticles can be improved within the sepiolite framework due to the net negative charge of the sepiolite. Thus, charge separation efficiency and high adsorption capability can enhance the removal performance for the photodecomposition of organic pollutants.

This chapter is focused on a ternary photocatalyst; ZnO-supported fly ash-sepiolite (ZnO-FA-Sep) by taking advantage from the above-mentioned unique characteristics of fly ash and sepiolite. This composite can be considered as the first approximation of in situ formation of ZnO nanoparticles in presence of a clay (Sep) and an ash material (FA). With this objective, the as-prepared supported catalysts are characterized, structurally examined and evaluated via adsorption ability, kinetics and photocatalytic performance.

### 2. Preparation and characterization of the photocatalysts

ZnO catalysts were synthesized via a co-precipitation route [20]. In a typical preparation step, 0.5 M (or 0.25 or 0.125 M) Zn(NO3)26H2O was added gradually to 0.5 M (or 0.25 or 0.125 M) Na2CO3 solution under vigorous stirring for 2 h at room temperature. The resulting product was collected by centrifugation, washed with deionized water several times, dried at 100�C overnight and calcined at 500�C. Finally, the samples were designated as 0.125 M ZnO, 0.25 M ZnO and 0.5 M ZnO.

mechanical behavior [2, 3]. Its applications focused on the use as additives and adsorbents. The crystalline structure is composed of alternating silicate blocks and cavities. The presence of silanol groups (Si-OH) makes use of sepiolite as a support for metals and metal oxide

ZnO is one of the most promising photocatalysts under the ultraviolet radiation to protect the environment by degradation of organic pollutants in water and air. In general, a photocatalytic reaction starts with the generation of electrons and holes by photoexcitation. Then, these charge carriers migrate to the surface of the photocatalyst and react with adsorbed electron acceptors and donors, respectively. Thus, an efficient photocatalyst requires a suitable band-gap, facile separation and transportation of electrons and holes for the feasibility of potential redox reactions. ZnO with its high photo sensitivity and large bandgap plays a significant role for reduction and oxidation processes. However, usage of ZnO nanoparticles in catalytic slurries alone creates fast charge carrier recombination and requires long-time centrifugation for the removal process. An effective way to overcome these difficulties is to immobilize the ZnO nanoparticles on the inner and outer surfaces of inorganic porous supports with the formation of nanocomposite materials [5, 6]. These materials induce high surface area, large pore volume, good dispersion and strong adsorptivity. A synergetic effect is expected in the coexistence of ZnO and a support which eventually transfer species from the support to ZnO or vice versa by the interface created between two phases. Hence, an increase in reaction rates is expected and ZnO/support composites have been postulated as suitable alternative photocatalysts in environmental applications.

The adsorption on the cenospheres and/or plerospheres of fly ashes makes use of them as ideal support materials. Synthesis, characterization, adsorption property and photoactivity of ZnO- or TiO2-loaded fly ash composites are recently examined for anti-corrosion in coatings and also degradation of inorganic and organic pollutants to provide additional way to utilize the waste fly ash [7–13]. Photoactive ZnO nanoparticles supported on sepiolite are also reported for applications in decontamination of pollutants [14–19]. The immobilization of ZnO nanoparticles can be improved within the sepiolite framework due to the net negative charge of the sepiolite. Thus, charge separation efficiency and high adsorption capability can enhance

This chapter is focused on a ternary photocatalyst; ZnO-supported fly ash-sepiolite (ZnO-FA-Sep) by taking advantage from the above-mentioned unique characteristics of fly ash and sepiolite. This composite can be considered as the first approximation of in situ formation of ZnO nanoparticles in presence of a clay (Sep) and an ash material (FA). With this objective, the as-prepared supported catalysts are characterized, structurally examined and evaluated via

ZnO catalysts were synthesized via a co-precipitation route [20]. In a typical preparation step, 0.5 M (or 0.25 or 0.125 M) Zn(NO3)26H2O was added gradually to 0.5 M (or 0.25 or 0.125 M)

the removal performance for the photodecomposition of organic pollutants.

adsorption ability, kinetics and photocatalytic performance.

2. Preparation and characterization of the photocatalysts

nanoparticles [4].

144 Advanced Chemical Kinetics

Raw Sep and FA used as supports in this study were obtained from Eskişehir-region of Anatolia and Soma (Turkey), respectively. They were characterized by X-ray diffraction and SEM-EDX analyses [18, 19]. Supported catalysts were prepared with the addition of FA-Sep dispersions (1:1 w/w, stirred about 12 h) into the above-mentioned ZnO solutions. The resulting product was collected by centrifugation, washed with deionized water for several times, dried at 100�C overnight and calcined at 500�C. Finally, the catalysts were designated as 0.125 M ZnO-FA-Sep, 0.25 M ZnO-FA-Sep and 0.5 M ZnO-FA-Sep.

X-ray diffraction patterns were recorded on an X-ray diffractometer (Rigaku-D/MAX-Ultimadiffractometer, 40 kV, and 40 mA) equipped with graphite monochromatized Cu-Kα1 radiation (λ = 1.54 Å) at a scan rate of 2� min�<sup>1</sup> . Brunauer-Emmett-Teller (BET)-specific surface area and pores size were determined from the nitrogen adsorption apparatus (Quantachrome Nova 2200e) at 77 K. Prior to the measurements, the samples were pretreated in a vacuum at 473 K for 24 h. The morphology of the products was investigated by scanning electron microscopy (ESEM-FEG/EDAX Philips XL-30) running at an accelerating voltage of 20 kV. The elemental composition of the composites was determined by energy dispersive X-ray spectroscopy (EDS). X-ray photoelectron spectroscopy (XPS) data were recorded with a Thermo Scientific K-Alpha Photoelectron Spectrometer using Al Kα (12.5 kV) X-ray source. Calibration of the instrument was done via carbon peak [21, 22]. UV-visible (UV-vis) absorption spectra were recorded with a Shimadzu UV-2450. Diffuse reflectance measurements (DRS) were recorded by using an integrated sphere reflectance accessory with BaSO4 reference.

The photodegradation of methyl orange (MO)-probe molecule in this study was carried out at room temperature in a homemade photocatalytic reactor under UV light (Philips TL 15 W/ 5BLB, <sup>λ</sup> = 365 nm, an incident photon flux of 4.7 � <sup>10</sup><sup>15</sup> photons s�<sup>1</sup> ) [12, 18]. A typical reaction system included 0.2 g of a catalyst and 200 mL of a known concentration of MO. The suspension was stirred in the dark for 30 min. Thereafter, irradiation was started and UV-vis absorption spectra were recorded to monitor both degradation and decolorization processes. The decrease of the band at 274 nm indicated degradation of MO's aromatic moiety while the one at 464 nm was followed for the decolorization of MO solution. All experiments were performed at room temperature and at pH = 8 (3.27 mg L�<sup>1</sup> MO in the presence of 0.5 M ZnO-FA-Sep) without concerning the degradation intermediates. Also, measurements were conducted at least twice and the average value was recorded. The degradation and decolorization rate percentages of MO were calculated by the following equation:

$$\text{Depradation (or deceleration)}\% = \frac{\text{C}\_0 - \text{C}}{\text{C}\_0} \times 100\tag{1}$$

where C0 was the initial concentration of MO and C was the concentration of MO after "t" minutes irradiation.

### 3. Structural characterization

#### 3.1. XRD analysis

XRD patterns of Sep, FA, FA-Sep and the supported catalysts are shown at both low-angle (2θ < 10 ) and high-angle (20 < 2θ < 60 ) ranges (Figure 1A). The characteristic d 1 1 0 reflection of the Sep appears at 7.24 (2θ ) with a basal spacing of 12.19 Å. The pattern of FA includes amorphous aluminosilicate glass (as major) phase. Quartz (SiO2) reflections of d 1 0 0, d 1 0 1 and d 1 1 0 are detected at 20.8, 26.6 and 36.6 (2θ), respectively. Minor constituents of calcite (CaCO3) reflections of d 1 0 1 and d 1 0 4 are observed at 30 and 48 (2θ), respectively. Lime (CaO) reflection at 62 (2θ ) of d 104 is also noticed. For the FA-Sep support, the intensities of d 1 1 0 reflection and all other high angle peaks decrease. Supported catalysts reveal d 1 0 0, d 0 0 2, d 1 0 1, d 1 0 2, d 1 1 0, d 1 0 3 and d 2 0 0 crystal planes of ZnO at 31.9, 34.6, 36.4, 47.7, 56.7, 63.1 and 66.6 (2θ), respectively (JCPDS file no. 36-1451). The peak position and basal spacing of the d 1 1 0 reflection do not change significantly for the FA-Sep and supported catalysts due to the non-expandable nature of the Sep. The ZnO signals are intensified with the increasing loading concentrations while the retained FA-Sep peaks decrease significantly.

Scherrer's equation is used to evaluate ZnO crystalline sizes (DZnO) in the supported catalysts. According to the d 1 0 1 reflection of ZnO, DZnO values are found as 16.1, 13.1, 9.85 and 11.7 nm for 0.25 M ZnO, 0.125 M ZnO-FA-Sep, 0.25 M ZnO-FA-Sep and 0.5 M ZnO-FA-Sep, respectively (Table 1). Hence, formation of ZnO aggregates is inhibited in the presence of the FA-Sep support. The reduction in the ZnO crystalline sizes in the form of supported catalysts and the decrements in the FA-Sep reflections may suggest distribution of ZnO nanoparticles over the surface and bulk.

3.2. SEM (EDX) analysis

supports and supported catalysts.

a

b

c

d

Catalysts DZnO (nm)a BET (m<sup>2</sup> g<sup>1</sup>

Calculated from the (1 0 1) diffraction peak of ZnO using the Scherrer equation.

Determined from cumulative adsorption pore volume using BJH method.

Determined from adsorption pore size using BJH method.

Determined from nitrogen adsorption–desorption isotherms using BET equation.

Figure 1B. SEM and mapping images of Sep, FA, FA-Sep and 0.25 M ZnO-FA-Sep.

Figure 1B shows SEM images of Sep, FA, FA-Sep, 0.25 M ZnO-FA-Sep and elemental mapping images of the supported catalyst. The Sep exhibits a wavy pattern among the layers. The FA displays spherical (with air holes) and non-shaped particles. For the FA-Sep, the structures of the Sep and FA are retained with Si, Ca and Al major, Mg and Fe minor constituents. The

Table 1. Crystalline sizes (DZnO), surface areas (BET), total pore volumes (Vpore) and pore radius (Rpore) of 0.25 M ZnO,

)

Adsorption, Kinetics and Photoactivity of ZnO-Supported Fly Ash-Sepiolite Ternary Catalyst

0.25 M ZnO 16.08 7.58 0.012 17.7 FA – 1.80 0.003 14.9 Sep – 104.5 0.140 14.9 FA-Sep – 46.4 0.006 15.6 0.125 M ZnO-FA-Sep 13.11 61.7 0.111 14.9 0.25 M ZnO-FA-Sep 9.85 62.3 0.121 15.4 0.5 M ZnO-FA-Sep 11.66 50.2 0.097 14.8

<sup>b</sup> Vpore (cm3 g<sup>1</sup>

)

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<sup>c</sup> Rpore (Å)<sup>d</sup>

147

Figure 1A. XRD patterns of Sep, FA-Sep and supported catalysts (Z: ZnO).

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a Calculated from the (1 0 1) diffraction peak of ZnO using the Scherrer equation.

b Determined from nitrogen adsorption–desorption isotherms using BET equation.

c Determined from cumulative adsorption pore volume using BJH method.

d Determined from adsorption pore size using BJH method.

Table 1. Crystalline sizes (DZnO), surface areas (BET), total pore volumes (Vpore) and pore radius (Rpore) of 0.25 M ZnO, supports and supported catalysts.

#### 3.2. SEM (EDX) analysis

3. Structural characterization

) and high-angle (20

and d 1 1 0 are detected at 20.8, 26.6 and 36.6

Figure 1A. XRD patterns of Sep, FA-Sep and supported catalysts (Z: ZnO).

of the Sep appears at 7.24

(CaO) reflection at 62

over the surface and bulk.

XRD patterns of Sep, FA, FA-Sep and the supported catalysts are shown at both low-angle

amorphous aluminosilicate glass (as major) phase. Quartz (SiO2) reflections of d 1 0 0, d 1 0 1

(CaCO3) reflections of d 1 0 1 and d 1 0 4 are observed at 30 and 48 (2θ), respectively. Lime

1 1 0 reflection and all other high angle peaks decrease. Supported catalysts reveal d 1 0 0, d 0 0 2, d 1 0 1, d 1 0 2, d 1 1 0, d 1 0 3 and d 2 0 0 crystal planes of ZnO at 31.9, 34.6, 36.4, 47.7, 56.7, 63.1 and 66.6 (2θ), respectively (JCPDS file no. 36-1451). The peak position and basal spacing of the d 1 1 0 reflection do not change significantly for the FA-Sep and supported catalysts due to the non-expandable nature of the Sep. The ZnO signals are intensified with the increasing loading concentrations while the retained FA-Sep peaks decrease significantly.

Scherrer's equation is used to evaluate ZnO crystalline sizes (DZnO) in the supported catalysts. According to the d 1 0 1 reflection of ZnO, DZnO values are found as 16.1, 13.1, 9.85 and 11.7 nm for 0.25 M ZnO, 0.125 M ZnO-FA-Sep, 0.25 M ZnO-FA-Sep and 0.5 M ZnO-FA-Sep, respectively (Table 1). Hence, formation of ZnO aggregates is inhibited in the presence of the FA-Sep support. The reduction in the ZnO crystalline sizes in the form of supported catalysts and the decrements in the FA-Sep reflections may suggest distribution of ZnO nanoparticles

) ranges (Figure 1A). The characteristic d 1 1 0 reflection

(2θ), respectively. Minor constituents of calcite

(2θ ) with a basal spacing of 12.19 Å. The pattern of FA includes

(2θ ) of d 104 is also noticed. For the FA-Sep support, the intensities of d

< 2θ < 60

3.1. XRD analysis

146 Advanced Chemical Kinetics

(2θ < 10

Figure 1B shows SEM images of Sep, FA, FA-Sep, 0.25 M ZnO-FA-Sep and elemental mapping images of the supported catalyst. The Sep exhibits a wavy pattern among the layers. The FA displays spherical (with air holes) and non-shaped particles. For the FA-Sep, the structures of the Sep and FA are retained with Si, Ca and Al major, Mg and Fe minor constituents. The

Figure 1B. SEM and mapping images of Sep, FA, FA-Sep and 0.25 M ZnO-FA-Sep.

appearance of 0.25 M ZnO-FA-Sep is different from the morphologies of Sep, FA and FA-Sep. The mixed structure of FA spheres and Sep layers suggests hosting of ZnO nanoparticles simultaneously on the spheres and/or non-shaped particles. This is proved by the EDX-spot analysis where Zn percentages are founds as 29 and 69% on the spheres 'a' and 'b' and 66% on the non-shaped particle 'c', respectively. Dominating Zn signals in the mapping images verify the dispersion of ZnO nanoparticles on the FA-Sep support.

FA-Sep and supported catalysts, Type II isotherms are also detected with sites of different affinity to nitrogen and multilayer coverage at high P/P0. Almost similar pore radius is detected for all catalysts and the supports (Table 1). The FA-Sep composite and supported catalysts exhibit lower surface areas and pore volumes in comparison to the Sep. This suggests an increment in the number of hosted FA spheres and/or ZnO nanoparticles. In the meantime, supported catalysts possess higher surface areas and pore volumes than the FA-Sep. Thus, enhanced adsorption capacities and degradation abilities are expected in the existence of the

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UV-vis absorption spectroscopies of the FA, Sep, FA-Sep and supported catalysts are presented in Figure 1E. Absorption profiles of the supports are similar with extensions in between 200 and 600 nm. 0.25 M ZnO shows its characteristic edge below 400 nm. All supported catalysts reveal this edge with a slight blue shift relative to 0.25 M ZnO and longer wavelength tails are not detected. The band gap energies for 0.125 M ZnO-FA-Sep, 0.25 M ZnO-FA-Sep and 0.5 M ZnO-FA-Sep are evaluated by linear extrapolation and taking the intercept on the x-axis as

Figure 1G-I. (G) XPS survey analysis of FA-Sep and 0.5 M ZnO-FA-Sep, (H) Zn 2p XPS spectra of 0.5 M ZnO-FA-Sep, (I)

supported catalysts.

3.4. UV-vis DRS analysis

O 1s XPS spectra of 0.5 M ZnO-FA-Sep.

#### 3.3. Nitrogen adsorption-desorption isotherms

Nitrogen adsorption-desorption isotherms and pore size distributions are shown in Figure 1C and D, respectively. The non-porous FA and 0.25 M ZnO reveal Type II isotherms. For the Sep,

Figure 1C-F. (C) nitrogen adsorption/desorption isotherms of Sep, FA, FA-Sep, 0.25 M ZnO, supported catalysts, (D) pores size distribution plots of Sep, FA, FA-Sep, 0.25 M ZnO, supported catalysts, (E) diffuse reflectance spectra of Sep, FA,FA-Sep, 0.25 M ZnO, supported catalysts, (F) Kubelka-Munk transformed reflectance spectra of supported catalysts.

FA-Sep and supported catalysts, Type II isotherms are also detected with sites of different affinity to nitrogen and multilayer coverage at high P/P0. Almost similar pore radius is detected for all catalysts and the supports (Table 1). The FA-Sep composite and supported catalysts exhibit lower surface areas and pore volumes in comparison to the Sep. This suggests an increment in the number of hosted FA spheres and/or ZnO nanoparticles. In the meantime, supported catalysts possess higher surface areas and pore volumes than the FA-Sep. Thus, enhanced adsorption capacities and degradation abilities are expected in the existence of the supported catalysts.

#### 3.4. UV-vis DRS analysis

appearance of 0.25 M ZnO-FA-Sep is different from the morphologies of Sep, FA and FA-Sep. The mixed structure of FA spheres and Sep layers suggests hosting of ZnO nanoparticles simultaneously on the spheres and/or non-shaped particles. This is proved by the EDX-spot analysis where Zn percentages are founds as 29 and 69% on the spheres 'a' and 'b' and 66% on the non-shaped particle 'c', respectively. Dominating Zn signals in the mapping images verify

Nitrogen adsorption-desorption isotherms and pore size distributions are shown in Figure 1C and D, respectively. The non-porous FA and 0.25 M ZnO reveal Type II isotherms. For the Sep,

Figure 1C-F. (C) nitrogen adsorption/desorption isotherms of Sep, FA, FA-Sep, 0.25 M ZnO, supported catalysts, (D) pores size distribution plots of Sep, FA, FA-Sep, 0.25 M ZnO, supported catalysts, (E) diffuse reflectance spectra of Sep, FA,FA-Sep, 0.25 M ZnO, supported catalysts, (F) Kubelka-Munk transformed reflectance spectra of supported catalysts.

the dispersion of ZnO nanoparticles on the FA-Sep support.

3.3. Nitrogen adsorption-desorption isotherms

148 Advanced Chemical Kinetics

UV-vis absorption spectroscopies of the FA, Sep, FA-Sep and supported catalysts are presented in Figure 1E. Absorption profiles of the supports are similar with extensions in between 200 and 600 nm. 0.25 M ZnO shows its characteristic edge below 400 nm. All supported catalysts reveal this edge with a slight blue shift relative to 0.25 M ZnO and longer wavelength tails are not detected. The band gap energies for 0.125 M ZnO-FA-Sep, 0.25 M ZnO-FA-Sep and 0.5 M ZnO-FA-Sep are evaluated by linear extrapolation and taking the intercept on the x-axis as

Figure 1G-I. (G) XPS survey analysis of FA-Sep and 0.5 M ZnO-FA-Sep, (H) Zn 2p XPS spectra of 0.5 M ZnO-FA-Sep, (I) O 1s XPS spectra of 0.5 M ZnO-FA-Sep.

3.10, 3.12 and 3.18 eV, respectively (Figure 1F). Thus, supported catalysts have suitable band gap energies for the degradation of MO under UV-A irradiation.

### 3.5. XPS analysis

XPS analysis is also performed to control the surface structure of the 0.5 M ZnO-FA-Sep. The survey scan reveals Zn peaks in addition to the Al (75.6 eV), Si (103 eV), Ca (347.07 eV), O (531.47 eV) and some Auger peaks of the FA-Sep support (Figure 1G). The doublet in Zn peaks corresponds to Zn 2p3/2 and 2p1/2 core levels (Figure 1H). Zn exists mainly in the form of Zn2+ oxidation state on the catalyst surface owing to the sharpness in Zn 2p3/2 peak [23]. The broad O 1 s signal of the 0.5 M ZnO-FA-Sep catalyst is deconvoluted by four subspectral parts (Figure 1I). CaO and Al2O3 (531.03 eV, 26.9% spectral area), oxygen in the form of Zn(OH)2 (531.69 eV, 18.5% spectral area), SiO2 (532.59 eV, 22.3% spectral area) and adsorbed water (533.58 eV, 32.2% spectral area) are labeled as the components of the supported catalyst.

### 4. Adsorption and photocatalytic applications

#### 4.1. Control experiments

Prior to the evaluation of photoactivities of the supported catalysts in detail, two control experiments are designed. As a first step, photolysis of MO is tested under UV illumination and a negligible degradation is found (Figure 2A). Then, FA-Sep, 0.25 M ZnO-FA-Sep and 0.5 M ZnO-FA-Sep are examined without irradiation. In the presence of FA-Sep, the remaining MO percentages in the solution are detected as 84% for decolorization and 85% for degradation. However, supported catalysts reveal better adsorption capabilities in comparison to FA-Sep, which further enhanced with the ZnO loading concentration. Accordingly, 0.25 M ZnO-FA-Sep demonstrates 75% (for decolorization) and 73% (for degradation) MO staying in solution within 30 min and thereafter no significant change is noticed. Contrarily, 0.5 M ZnO-FA-Sep shows rapid decrements in both decolorization (7%) and degradation (5.3%) processes within 80 min.

MO exists in the anionic form in water since its natural pH (5.85) is higher than its pKa (3.4) value [24]. The alkaline character of FA-Sep (pH = 10) solution, hence, induces repulsive forces among the MO molecules and FA-Sep. However, the weak interaction between positively charged species (Fe2O3, TiO2 as minor phases) within the disordered FA-Sep structure and negatively charged MO moiety induce decrements in MO percentages. The attraction may proceed through the chromophoric (dN]Nd) group and declines the absorption band at 464 nm. Simultaneously, weakening in the conjugation disrupts the benzenic rings and decreases the 274 nm band. The presence of ZnO nanoparticles in the supported matrixes is expected to increase the contact among the supported catalysts and MO molecules which eventually facilitate the degradation and decolorization processes.

0.5 M ZnO-FA-Sep shows the best activity with the lowest MO remaining percentages (15% for decolorization and 12% for degradation) in less than 10 min. Rapid photodegradation of MO is facilitated, due to the synergistic effect of: (1) its adsorption on the mixed structures of FA and

Figure 2. (A) Photolysis of MO and dark adsorption experiments of FA-Sep and supported catalysts, (B) photocatalytic activities of the supported catalysts, (C) MO remaining percentages for decolorization and (D) MO remaining percentages

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Dark adsorption capacity of 0.5 M ZnO-FA-Sep catalyst is also investigated by varying the initial MO concentrations from 3.27 to 32.7 mg L<sup>1</sup> (Figure 2C and D). It is evident that the amount of adsorbed MO at low initial concentrations is smaller than the corresponding amount at higher initial values, while MO removal percentages decrease significantly with increasing initial MO concentration. The highest MO remaining percentages are noticed with 32.7 mg L<sup>1</sup> MO concentration as 73.2 and 71.2% after 120 min for decolorization and degradation processes, respectively. The removal rate of MO is fast up to 30–40 min, and then

Sep, and (2) its photodegradation by the ZnO nanoparticles.

for degradation.

In the second set, the photoactivities of the supported catalysts are controlled under irradiation (Figure 2B). The lowest MO remaining percentages with slower rates are obtained in the presence of 0.125 M ZnO-FA-Sep within 130 min (45% for decolorization and 47% for degradation). The increment in the ZnO concentration improves the performances of the catalysts. Adsorption, Kinetics and Photoactivity of ZnO-Supported Fly Ash-Sepiolite Ternary Catalyst http://dx.doi.org/10.5772/intechopen.70504 151

3.10, 3.12 and 3.18 eV, respectively (Figure 1F). Thus, supported catalysts have suitable band

XPS analysis is also performed to control the surface structure of the 0.5 M ZnO-FA-Sep. The survey scan reveals Zn peaks in addition to the Al (75.6 eV), Si (103 eV), Ca (347.07 eV), O (531.47 eV) and some Auger peaks of the FA-Sep support (Figure 1G). The doublet in Zn peaks corresponds to Zn 2p3/2 and 2p1/2 core levels (Figure 1H). Zn exists mainly in the form of Zn2+ oxidation state on the catalyst surface owing to the sharpness in Zn 2p3/2 peak [23]. The broad O 1 s signal of the 0.5 M ZnO-FA-Sep catalyst is deconvoluted by four subspectral parts (Figure 1I). CaO and Al2O3 (531.03 eV, 26.9% spectral area), oxygen in the form of Zn(OH)2 (531.69 eV, 18.5% spectral area), SiO2 (532.59 eV, 22.3% spectral area) and adsorbed water (533.58 eV, 32.2% spectral area) are labeled as the components of the supported catalyst.

Prior to the evaluation of photoactivities of the supported catalysts in detail, two control experiments are designed. As a first step, photolysis of MO is tested under UV illumination and a negligible degradation is found (Figure 2A). Then, FA-Sep, 0.25 M ZnO-FA-Sep and 0.5 M ZnO-FA-Sep are examined without irradiation. In the presence of FA-Sep, the remaining MO percentages in the solution are detected as 84% for decolorization and 85% for degradation. However, supported catalysts reveal better adsorption capabilities in comparison to FA-Sep, which further enhanced with the ZnO loading concentration. Accordingly, 0.25 M ZnO-FA-Sep demonstrates 75% (for decolorization) and 73% (for degradation) MO staying in solution within 30 min and thereafter no significant change is noticed. Contrarily, 0.5 M ZnO-FA-Sep shows rapid decrements in both decolorization (7%) and degradation (5.3%) processes within 80 min.

MO exists in the anionic form in water since its natural pH (5.85) is higher than its pKa (3.4) value [24]. The alkaline character of FA-Sep (pH = 10) solution, hence, induces repulsive forces among the MO molecules and FA-Sep. However, the weak interaction between positively charged species (Fe2O3, TiO2 as minor phases) within the disordered FA-Sep structure and negatively charged MO moiety induce decrements in MO percentages. The attraction may proceed through the chromophoric (dN]Nd) group and declines the absorption band at 464 nm. Simultaneously, weakening in the conjugation disrupts the benzenic rings and decreases the 274 nm band. The presence of ZnO nanoparticles in the supported matrixes is expected to increase the contact among the supported catalysts and MO molecules which

In the second set, the photoactivities of the supported catalysts are controlled under irradiation (Figure 2B). The lowest MO remaining percentages with slower rates are obtained in the presence of 0.125 M ZnO-FA-Sep within 130 min (45% for decolorization and 47% for degradation). The increment in the ZnO concentration improves the performances of the catalysts.

gap energies for the degradation of MO under UV-A irradiation.

4. Adsorption and photocatalytic applications

eventually facilitate the degradation and decolorization processes.

3.5. XPS analysis

150 Advanced Chemical Kinetics

4.1. Control experiments

Figure 2. (A) Photolysis of MO and dark adsorption experiments of FA-Sep and supported catalysts, (B) photocatalytic activities of the supported catalysts, (C) MO remaining percentages for decolorization and (D) MO remaining percentages for degradation.

0.5 M ZnO-FA-Sep shows the best activity with the lowest MO remaining percentages (15% for decolorization and 12% for degradation) in less than 10 min. Rapid photodegradation of MO is facilitated, due to the synergistic effect of: (1) its adsorption on the mixed structures of FA and Sep, and (2) its photodegradation by the ZnO nanoparticles.

Dark adsorption capacity of 0.5 M ZnO-FA-Sep catalyst is also investigated by varying the initial MO concentrations from 3.27 to 32.7 mg L<sup>1</sup> (Figure 2C and D). It is evident that the amount of adsorbed MO at low initial concentrations is smaller than the corresponding amount at higher initial values, while MO removal percentages decrease significantly with increasing initial MO concentration. The highest MO remaining percentages are noticed with 32.7 mg L<sup>1</sup> MO concentration as 73.2 and 71.2% after 120 min for decolorization and degradation processes, respectively. The removal rate of MO is fast up to 30–40 min, and then gradually decreases with the increase in contact time due to the saturation on the catalyst surface. Contrarily, the lowest MO percentages (around 10% for decolorization and 16% for degradation) are obtained within 60 min for 3.27 mg L�<sup>1</sup> initial MO concentration. Although surface active sites are more available, very fast adsorption rate and short extraction time are achieved for lower MO concentrations.

#### 4.2. Adsorption equilibrium and kinetics

The isotherm analysis of the equilibrium data is examined by fitting the experimental data to Langmuir, Freundlich, Temkin and Dubinin and Radushkevich (D-R) isotherms to find the suitable model [25–31].

Langmuir isotherm: Langmuir isotherm assumes that the adsorption takes place at a specific homogeneous site within the adsorbent, all sites are equivalent, and there are no inteactions among the adsorbate molecules. The isotherm can be presented by the following equation [32]:

$$\mathbf{q}\_{\mathbf{e}} = \frac{\mathbf{K}\_{\text{L}} \mathbf{a}\_{\text{L}} \mathbf{C}\_{\text{e}}}{1 + \mathbf{a}\_{\text{L}} \mathbf{C}\_{\text{e}}} \tag{2}$$

Figure 3. (A) Langmuir isotherm, (B) Freundlich isotherm, (C) Temkin isotherm, (D) Dubinin-Radushkevich isotherm.

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KL 10.84 8.41 aL 0.225 0.294 qm 48.18 28.6 R<sup>2</sup> 0.917 0.858

KF 2.14 3.02 1/n 0.45 0.35 R<sup>2</sup> 0.864 0.652

KT 4.62 1.79 BT 1.89 2.29 R<sup>2</sup> 0.567 0.782

qm 8.12 1.79 E 0.79 0.91 R<sup>2</sup> 0.826 0.667

Langmuir

Freundlich

Temkin

Dubinin-Radushkevich

Table 2. Adsorption isotherm constants.

Decolorization Degradation

where KL is the adsorption capacity and aL is the energy of adsorption. Eq. (3) presents the linearized form of Langmuir isotherm. Figure 3A supplies data about the KL (from the yintercept) and aL (from the slope) values

$$\frac{1}{\mathbf{q}\_{\text{e}}} = \frac{1}{\mathbf{K}\_{\text{L}}\mathbf{a}\_{\text{L}}\mathbf{C}\_{\text{e}}} + \frac{1}{\mathbf{K}\_{\text{L}}} \tag{3}$$

The theoretical maximum monolayer adsorption capacity of 0.5 M ZnO-FA-Sep, qm (mg g�<sup>1</sup> ), is also calculated as 48.8 and 28.6 mg g�<sup>1</sup> from the ratio of KL to aL for the decolorization and degradation processes, respectively (Table 2).

The separation factor RL (dimensionless constant) indicates the favorable adsorption within 0– 1 range [33] and depending on aL and C0 values as:

$$R\_L = \frac{1}{1 + \mathbf{a}\_L \mathbf{C}\_0} \tag{4}$$

The RL values in the MO concentration range of 3.27–32.7 mg L�<sup>1</sup> are found to vary in between 0.58–0.12 and 0.51–0.094 for decolorization and degradation, respectively.

The correlation coefficients (0.917 for decolorization and 0.858 for degradation) are reasonable to suggest the applicability of the Langmuir model for the interpretation of the experimental data over the whole concentration range.

Freundlich isotherm: Freundlich isotherm predicts heterogeneous adsorption surface and active sites with different energy [34] and presented by the following equation [26] and Figure 3B.

$$\mathbf{q}\_{\mathbf{e}} = \mathbf{K}\_{\mathbf{f}} \mathbf{C}\_{\mathbf{e}}^{1/\mathbf{n}} \tag{5}$$

Adsorption, Kinetics and Photoactivity of ZnO-Supported Fly Ash-Sepiolite Ternary Catalyst http://dx.doi.org/10.5772/intechopen.70504 153

Figure 3. (A) Langmuir isotherm, (B) Freundlich isotherm, (C) Temkin isotherm, (D) Dubinin-Radushkevich isotherm.


Table 2. Adsorption isotherm constants.

gradually decreases with the increase in contact time due to the saturation on the catalyst surface. Contrarily, the lowest MO percentages (around 10% for decolorization and 16% for degradation) are obtained within 60 min for 3.27 mg L�<sup>1</sup> initial MO concentration. Although surface active sites are more available, very fast adsorption rate and short extraction time are

The isotherm analysis of the equilibrium data is examined by fitting the experimental data to Langmuir, Freundlich, Temkin and Dubinin and Radushkevich (D-R) isotherms to find the

Langmuir isotherm: Langmuir isotherm assumes that the adsorption takes place at a specific homogeneous site within the adsorbent, all sites are equivalent, and there are no inteactions among the adsorbate molecules. The isotherm can be presented by the following equation [32]:

> qe <sup>¼</sup> KLaLCe 1 þ aLCe

where KL is the adsorption capacity and aL is the energy of adsorption. Eq. (3) presents the linearized form of Langmuir isotherm. Figure 3A supplies data about the KL (from the y-

> þ 1 KL

1 qe <sup>¼</sup> <sup>1</sup> KLaLCe

The theoretical maximum monolayer adsorption capacity of 0.5 M ZnO-FA-Sep, qm (mg g�<sup>1</sup>

is also calculated as 48.8 and 28.6 mg g�<sup>1</sup> from the ratio of KL to aL for the decolorization and

The separation factor RL (dimensionless constant) indicates the favorable adsorption within 0–

RL <sup>¼</sup> <sup>1</sup>

0.58–0.12 and 0.51–0.094 for decolorization and degradation, respectively.

The RL values in the MO concentration range of 3.27–32.7 mg L�<sup>1</sup> are found to vary in between

The correlation coefficients (0.917 for decolorization and 0.858 for degradation) are reasonable to suggest the applicability of the Langmuir model for the interpretation of the experimental

Freundlich isotherm: Freundlich isotherm predicts heterogeneous adsorption surface and active sites with different energy [34] and presented by the following equation [26] and Figure 3B.

qe ¼ KfCe

<sup>1</sup>=<sup>n</sup> (5)

1 þ aLC0

(2)

(3)

),

(4)

achieved for lower MO concentrations.

suitable model [25–31].

152 Advanced Chemical Kinetics

4.2. Adsorption equilibrium and kinetics

intercept) and aL (from the slope) values

degradation processes, respectively (Table 2).

data over the whole concentration range.

1 range [33] and depending on aL and C0 values as:

where qe is equilibrium concentration (mg g�<sup>1</sup> ), Ce is equilibrium liquid phase concentration (mg L�<sup>1</sup> ) and Kf is adsorption capacity. Adsorption intensity is determined by "n". The values of 1/n are found as 0.451 (for decolorization) and 0.354 (for degradation) indicate high tendency of MO for the adsorption onto the supported catalyst. However, Freundlich model is not suitable to describe the relation between sorbed MO molecules and their equilibrium concentrations owing to the lower correlation coefficients (0.864 for decolorization and 0.652 for degradation).

Temkin isotherm: The heat of adsorption and the adsorption-binding energy relation are explored by the following Temkin equation [35]:

$$\mathbf{q}\_{\rm e} = \frac{\rm RT}{\rm b} \ln \left( \mathbf{K}\_{\rm Te} \mathbf{C}\_{\rm e} \right) \tag{6}$$

are calculated as 0.79 kJ mol�<sup>1</sup> for decolorization and 0.91 kJ mol�<sup>1</sup> for degradation processes, only physical interactions are probable among MO moiety and the supported catalyst. The lower correlation coefficients (R<sup>2</sup> = 0.826 for decolorization and R<sup>2</sup> = 0.667 for degradation)

Adsorption, Kinetics and Photoactivity of ZnO-Supported Fly Ash-Sepiolite Ternary Catalyst

The kinetics of MO adsorption onto 0.5 M ZnO-FA-Sep are studied in terms of pseudo-first order [39], pseudo-second order [40], Elovich [41–43] and intraparticle diffusion [44, 45]

Pseudo-first order model: Pseudo-first order model describes the adsorption rate based on the

dt <sup>¼</sup> k1 qe � qt

where k1 is the pseudo-first order rate constant (min), qe is the adsorption capacity at equilib-

Accordingly, the values of ln(qe�qt) are linearly correlated with t by plot of ln (qe�qt) versus t. The rate constant (k1) and qe can be determined from the slope and intercept of the plot, respectively. The pseudo-first order equation fits well for the first 30 min data and then deviations are noticed. Although rate should be proportional to the first power of MO concentration, the linearity is lost for the higher initial MO concentrations. This may be attributed to the limiting effect of pore diffusion through the adsorption process. For the rapid adsorption of the initial stages, the first order rate constants, k1, decrease with increments in MO concentrations for both decolorization and degradation processes (Table 3). It is also noticed that calculated qe values agree well with the experimental data. The high correlation coefficients show the applicability of pseudo-first order kinetics to the adsorption of MO onto the

Pseudo-second-order equation: The adsorption kinetics may also be described by the pseudo-

dt <sup>¼</sup> k2 qe � qt

where k2 is the second-order rate constant of adsorption. Integrating Eq. (12) for the boundary

þ t qe

<sup>¼</sup> <sup>1</sup> k2q2 e

second order model [40]. The differential equation is given as follows:

conditions of qt = 0 at t = 0 and qt = qt at t = t gives

dqt

t qt

Integrating Eq. (10) for the boundary conditions of qt = 0 at t = 0 and qt = qt at t = t gives

(10)

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155

<sup>2</sup> (12)

(13)

<sup>¼</sup> ln qe � k1t (11)

dqt

ln qe � qt

again represents the poorer fit of the experimental data.

The differential equation of the model is expressed as follows:

rium and qt is the adsorption capacity at time t.

models.

adsorption capacity [39].

supported catalyst.

Eq. (6) can be linearized as

$$\mathbf{q}\_{\rm le} = \mathbf{B}\_{\rm T} \ln \mathbf{K}\_{\rm T} + \mathbf{B}\_{\rm T} \ln \mathbf{C}\_{\rm e} \tag{7}$$

where KTe is equilibrium binding constant (L mg�<sup>1</sup> ), b is the heat of adsorption (J mol�<sup>1</sup> ), BT is related to the heat of adsorption as being equal to RT/b, R is the gas constant and T is the temperature (K). The values of Temkin constants (KTe = 4.62 and BT = 1.89 for decolorization and KTe = 1.79 and BT = 2.29 for degradation) and correlation coefficients (R2 = 0.567 for decolorization and R2 = 0.782 for degradation) are found to be lower than the Langmuir values (Table 2, Figure 3C). Thus, Temkin model does not fit to the corresponding experimental data of MO adsorption on 0.5 M ZnO-FA-Sep.

Dubinin-Radushkevich (D-R) isotherm: Dubinin-Radushkevich model is based on heterogeneous surfaces, different sorption sites and steric hindrance effect among adsorbed molecules and bulk species [36]. The linear form of D-R isotherm is expressed by the following equation [31]:

$$
\ln \mathbf{q}\_{\mathbf{e}} = \ln \mathbf{q}\_{\mathbf{m}} - \beta \varepsilon^2 \tag{8}
$$

where qe is the amount of adsorbate per unit weight of adsorbent (mg g�<sup>1</sup> ), qm is the maximum adsorption capacity (mg g�<sup>1</sup> ), β is a coefficient for adsor ption mean free energy (mol<sup>2</sup> J �2 ) and ε is the Polanyi potential (ε = RT ln(1 + 1/Ce)).

The qm values are found using the intercept of the plot as 8.12 and 7.02 mg g�<sup>1</sup> for decolorization and degradation, respectively (Table 2, Figure 3D).

The adsorption mean free energy (E; kJ mol�<sup>1</sup> ) can be found from the slope as follows

$$\mathbf{E} = \frac{1}{\sqrt{-2\beta}}\tag{9}$$

Its value gives information about adsorption mechanism whether it is physical or chemical. If it lies between 8 and 16 kJ mol�<sup>1</sup> , the adsorption process takes place chemically and while E < 8 kJ mol�<sup>1</sup> , the adsorption process proceeds physically [37, 38]. Since adsorption energies are calculated as 0.79 kJ mol�<sup>1</sup> for decolorization and 0.91 kJ mol�<sup>1</sup> for degradation processes, only physical interactions are probable among MO moiety and the supported catalyst. The lower correlation coefficients (R<sup>2</sup> = 0.826 for decolorization and R<sup>2</sup> = 0.667 for degradation) again represents the poorer fit of the experimental data.

The kinetics of MO adsorption onto 0.5 M ZnO-FA-Sep are studied in terms of pseudo-first order [39], pseudo-second order [40], Elovich [41–43] and intraparticle diffusion [44, 45] models.

Pseudo-first order model: Pseudo-first order model describes the adsorption rate based on the adsorption capacity [39].

The differential equation of the model is expressed as follows:

where qe is equilibrium concentration (mg g�<sup>1</sup>

explored by the following Temkin equation [35]:

where KTe is equilibrium binding constant (L mg�<sup>1</sup>

of MO adsorption on 0.5 M ZnO-FA-Sep.

ε is the Polanyi potential (ε = RT ln(1 + 1/Ce)).

The adsorption mean free energy (E; kJ mol�<sup>1</sup>

it lies between 8 and 16 kJ mol�<sup>1</sup>

E < 8 kJ mol�<sup>1</sup>

tion and degradation, respectively (Table 2, Figure 3D).

adsorption capacity (mg g�<sup>1</sup>

(mg L�<sup>1</sup>

154 Advanced Chemical Kinetics

degradation).

Eq. (6) can be linearized as

), Ce is equilibrium liquid phase concentration

<sup>b</sup> ln Kð Þ TeCe (6)

), b is the heat of adsorption (J mol�<sup>1</sup>

), BT is

), qm is the maximum

�2 ) and

qe ¼ BT ln KT þ BT ln Ce (7)

ln qe <sup>¼</sup> ln qm � βε<sup>2</sup> (8)

) can be found from the slope as follows

, the adsorption process takes place chemically and while

�2<sup>β</sup> <sup>p</sup> (9)

), β is a coefficient for adsor ption mean free energy (mol<sup>2</sup> J

) and Kf is adsorption capacity. Adsorption intensity is determined by "n". The values

of 1/n are found as 0.451 (for decolorization) and 0.354 (for degradation) indicate high tendency of MO for the adsorption onto the supported catalyst. However, Freundlich model is not suitable to describe the relation between sorbed MO molecules and their equilibrium concentrations owing to the lower correlation coefficients (0.864 for decolorization and 0.652 for

Temkin isotherm: The heat of adsorption and the adsorption-binding energy relation are

related to the heat of adsorption as being equal to RT/b, R is the gas constant and T is the temperature (K). The values of Temkin constants (KTe = 4.62 and BT = 1.89 for decolorization and KTe = 1.79 and BT = 2.29 for degradation) and correlation coefficients (R2 = 0.567 for decolorization and R2 = 0.782 for degradation) are found to be lower than the Langmuir values (Table 2, Figure 3C). Thus, Temkin model does not fit to the corresponding experimental data

Dubinin-Radushkevich (D-R) isotherm: Dubinin-Radushkevich model is based on heterogeneous surfaces, different sorption sites and steric hindrance effect among adsorbed molecules and bulk species [36]. The linear form of D-R isotherm is expressed by the following equation [31]:

The qm values are found using the intercept of the plot as 8.12 and 7.02 mg g�<sup>1</sup> for decoloriza-

<sup>E</sup> <sup>¼</sup> <sup>1</sup>

Its value gives information about adsorption mechanism whether it is physical or chemical. If

ffiffiffiffiffiffiffiffiffi

, the adsorption process proceeds physically [37, 38]. Since adsorption energies

where qe is the amount of adsorbate per unit weight of adsorbent (mg g�<sup>1</sup>

qe <sup>¼</sup> RT

$$\frac{\mathbf{dq\_t}}{\mathbf{dt}} = \mathbf{k\_1}(\mathbf{q\_e} - \mathbf{q\_t}) \tag{10}$$

where k1 is the pseudo-first order rate constant (min), qe is the adsorption capacity at equilibrium and qt is the adsorption capacity at time t.

Integrating Eq. (10) for the boundary conditions of qt = 0 at t = 0 and qt = qt at t = t gives

$$
\ln\left(\mathbf{q}\_{\text{e}} - \mathbf{q}\_{\text{t}}\right) = \ln\mathbf{q}\_{\text{e}} - \mathbf{k}\_{\text{l}}\mathbf{t} \tag{11}
$$

Accordingly, the values of ln(qe�qt) are linearly correlated with t by plot of ln (qe�qt) versus t. The rate constant (k1) and qe can be determined from the slope and intercept of the plot, respectively. The pseudo-first order equation fits well for the first 30 min data and then deviations are noticed. Although rate should be proportional to the first power of MO concentration, the linearity is lost for the higher initial MO concentrations. This may be attributed to the limiting effect of pore diffusion through the adsorption process. For the rapid adsorption of the initial stages, the first order rate constants, k1, decrease with increments in MO concentrations for both decolorization and degradation processes (Table 3). It is also noticed that calculated qe values agree well with the experimental data. The high correlation coefficients show the applicability of pseudo-first order kinetics to the adsorption of MO onto the supported catalyst.

Pseudo-second-order equation: The adsorption kinetics may also be described by the pseudosecond order model [40]. The differential equation is given as follows:

$$\frac{\mathbf{dq\_t}}{\mathbf{dt}} = \mathbf{k\_2} \left(\mathbf{q\_e} - \mathbf{q\_t}\right)^2 \tag{12}$$

where k2 is the second-order rate constant of adsorption. Integrating Eq. (12) for the boundary conditions of qt = 0 at t = 0 and qt = qt at t = t gives

$$\frac{\mathbf{t}}{\mathbf{q}\_{\rm t}} = \left(\frac{1}{\mathbf{k}\_2 \mathbf{q}\_{\rm e}^2}\right) + \frac{\mathbf{t}}{\mathbf{q}\_{\rm e}} \tag{13}$$

The linearity obtained in the plot of t/qt versus t results in k2 value (as the intercept) and qe value as the equilibrium adsorption capacity (from the slope). Similar to the pseudo-first order kinetics, k2 decreases as the concentration of initial MO increases for both processes (Table 3). Although high correlation coefficients are obtained, calculated qe values are not closer to the experimental values. Moreover, the predicted chemical adsorption cannot be applicable since only physical interactions are suggested between MO molecules and the supported catalyst via D-R model.

Elovich equation: The Elovich equation is based on the adsorption capacity and expressed as follows [46–48]:

$$\frac{d\mathbf{q}\_t}{dt} = \alpha \exp\left(-\beta\_{\mathbf{q}t}\right) \tag{14}$$

where β is the initial adsorption rate (mg g�<sup>1</sup> min�<sup>1</sup> ) and α is the desorption constant (g mg�<sup>1</sup> ). The linearized form of Eq. (14) with boundary conditions of qt = 0 at t = 0 and qt = qt at t = t is as follows

$$\mathbf{q}\_{\mathbf{i}} = \begin{pmatrix} 1/\beta \end{pmatrix} \ln \left( a \,\beta \right) - \begin{pmatrix} 1/\beta \end{pmatrix} \ln \mathbf{t} \tag{15}$$

Elovich parameters are given in Table 3. The plot of qt versus ln t yields a linear relationship with a slope of 1/ β and an intercept of (1/β) ln (α β). The high correlation coefficients indicate suitability of the model for the evaluation of the adsorption process. The limited number of vacant-available sites on the supported catalyst may decrease the possibility of chemical adsorption process through increments in MO concentration. This eventually results in smaller β values in both decolorization and degradation processes. Simultaneously, desorptions from the surface may be enhanced via less strong physical attractions and increase α values.

Interparticle diffusion model: The adsorbate species are probably transported from the bulk of the solution into the solid phase through intraparticle diffusion/transport process. The model is expressed by the following equation:

$$\mathbf{q}\_{\rm th} = \mathbf{K}\_{\rm diff} \mathbf{t}^{1/2} + \mathbf{C} \tag{16}$$

Models

 Parameters

3.27 mg L1 8.17 mg L1 16.3 mg L1 24.5 mg L1 32.7 mg L1 3.27 mg L1 8.17 mg L1 16.3 mg L1 24.5 mg L1 32.7 mg L1

First-order

k1 qe R2

Second-order

k2 qe R2

> Elowich

α β R2

Intraparticle

Kdiff

C R2

Experimental

qe(exp)

 3.02

 4.67

 9.21

 9.15

 7.16

 2.65

 3.79

 6.99

 9.52

 7.90

Adsorption, Kinetics and Photoactivity of ZnO-Supported Fly Ash-Sepiolite Ternary Catalyst

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157

data

Table 3.

Adsorption

 kinetics constants.

0.936

 0.874

 0.924

 0.922

 0.66

 0.903

 0.813

 0.937

 0.947

 0.882

0.12

 1.45

 0.29

 0.76

 1.67

 0.153

 0.931

 0.978

 2.14

 1.513

0.362

 0.385

 1.08

 1.054

 0.975

 0.397

 0.372

 0.747

 0.886

 0.865

diffusion

0.958

 0.886

 0.951

 0.920

 0.647

 0.925

 0.821

 0.985

 0.952

 0.914

0.683

 0.621

 0.248

 0.229

 0.219

 0.633

 0.534

 0.442

 0.273

 0.271

0.158

 0.383

 0.464

 0.510

 0.560

 0.273

 0.526

 0.651

 1.095

 1.256

0.697

 0.941

 0.846

 0.856

 0.852

 0.916

 0.987

 0.998

 0.903

 0.898

6.45

 6.89

 16.94

 16.94

 9.09

 5.43

 4.85

 9.17

 16.67

 13.51

3.83 103 1.77 103 1.62 103 8.36 104 7.47 104

> kinetic model

0.897

 0.934

 0.949

 0.971

 0.912

 0.984 0.0508

 7.65 103 2.12 103 1.38 103 1.02 103

 0.727

 0.985

 0.924

 0.906

3.35

 4.64

 10.17

 9.67

 6.88

 2.65

 4.55

 6.62

 9.20

 9.02

0.035

 0.032

 0.026

 0.025

 0.0021

 0.056

 0.052

 0.039

 0.028

 0.0039

> kinetic model

Decolorization

Degradation

where C (mg g�<sup>1</sup> ) is the intercept and Kdiff is the intraparticle diffusion rate constant (in mg g�<sup>1</sup> min1/2). Kdiff can be evaluated by the linear correlation of qt versus t1/2 (Table 3). As a general trend, Kdiff values increase with increase of initial MO concentration but for the highest concentrations there seems to be a constancy. This may point out the existence of restricted diffusion for the external mass. Although C values supplies information about the thickness of the boundary layer, experimental data do not exhibit neither an increasing nor a decreasing trend. Thus, the adsorption mechanism cannot be explained by using this model owing to the complex structure of the supported catalyst.


The linearity obtained in the plot of t/qt versus t results in k2 value (as the intercept) and qe value as the equilibrium adsorption capacity (from the slope). Similar to the pseudo-first order kinetics, k2 decreases as the concentration of initial MO increases for both processes (Table 3). Although high correlation coefficients are obtained, calculated qe values are not closer to the experimental values. Moreover, the predicted chemical adsorption cannot be applicable since only physical interactions are suggested between MO molecules and the supported catalyst via

Elovich equation: The Elovich equation is based on the adsorption capacity and expressed as

dt <sup>¼</sup> <sup>α</sup> exp �βqt

The linearized form of Eq. (14) with boundary conditions of qt = 0 at t = 0 and qt = qt at t = t is as

Elovich parameters are given in Table 3. The plot of qt versus ln t yields a linear relationship with a slope of 1/ β and an intercept of (1/β) ln (α β). The high correlation coefficients indicate suitability of the model for the evaluation of the adsorption process. The limited number of vacant-available sites on the supported catalyst may decrease the possibility of chemical adsorption process through increments in MO concentration. This eventually results in smaller β values in both decolorization and degradation processes. Simultaneously, desorptions from the surface may be enhanced via less strong physical attractions and increase α

Interparticle diffusion model: The adsorbate species are probably transported from the bulk of the solution into the solid phase through intraparticle diffusion/transport process. The model is

mg g�<sup>1</sup> min1/2). Kdiff can be evaluated by the linear correlation of qt versus t1/2 (Table 3). As a general trend, Kdiff values increase with increase of initial MO concentration but for the highest concentrations there seems to be a constancy. This may point out the existence of restricted diffusion for the external mass. Although C values supplies information about the thickness of the boundary layer, experimental data do not exhibit neither an increasing nor a decreasing trend. Thus, the adsorption mechanism cannot be explained by using this model owing to the

) is the intercept and Kdiff is the intraparticle diffusion rate constant (in

qt ¼ Kdifft

) and α is the desorption constant (g mg�<sup>1</sup>

� <sup>1</sup>=<sup>β</sup> ln t (15)

<sup>1</sup>=<sup>2</sup> <sup>þ</sup> <sup>C</sup> (16)

(14)

).

dqt

qt <sup>¼</sup> <sup>1</sup>=<sup>β</sup> ln α β

where β is the initial adsorption rate (mg g�<sup>1</sup> min�<sup>1</sup>

D-R model.

follows

values.

where C (mg g�<sup>1</sup>

expressed by the following equation:

complex structure of the supported catalyst.

follows [46–48]:

156 Advanced Chemical Kinetics

Table 3. Adsorption kinetics constants.

#### 4.3. Photocatalytic degradation

#### 4.3.1. Kinetics

The 0.5 M ZnO-FA-Sep is further used to analyze the rate of reactions in the initial concentration range of MO from 3.27 to 24.5 mg L�<sup>1</sup> (Figure 4A). The data from the photocatalytic activities is analyzed for the following rate expression

$$\ln \frac{\text{C}\_0}{\text{C}} = \text{kt} \tag{17}$$

where C0 is taken as the equilibrium concentration of MO (mg L�<sup>1</sup> ) after dark adsorption. The linearity in the plot of ln(C0/C) versus t results confirmed the validity of pseudo-first-order kinetics. The rate-constants (k, min�<sup>1</sup> ) are calculated from the slopes of the lines.

For the initial concentration of 3.27 mg L�<sup>1</sup> , 88% degradation and 85% decolorization are achieved within 20 min whereas only 44% (degradation) and 43% (decolorization) MO removal are obtained even at 70 min for the concentration of 24.5 mg L�<sup>1</sup> .Similarly, k values decrease from 0.122 to 0.036 min�<sup>1</sup> (for degradation) and from 0.121 to 0.056 min�<sup>1</sup> (for decolorization) as the initial concentration of MO increases from 3.27 to 24.5 mg L�<sup>1</sup> (not shown). Since more MO molecules are expected to be adsorbed to the surface of 0.5 M ZnO-FA-Sep as the initial concentration of MO increases, the sorption of both OH� and O2 will be reduced. Thus, the number of both photogenerated holes and • OH radicals is suppressed and resulted in lower photocatalytic efficiencies. Meanwhile, more photons are absorbed in bulk solutions by the high concentrations of MO. This creates the shortage of photons to activate the supported catalyst.

Additionally, Langmuir-Hinshelwood model is successfully applied to estimate the relationship between the photocatalytic degradation rate and the initial concentration of organic contaminants by the following rearranged form [49, 50].

$$\frac{1}{\mathbf{R}} = \frac{1}{\mathbf{k}\mathbf{K}\mathbf{C}\_0} + \frac{1}{\mathbf{k}}\tag{18}$$

highest percentages (74% for decolorization and 82% for degradation) among the binary catalysts. However, the existence of FA spheres within the catalyst matrixes decreases the MO percentages. The lowest values (17% for decolorization and 9% for degradation) are noticed in the presence of 0.5 M ZnO-FA while relatively higher values (29% for decolorization and 26% for degradation) are obtained with 0.5 M ZnO-FA-Sep. Under irradiation, binary catalyst (0.5 M ZnO-Sep) does not work efficiently while the others demonstrate much lower

Figure 4. (A) Effect of initial MO concentration on the photoactivity of 0.5 M ZnO-FA-Sep, (B) Langmuir-Hinshelwood kinetic analysis in the presence of 0.5 M ZnO-FA-Sep, (C) photoactivity comparison between 0.5 M ZnO-FA-Sep, binary

Adsorption, Kinetics and Photoactivity of ZnO-Supported Fly Ash-Sepiolite Ternary Catalyst

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159

catalysts and 0.5 M ZnO, (D) reuse properties of 0.5 M ZnO-FA-Sep.

where R is the rate of decolorization (or degradation), K is the adsorption coefficient of MO onto the 0.5 M ZnO-FA-Sep (L mg�<sup>1</sup> ), k is the reaction rate constant (mg L�<sup>1</sup> min�<sup>1</sup> ). The linear correlation [0.997 (for degradation) and 0.998 (for decolorization)] in the plot of (1/R) against (1/C0) proved the validity of the model for the as-prepared supported catalysts (Figure 4B). Accordingly, both adsorption of MO to 0.5 M ZnO-FA-Sep (K) and photocatalytic degradation of MO by 0.5 M ZnO-FA-Sep (k) are calculated as 0.066 L mg�<sup>1</sup> and 0.200 mg L�<sup>1</sup> min�<sup>1</sup> (for degradation) and 0.177 L mg�<sup>1</sup> and 0.154 mg L�<sup>1</sup> min�<sup>1</sup> (for decolorization).

#### 4.3.2. Comparison with binary composites

The ternary-supported catalyst (0.5 M ZnO-FA-Sep) is also compared with the binary ones (0.5 M ZnO-Sep and 0.5 M ZnO-FA) and 0.5 M ZnO (Figure 4C). After 20 min dark adsorption, supported catalysts show lower MO percentages remaining in the solution than the 0.5 M ZnO (97% for decolorization and 91% for degradation). Meanwhile, 0.5 M ZnO-Sep displays the Adsorption, Kinetics and Photoactivity of ZnO-Supported Fly Ash-Sepiolite Ternary Catalyst http://dx.doi.org/10.5772/intechopen.70504 159

4.3. Photocatalytic degradation

tion range of MO from 3.27 to 24.5 mg L�<sup>1</sup>

kinetics. The rate-constants (k, min�<sup>1</sup>

both photogenerated holes and •

onto the 0.5 M ZnO-FA-Sep (L mg�<sup>1</sup>

4.3.2. Comparison with binary composites

For the initial concentration of 3.27 mg L�<sup>1</sup>

activities is analyzed for the following rate expression

where C0 is taken as the equilibrium concentration of MO (mg L�<sup>1</sup>

are obtained even at 70 min for the concentration of 24.5 mg L�<sup>1</sup>

the initial concentration of MO increases from 3.27 to 24.5 mg L�<sup>1</sup>

contaminants by the following rearranged form [49, 50].

of MO. This creates the shortage of photons to activate the supported catalyst.

1 <sup>R</sup> <sup>¼</sup> <sup>1</sup> kKC0 þ 1

degradation) and 0.177 L mg�<sup>1</sup> and 0.154 mg L�<sup>1</sup> min�<sup>1</sup> (for decolorization).

The 0.5 M ZnO-FA-Sep is further used to analyze the rate of reactions in the initial concentra-

linearity in the plot of ln(C0/C) versus t results confirmed the validity of pseudo-first-order

achieved within 20 min whereas only 44% (degradation) and 43% (decolorization) MO removal

from 0.122 to 0.036 min�<sup>1</sup> (for degradation) and from 0.121 to 0.056 min�<sup>1</sup> (for decolorization) as

molecules are expected to be adsorbed to the surface of 0.5 M ZnO-FA-Sep as the initial concentration of MO increases, the sorption of both OH� and O2 will be reduced. Thus, the number of

efficiencies. Meanwhile, more photons are absorbed in bulk solutions by the high concentrations

Additionally, Langmuir-Hinshelwood model is successfully applied to estimate the relationship between the photocatalytic degradation rate and the initial concentration of organic

where R is the rate of decolorization (or degradation), K is the adsorption coefficient of MO

correlation [0.997 (for degradation) and 0.998 (for decolorization)] in the plot of (1/R) against (1/C0) proved the validity of the model for the as-prepared supported catalysts (Figure 4B). Accordingly, both adsorption of MO to 0.5 M ZnO-FA-Sep (K) and photocatalytic degradation of MO by 0.5 M ZnO-FA-Sep (k) are calculated as 0.066 L mg�<sup>1</sup> and 0.200 mg L�<sup>1</sup> min�<sup>1</sup> (for

The ternary-supported catalyst (0.5 M ZnO-FA-Sep) is also compared with the binary ones (0.5 M ZnO-Sep and 0.5 M ZnO-FA) and 0.5 M ZnO (Figure 4C). After 20 min dark adsorption, supported catalysts show lower MO percentages remaining in the solution than the 0.5 M ZnO (97% for decolorization and 91% for degradation). Meanwhile, 0.5 M ZnO-Sep displays the

) are calculated from the slopes of the lines.

OH radicals is suppressed and resulted in lower photocatalytic

), k is the reaction rate constant (mg L�<sup>1</sup> min�<sup>1</sup>

ln C0

(Figure 4A). The data from the photocatalytic

<sup>C</sup> <sup>¼</sup> kt (17)

, 88% degradation and 85% decolorization are

<sup>k</sup> (18)

). The linear

) after dark adsorption. The

.Similarly, k values decrease

(not shown). Since more MO

4.3.1. Kinetics

158 Advanced Chemical Kinetics

Figure 4. (A) Effect of initial MO concentration on the photoactivity of 0.5 M ZnO-FA-Sep, (B) Langmuir-Hinshelwood kinetic analysis in the presence of 0.5 M ZnO-FA-Sep, (C) photoactivity comparison between 0.5 M ZnO-FA-Sep, binary catalysts and 0.5 M ZnO, (D) reuse properties of 0.5 M ZnO-FA-Sep.

highest percentages (74% for decolorization and 82% for degradation) among the binary catalysts. However, the existence of FA spheres within the catalyst matrixes decreases the MO percentages. The lowest values (17% for decolorization and 9% for degradation) are noticed in the presence of 0.5 M ZnO-FA while relatively higher values (29% for decolorization and 26% for degradation) are obtained with 0.5 M ZnO-FA-Sep. Under irradiation, binary catalyst (0.5 M ZnO-Sep) does not work efficiently while the others demonstrate much lower percentages. Among which, 0.5 M ZnO-FA-Sep competes with the 0.5 M ZnO-FA within 10 min irradiation. The slight difference in the degradation and decolorization percentages may be due the smaller variations in the ZnO crystalline sizes, BET areas and pore volumes (DZnO = 8.12 nm, BET = 60 m2 g<sup>1</sup> , Vpore = 0.122 cm<sup>3</sup> g<sup>1</sup> for 0.5 M ZnO-FA and DZnO = 11.6 nm, BET = 50.2 m<sup>2</sup> g<sup>1</sup> , Vpore = 0.097 cm3 g<sup>1</sup> for 0.5 M ZnO) [12]. Although FA-Sep has a more complex structure than the FA alone, ZnO nanoparticles in the ternary system are located on the external surfaces of both FA and Sep showing no preference to any of these minerals as detected in the SEM images. Moreover, FA as well as Sep crystals do not agglomerate in the ternary composite owing to their morphological differences in shape and sizes. This creates uniqueness for 0.5 M ZnO-FA-Sep and enhances dispersion of ZnO nanoparticles.

Author details

Ayşe Neren Ökte

References

nology. 1991;51:47-60

Materials. 2015;285:212-220

Address all correspondence to: okteayse@boun.edu.tr

Department of Chemistry, Boğaziçi University, Istanbul, Turkey

monitoring. Applied Clay Science. 2015;115:165-173

Applied Catalysis A: General. 2014;485:157-162

light. Applied Surface Science. 2012;258:9989-9996

[1] Yadava KP, Tyagi BS, Singh VN. Effect of temperature on the removal of lead (II) by adsorption on China clay and wollastonite. Journal of Chemical Technology and Biotech-

Adsorption, Kinetics and Photoactivity of ZnO-Supported Fly Ash-Sepiolite Ternary Catalyst

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161

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and surfactants. Journal of Chemical Engineering. 2013;223:860-868

performance and mechanism. Chemical Engineering Journal. 2016;288:70-78

#### 4.3.3. Reusability

Furthermore, to investigate the photocatalytic stability of 0.5 M ZnO-FA-Sep, cyclic experiments are carried out under the same experimental conditions (Figure 4D). For each run, 0.5 M ZnO-FA-Sep is filtrated, washed and calcined at 500C for 2 h. After four cycles, the percentage of MO remaining in solution is found to increase only approximately 2% (from 15 to 17% for decolorization process) and 3% (from 12 to 15% for degradation process). The slight increments in the percentages can be attributed to the catalyst loss during each collection and rinsing steps.

### 5. Conclusions

A ternary-supported catalyst has been prepared and characterized by XRD, BET, SEM (EDX), XPS and DRUV techniques. ZnO nanoparticles are found to be dispersed on both FA and Sep minerals. Supported catalysts exhibit higher surface areas and pore volumes than FA-Sep, FA and 0.25 M ZnODZnO sizes do not exhibit significant differences depending on the ZnO loading concentrations. EDX, mapping and XPS analysis evidence the existence of ZnO nanoparticles. Moreover, supported catalysts exhibit an absorption edge similar to 0.25 M ZnO with a slight blue shift. High dark adsorption capacities of the supported catalysts improve their photocatalytic activities, which further enhanced with the ZnO loading concentration. The existence of both FA and Sep with different shapes and sizes decrease their agglomeration and expose more of their surfaces for the adsorption of ZnO nanoparticles.

Future studies will focus on the development of new composites and their applications in environmental issues.

### Acknowledgements

This study was supported by Boğaziçi University Research Foundation (Project No. 17B05P4/ 13021).

### Author details

percentages. Among which, 0.5 M ZnO-FA-Sep competes with the 0.5 M ZnO-FA within 10 min irradiation. The slight difference in the degradation and decolorization percentages may be due the smaller variations in the ZnO crystalline sizes, BET areas and pore volumes

complex structure than the FA alone, ZnO nanoparticles in the ternary system are located on the external surfaces of both FA and Sep showing no preference to any of these minerals as detected in the SEM images. Moreover, FA as well as Sep crystals do not agglomerate in the ternary composite owing to their morphological differences in shape and sizes. This creates

Furthermore, to investigate the photocatalytic stability of 0.5 M ZnO-FA-Sep, cyclic experiments are carried out under the same experimental conditions (Figure 4D). For each run, 0.5 M ZnO-FA-Sep is filtrated, washed and calcined at 500C for 2 h. After four cycles, the percentage of MO remaining in solution is found to increase only approximately 2% (from 15 to 17% for decolorization process) and 3% (from 12 to 15% for degradation process). The slight increments in the percentages can be attributed to the catalyst loss during each collection and

A ternary-supported catalyst has been prepared and characterized by XRD, BET, SEM (EDX), XPS and DRUV techniques. ZnO nanoparticles are found to be dispersed on both FA and Sep minerals. Supported catalysts exhibit higher surface areas and pore volumes than FA-Sep, FA and 0.25 M ZnODZnO sizes do not exhibit significant differences depending on the ZnO loading concentrations. EDX, mapping and XPS analysis evidence the existence of ZnO nanoparticles. Moreover, supported catalysts exhibit an absorption edge similar to 0.25 M ZnO with a slight blue shift. High dark adsorption capacities of the supported catalysts improve their photocatalytic activities, which further enhanced with the ZnO loading concentration. The existence of both FA and Sep with different shapes and sizes decrease their agglomeration and expose more of their surfaces for the adsorption of ZnO nanoparticles.

Future studies will focus on the development of new composites and their applications in

This study was supported by Boğaziçi University Research Foundation (Project No. 17B05P4/

uniqueness for 0.5 M ZnO-FA-Sep and enhances dispersion of ZnO nanoparticles.

, Vpore = 0.122 cm<sup>3</sup> g<sup>1</sup> for 0.5 M ZnO-FA and DZnO = 11.6 nm,

, Vpore = 0.097 cm3 g<sup>1</sup> for 0.5 M ZnO) [12]. Although FA-Sep has a more

(DZnO = 8.12 nm, BET = 60 m2 g<sup>1</sup>

BET = 50.2 m<sup>2</sup> g<sup>1</sup>

160 Advanced Chemical Kinetics

4.3.3. Reusability

rinsing steps.

5. Conclusions

environmental issues.

Acknowledgements

13021).

Ayşe Neren Ökte

Address all correspondence to: okteayse@boun.edu.tr

Department of Chemistry, Boğaziçi University, Istanbul, Turkey

### References


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**Section 3**

**Kinetics Techniques**


## **Kinetics Techniques**

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**Chapter 10**

Provisional chapter

**Kinetics of Heterogeneous Self-Propagating High-**

DOI: 10.5772/intechopen.70560

In this chapter, we present an overview of experimental techniques utilized and kinetic data collected for exothermic self-sustained noncatalytic heterogeneous reactions. The data focuses on five primary experimental techniques: electrothermal explosion, differential thermal analysis, electrothermography, combustion velocity/temperature analyses, and several advanced in situ diagnostics, including time-resolved X-ray diffraction.

Self-propagating high-temperature synthesis (SHS) is a technological approach for fabrication of materials, which involves self-sustained noncatalytic reactions [1–3]. Currently, there exist three major types of SHS systems: (i) gasless; (ii) with gasification of initially solid precursors; (iii) gas-solid. Within gasless systems, there are three major types of chemical reactions that occur: metal-metal, producing intermetallic (e.g., NiAl, NiTi), metal-nonmetal, leading to synthesis of borides, carbides and silicides (e.g., TiB2, TaC, MoSi2); nonmetal-nonmetal, producing ceramics (e.g., B4C, SiC). In the gasification reactions, one of the precursors is volatile, including such elements as S, Se, P, As, Sb. Finally, the gas-solid systems include reactions between metals or nonmetals with different gases, such as nitrogen, oxygen, hydrogen, CO, and CO2 leading to formation of nitrides, oxides, hydrides and etc. These lists are by no means exhaustive, as different research groups are continually exploring the limits of SHS reactions with different systems, reactants, and conditions. In order to obtain materials with desired

> © The Author(s). Licensee InTech. 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 eproduction in any medium, provided the original work is properly cited.

© 2018 The Author(s). Licensee InTech. 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.

Keywords: self-propagating high-temperature synthesis (SHS), electrothermal explosion, electrothermography, combustion synthesis, mechanical activation,

Kinetics of Heterogeneous Self-Propagating

**Temperature Reactions**

Christopher E. Shuck and Alexander S. Mukasyan

Abstract

1. Introduction

High-Temperature Reactions

http://dx.doi.org/10.5772/intechopen.70560

Christopher E. Shuck and Alexander S. Mukasyan

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

high-energy ball milling, intermetallics, thermites

#### **Kinetics of Heterogeneous Self-Propagating High-Temperature Reactions** Kinetics of Heterogeneous Self-Propagating High-Temperature Reactions

DOI: 10.5772/intechopen.70560

Christopher E. Shuck and Alexander S. Mukasyan Christopher E. Shuck and

Additional information is available at the end of the chapter Alexander S. Mukasyan

http://dx.doi.org/10.5772/intechopen.70560 Additional information is available at the end of the chapter

Abstract

In this chapter, we present an overview of experimental techniques utilized and kinetic data collected for exothermic self-sustained noncatalytic heterogeneous reactions. The data focuses on five primary experimental techniques: electrothermal explosion, differential thermal analysis, electrothermography, combustion velocity/temperature analyses, and several advanced in situ diagnostics, including time-resolved X-ray diffraction.

Keywords: self-propagating high-temperature synthesis (SHS), electrothermal explosion, electrothermography, combustion synthesis, mechanical activation, high-energy ball milling, intermetallics, thermites

### 1. Introduction

Self-propagating high-temperature synthesis (SHS) is a technological approach for fabrication of materials, which involves self-sustained noncatalytic reactions [1–3]. Currently, there exist three major types of SHS systems: (i) gasless; (ii) with gasification of initially solid precursors; (iii) gas-solid. Within gasless systems, there are three major types of chemical reactions that occur: metal-metal, producing intermetallic (e.g., NiAl, NiTi), metal-nonmetal, leading to synthesis of borides, carbides and silicides (e.g., TiB2, TaC, MoSi2); nonmetal-nonmetal, producing ceramics (e.g., B4C, SiC). In the gasification reactions, one of the precursors is volatile, including such elements as S, Se, P, As, Sb. Finally, the gas-solid systems include reactions between metals or nonmetals with different gases, such as nitrogen, oxygen, hydrogen, CO, and CO2 leading to formation of nitrides, oxides, hydrides and etc. These lists are by no means exhaustive, as different research groups are continually exploring the limits of SHS reactions with different systems, reactants, and conditions. In order to obtain materials with desired

© 2018 The Author(s). Licensee InTech. 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.

© The Author(s). Licensee InTech. 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 eproduction in any medium, provided the original work is properly cited.

microstructures, and thus properties, one has to precisely control the synthesis conditions during SHS. These conditions are primarily defined by the kinetics of the chemical reactions taking place in the combustion wave.

In order to study and understand the kinetics of SHS reactions, it is important to examine the fundamentals of kinetics and how they relate to SHS itself. Let us start with general definitions. Thus, assuming that the concentrations of any initial reagent, ci, and the product are uniformly distributed throughout the entire volume (homogeneous or quasi homogeneous cases), the chemical reaction rate can be expressed by the following equation:

$$\mathcal{W}\_i = \frac{d\mathbb{C}\_i}{dt} \text{ or } \mathcal{W}\_i = \frac{d\eta\_i}{dt} \tag{1}$$

dη

Arrhenius equation:

temperature by use of a thermostat.

chemical reactions can be represented as follows:

dη

The temperature function K(T) is generally considered to be the rate constant, while the conversion function Φ(η) is generally considered represent the process mechanism. It is assumed that the reaction mechanism is solely dependent on the conversion, and not the temperature. Eq. (3) resembles a single-step kinetic equation, even though it represents the kinetics of a complex condensed-phase process. The single-step kinetic approximation results in the substitution of a generally complex set of kinetic equations with the sole single-step kinetic equation. Eq. (5) represents a mathematical formulation of the single-step kinetic approximation. With few exceptions, the temperature function is exclusively expressed by the

where A and E<sup>a</sup> are considered to be the pre-exponential factor and the activation energy,

As our knowledge about the atomic and molecular structure of matter increased, coupled with the development of quantum mechanics, new directions in chemical kinetics have emerged. These directions are typically related to the interactions of individual atoms and molecules, which are more fundamental studies. The set of elementary events is called the reaction mechanism. Fundamental studies on the reaction mechanisms allow us to formulate physical explanations to the kinetic parameters (A, Ea, etc.), which were originally introduced as empirical constants. For example, the activation energy E<sup>a</sup> is an energy barrier that must be overcome by molecules in the reaction mixture to reach an interatomic distance where they can from a chemical bond. From Eq. (5), it is clear that, if the concentration of substances or the temperature in the given system varies from point to point. Thus, it is impossible to introduce a common reaction rate for the entire system. In order to get closer to these ideal conditions, in classical kinetic experiments we must continuously mix the reagents and maintain a constant

In the case of heterogeneous reactions involving a condensed phase, where the reactants are not mixed on the molecular level, there is an additional parameter, which controls the rate of interaction, i.e., the contact surface area (S) between the reagents [2]. In this case, the rate of the

The presence of condensed phases complicates the reaction; this phase requires that transport plays a role in the reaction. Thus, in general, the kinetics of such reactions are determined both by the intrinsic rate of the chemical reaction and by mass transport (e.g., diffusion). The transport phenomena are essential for replenishing the reactants that were consumed in the reaction zone [4]. Describing the reaction rate is further complicated when the temperature of the reacting environment is changing with time. In this case, along with the processes of mass

respectively, T is the absolute temperature, and R is the gas constant.

dt <sup>¼</sup> K Tð ÞΦ η (5)

http://dx.doi.org/10.5772/intechopen.70560

169

Kinetics of Heterogeneous Self-Propagating High-Temperature Reactions

K Tð Þ¼ A exp ð Þ �Ea=RT (6)

dt <sup>¼</sup> <sup>A</sup> � <sup>S</sup> � Φ η exp ð Þ �Ea=RT (7)

where Wi is the reaction rate for the i th reagent or product, η<sup>i</sup> = (c 0 <sup>i</sup> � ci)/c<sup>0</sup> is the degree of conversion for the i th reagent, c 0 <sup>i</sup> is the initial concentration of the i th reagent, and t is time.

In the nineteenth century, C.M. Guldberg with P. Waage and N.N. Beketov independently formulated the law of mass action. This essentially states that the chemical reaction rates at a given point are proportional to the concentration (mass) of the reactants raised to a proportional exponent. Thus, for an elementary chemical reaction between two reagents A and B of the following form:

$$
\upsilon\_1 A + \upsilon\_2 B \to \mathbb{C},\tag{2}
$$

where υ1,υ<sup>2</sup> are stoichiometric coefficients.

For this reaction, the law of mass action can be written in the form of a kinetic equation:

$$\mathcal{W} = kc\_A^{\nu\_1} c\_{B}^{\nu\_2} \, , \tag{3}$$

where k is the reaction rate constant.

Along with the reactant concentration, the temperature affects the rate of the chemical reaction in a noncatalytic homogeneous reaction. However, the mechanisms of these processes are often unknown or too complicated. This is because the reactions occur in multiple steps, each of which has unique reaction rates. In order to describe the chemical kinetics, a single-step approximation is typically used. This states that the rate of the processes in the condensed state is generally a function of the temperature and degree of conversion:

$$\frac{d\eta}{dt} = F(T, \eta) \tag{4}$$

The single-step approximation employs the assumption that the function in Eq. (4) can be expressed as a product of two separable functions that are independent of each other; the first, K(T), depends solely on the temperature, T, and the second, Φ(η), depends solely on the degree of conversion, η:

Kinetics of Heterogeneous Self-Propagating High-Temperature Reactions http://dx.doi.org/10.5772/intechopen.70560 169

$$\frac{d\eta}{dt} = K(T)\Phi(\eta)\tag{5}$$

The temperature function K(T) is generally considered to be the rate constant, while the conversion function Φ(η) is generally considered represent the process mechanism. It is assumed that the reaction mechanism is solely dependent on the conversion, and not the temperature. Eq. (3) resembles a single-step kinetic equation, even though it represents the kinetics of a complex condensed-phase process. The single-step kinetic approximation results in the substitution of a generally complex set of kinetic equations with the sole single-step kinetic equation. Eq. (5) represents a mathematical formulation of the single-step kinetic approximation. With few exceptions, the temperature function is exclusively expressed by the Arrhenius equation:

microstructures, and thus properties, one has to precisely control the synthesis conditions during SHS. These conditions are primarily defined by the kinetics of the chemical reactions

In order to study and understand the kinetics of SHS reactions, it is important to examine the fundamentals of kinetics and how they relate to SHS itself. Let us start with general definitions. Thus, assuming that the concentrations of any initial reagent, ci, and the product are uniformly distributed throughout the entire volume (homogeneous or quasi homogeneous cases), the chemical reaction rate can be expressed by the following equa-

dt or Wi <sup>¼</sup> <sup>d</sup>η<sup>i</sup>

<sup>i</sup> is the initial concentration of the i

In the nineteenth century, C.M. Guldberg with P. Waage and N.N. Beketov independently formulated the law of mass action. This essentially states that the chemical reaction rates at a given point are proportional to the concentration (mass) of the reactants raised to a proportional exponent. Thus, for an elementary chemical reaction between two reagents A and B of

For this reaction, the law of mass action can be written in the form of a kinetic equation:

<sup>W</sup> <sup>¼</sup> kc<sup>υ</sup><sup>1</sup> A c υ2

Along with the reactant concentration, the temperature affects the rate of the chemical reaction in a noncatalytic homogeneous reaction. However, the mechanisms of these processes are often unknown or too complicated. This is because the reactions occur in multiple steps, each of which has unique reaction rates. In order to describe the chemical kinetics, a single-step approximation is typically used. This states that the rate of the processes in the condensed state

The single-step approximation employs the assumption that the function in Eq. (4) can be expressed as a product of two separable functions that are independent of each other; the first, K(T), depends solely on the temperature, T, and the second, Φ(η), depends solely on the degree

th reagent or product, η<sup>i</sup> = (c

dt (1)

<sup>i</sup> � ci)/c<sup>0</sup> is the degree of

th reagent, and t is time.

0

υ1A þ υ2B ! C, (2)

dt <sup>¼</sup> F T; <sup>η</sup> (4)

<sup>B</sup> , (3)

Wi <sup>¼</sup> dCi

taking place in the combustion wave.

where Wi is the reaction rate for the i

where υ1,υ<sup>2</sup> are stoichiometric coefficients.

where k is the reaction rate constant.

th reagent, c

0

is generally a function of the temperature and degree of conversion:

dη

conversion for the i

168 Advanced Chemical Kinetics

the following form:

of conversion, η:

tion:

$$K(T) = A \exp\left(-E\_\text{a}/RT\right) \tag{6}$$

where A and E<sup>a</sup> are considered to be the pre-exponential factor and the activation energy, respectively, T is the absolute temperature, and R is the gas constant.

As our knowledge about the atomic and molecular structure of matter increased, coupled with the development of quantum mechanics, new directions in chemical kinetics have emerged. These directions are typically related to the interactions of individual atoms and molecules, which are more fundamental studies. The set of elementary events is called the reaction mechanism. Fundamental studies on the reaction mechanisms allow us to formulate physical explanations to the kinetic parameters (A, Ea, etc.), which were originally introduced as empirical constants. For example, the activation energy E<sup>a</sup> is an energy barrier that must be overcome by molecules in the reaction mixture to reach an interatomic distance where they can from a chemical bond. From Eq. (5), it is clear that, if the concentration of substances or the temperature in the given system varies from point to point. Thus, it is impossible to introduce a common reaction rate for the entire system. In order to get closer to these ideal conditions, in classical kinetic experiments we must continuously mix the reagents and maintain a constant temperature by use of a thermostat.

In the case of heterogeneous reactions involving a condensed phase, where the reactants are not mixed on the molecular level, there is an additional parameter, which controls the rate of interaction, i.e., the contact surface area (S) between the reagents [2]. In this case, the rate of the chemical reactions can be represented as follows:

$$\frac{d\eta}{dt} = A \cdot \mathbf{S} \cdot \Phi(\eta) \exp\left(-E\_{\mathbf{a}}/RT\right) \tag{7}$$

The presence of condensed phases complicates the reaction; this phase requires that transport plays a role in the reaction. Thus, in general, the kinetics of such reactions are determined both by the intrinsic rate of the chemical reaction and by mass transport (e.g., diffusion). The transport phenomena are essential for replenishing the reactants that were consumed in the reaction zone [4]. Describing the reaction rate is further complicated when the temperature of the reacting environment is changing with time. In this case, along with the processes of mass transfer and chemical reactions, it is necessary to consider the specifics of heat transfer mechanisms [5]. Typically, the activation parameters are obtained after experiments considering the dependences of time vs. temperature (for isothermal measurements), temperature vs. heating rate (for integral and incremental methods with linear heating rates), or from reaction rate vs. temperature. Considering the above limitations and complications, only the effective or apparent activation energy can truly be considered, as it includes both the intrinsic kinetics as well as processes of heat and mass transport.

### 2. Techniques for studying SHS kinetics

The task of accurately determining kinetics becomes even more complicated when accounting for the extremely high temperatures of SHS processes (>1800 K) and rapid heating rates (103 –105 K/s). Such parameters are essentially impossible to achieve using conventional approaches for measurement of kinetics parameters. While standard nonisothermal TGA/DTA-based approaches [6] are still used to evaluate the kinetics of SHS reactions, several unique methods such as electrothermal explosion (ETE) [7] and electrothermography (ET) [8] were specifically developed to fit the experimental conditions of SHS reactions. Moreover, recently a variety of advanced in situ diagnostics, including time-resolved X-ray diffraction (TRXRD) [9], high-speed X-ray phasecontrast imaging [10], and high speed transmission electron microscopy (HSTEM) [11] were modified to obtain the kinetics of phase transformations during SHS reactions.

### 3. Electrothermal explosion

The ETE method was developed in 1977 to study the rapid, high-temperature kinetics that occur in SHS systems [7]. It relies on rapid, uniform preheating of the sample until adiabatic thermal explosion occurs. A representation of a typical ETE setup is shown in Figure 1. Briefly, the sample is clamped between two metallic electrodes with sufficient clamping pressure to ensure adequate contact. The power is then initiated, leading to preheating of the sample until a set Toff point. After initiation, the resulting time-temperature profiles are simultaneously collected across a number of high-speed photodiodes. In the commonly used ETA-100 system (Aloft, Inc., Berkley, CA), there are 16 photodiodes present, with 1 mm in between them; this corresponds to 0.5 mm spatial resolution. The photodiodes have a temporal resolution of 10<sup>5</sup> s and are accurate within 900–3000 K. Once the sample is heated to the selected Toff point, the equipment heating is halted, with the consequent rate of self-heating determined solely by the chemical reaction rate. Due to the experimental conditions, i.e., the rapid initial preheating, the reaction occurs in the adiabatic mode. Once thermal ignition occurs, analysis of the time-temperature profile enables extraction of the kinetic parameters (see details in [12]). This technique can be used to study the kinetics at temperatures much higher than can be achieved in other experiments. However, it is often limited in the systems that can be studied due to the stringent heating conditions caused by Joule preheating.

methods. For carbides, the Ti/C system has been studied [13–15], with additional studies in the Ta/C [14, 16] and Si/C [14, 17] mixtures. The Ti/B system was also investigated [18]. The majority of ETE work being focused on the Ni/Al system [12, 19–21]. The Ti/Fe2O3 system is the only thermite system investigated by ETE [22]. In addition to the experimental studies, a number of theoretical models have been developed to better understand the ETE process [23–26]. Figure 1 shows that ranges of reported activation energies for the above mentioned gasless systems, including both intermetallics and thermites obtained by ETE. It can be seen that the results are reproducible, confirming the reliability of the ETE approach. Additionally, the technique allows for a more complete understanding of systems that have multiple steps that rapidly occur in the

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high-temperature regime, which gives insight into the combustion process [2].

Figure 1. Summary of data collected using the electrothermal explosion technique.

4. Differential thermal analysis/differential scanning calorimetry

This technique has been extensively used in many fields, including: polymer science, biochemistry, and materials science. In order to utilize these methods, a sample is heated at a constant rate until the maximum set temperature is reached. Throughout the experiment, the heat release characteristics of the sample are measured against an inert reference standard.

ETE has been used for different gasless SHS systems. These studies have provided valuable kinetic data in extremely high-temperature ranges that are essentially inaccessible by other

Figure 1. Summary of data collected using the electrothermal explosion technique.

transfer and chemical reactions, it is necessary to consider the specifics of heat transfer mechanisms [5]. Typically, the activation parameters are obtained after experiments considering the dependences of time vs. temperature (for isothermal measurements), temperature vs. heating rate (for integral and incremental methods with linear heating rates), or from reaction rate vs. temperature. Considering the above limitations and complications, only the effective or apparent activation energy can truly be considered, as it includes both the intrinsic kinetics as well as

The task of accurately determining kinetics becomes even more complicated when accounting for

Such parameters are essentially impossible to achieve using conventional approaches for measurement of kinetics parameters. While standard nonisothermal TGA/DTA-based approaches [6] are still used to evaluate the kinetics of SHS reactions, several unique methods such as electrothermal explosion (ETE) [7] and electrothermography (ET) [8] were specifically developed to fit the experimental conditions of SHS reactions. Moreover, recently a variety of advanced in situ diagnostics, including time-resolved X-ray diffraction (TRXRD) [9], high-speed X-ray phasecontrast imaging [10], and high speed transmission electron microscopy (HSTEM) [11] were

The ETE method was developed in 1977 to study the rapid, high-temperature kinetics that occur in SHS systems [7]. It relies on rapid, uniform preheating of the sample until adiabatic thermal explosion occurs. A representation of a typical ETE setup is shown in Figure 1. Briefly, the sample is clamped between two metallic electrodes with sufficient clamping pressure to ensure adequate contact. The power is then initiated, leading to preheating of the sample until a set Toff point. After initiation, the resulting time-temperature profiles are simultaneously collected across a number of high-speed photodiodes. In the commonly used ETA-100 system (Aloft, Inc., Berkley, CA), there are 16 photodiodes present, with 1 mm in between them; this corresponds to 0.5 mm spatial resolution. The photodiodes have a temporal resolution of 10<sup>5</sup> s and are accurate within 900–3000 K. Once the sample is heated to the selected Toff point, the equipment heating is halted, with the consequent rate of self-heating determined solely by the chemical reaction rate. Due to the experimental conditions, i.e., the rapid initial preheating, the reaction occurs in the adiabatic mode. Once thermal ignition occurs, analysis of the time-temperature profile enables extraction of the kinetic parameters (see details in [12]). This technique can be used to study the kinetics at temperatures much higher than can be achieved in other experiments. However, it is often limited in the systems that can be studied

ETE has been used for different gasless SHS systems. These studies have provided valuable kinetic data in extremely high-temperature ranges that are essentially inaccessible by other

–105 K/s).

the extremely high temperatures of SHS processes (>1800 K) and rapid heating rates (103

modified to obtain the kinetics of phase transformations during SHS reactions.

due to the stringent heating conditions caused by Joule preheating.

processes of heat and mass transport.

170 Advanced Chemical Kinetics

3. Electrothermal explosion

2. Techniques for studying SHS kinetics

methods. For carbides, the Ti/C system has been studied [13–15], with additional studies in the Ta/C [14, 16] and Si/C [14, 17] mixtures. The Ti/B system was also investigated [18]. The majority of ETE work being focused on the Ni/Al system [12, 19–21]. The Ti/Fe2O3 system is the only thermite system investigated by ETE [22]. In addition to the experimental studies, a number of theoretical models have been developed to better understand the ETE process [23–26]. Figure 1 shows that ranges of reported activation energies for the above mentioned gasless systems, including both intermetallics and thermites obtained by ETE. It can be seen that the results are reproducible, confirming the reliability of the ETE approach. Additionally, the technique allows for a more complete understanding of systems that have multiple steps that rapidly occur in the high-temperature regime, which gives insight into the combustion process [2].

### 4. Differential thermal analysis/differential scanning calorimetry

This technique has been extensively used in many fields, including: polymer science, biochemistry, and materials science. In order to utilize these methods, a sample is heated at a constant rate until the maximum set temperature is reached. Throughout the experiment, the heat release characteristics of the sample are measured against an inert reference standard. For typical systems, the points of differing heat release characteristics can be due to phase transitions, crystallization, or reactions; however, this section will only focus on SHS-reaction kinetics. In order to determine the reaction kinetics, the experiment is conducted multiple times with different heating rates. The classical method for determining the reaction kinetics, specifically the activation energy, is by use of the Kissinger method [27], however, many alternative methods for data analysis have been suggested and are widely utilized [28–34]. The activation energy, Ea, can be computed by plotting ln(β/T<sup>p</sup> 2 ) as a function of 1/Tp, where T<sup>p</sup> is the peak temperature (Figure 2).

general conclusions can be drawn. Additionally, because the experimental conditions, typically specifically heating rate and temperature ranges, are not the same as in traditional SHS, it is unclear whether the determined values can be directly compared or if there is some systemic

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Figure 2 illustrates the ranges of the obtained values of activation energies for a variety of gasless exothermic reactions measured by DTA method. It can be seen that the determined values are dependent on the experimental conditions utilized, including variations in reactant microstructure, heating rates, among other factors. This issue is discussed in detail below. It would be valuable for systematic studies to be done where these factors are studied in depth across different systems. Additionally, while the activation energies reported using different DTA-based approaches does not appear to be significantly different, it is still important to understand why these differences are present and which methods of analysis are most suitable

There has been significant effort done to accurately correlate experimental combustion parameters, such as combustion wave velocity and temperature, with the kinetics parameters. Two major approaches have been developed to determine the activation energy by measuring the layer-by-layer combustion front combustion velocity. The first was suggested in 1977 by

> RT<sup>2</sup> c E

where f(ηs) is the selected kinetic law. This technique is most commonly used by adding diluent to the sample. This affects the combustion velocity and temperature; the change in both of these values is measured then compared, leading to the kinetic relationship being

The other major approach to determining the kinetics based on the velocity was developed by

where td and tr, are the decay and rise times, with τad being the temperature rise under adiabatic conditions. More complete derivations of these two models can be found in the original articles [62–64]. Additionally, a more complete understanding of these models, including their relative merits, has been examined in a number of prior works [65–68]. In order to properly use these techniques, relatively simple equipment is required. Typically, sets of thermocouples are used to measure combustion wave propagation velocities, but there are many alternatives, such as IR or high-speed cameras, to measure the propagation velocity.

<sup>∂</sup><sup>t</sup> � <sup>α</sup> v2 � � <sup>∂</sup>2<sup>T</sup> ∂t 2

τad

h i � �

<sup>k</sup><sup>0</sup> exp � <sup>E</sup>

f η<sup>s</sup>

RTc � �

� � (8)

(9)

difference that is occurring.

for these systems.

understood.

5. Combustion velocity/temperature analysis

Boddington et al. [63]. The relationship takes the form:

Merzhanov for 1D propagation [62]. The derived equation takes the form:

<sup>v</sup><sup>2</sup> <sup>¼</sup> <sup>λ</sup>

∂η ∂t ¼

ð Þ �ΔH<sup>r</sup> ρ

T�T<sup>0</sup> <sup>t</sup>d�t<sup>r</sup> <sup>þ</sup> <sup>∂</sup><sup>T</sup>

The DTA/DSC based methods are the most widely used for gasless SHS systems, with multiple studies into intermetallics, specifically the Ni/Al [35–43], Ti/Al [44–46], Co/Al [47], Al/Ru [48], Nb/Al [49], and Mg/Al [50] systems, in addition to other binary solid-solid compositions, i.e., the Si/C [51], Mo/Si [52], Zr/B [53], Fe/Se [54]. More complicated ternary systems were also investigated [54–61]. In general, a wide variety of factors can influence the measured kinetics, including variations in reactant microstructure, heating rates, among other factors. Although there are a number of studies into the same systems, it would be valuable for systematic work to be conducted where these factors are studied in depth across different systems to see what

Figure 2. Summary of data collected using isothermal kinetic analysis methods.

general conclusions can be drawn. Additionally, because the experimental conditions, typically specifically heating rate and temperature ranges, are not the same as in traditional SHS, it is unclear whether the determined values can be directly compared or if there is some systemic difference that is occurring.

Figure 2 illustrates the ranges of the obtained values of activation energies for a variety of gasless exothermic reactions measured by DTA method. It can be seen that the determined values are dependent on the experimental conditions utilized, including variations in reactant microstructure, heating rates, among other factors. This issue is discussed in detail below. It would be valuable for systematic studies to be done where these factors are studied in depth across different systems. Additionally, while the activation energies reported using different DTA-based approaches does not appear to be significantly different, it is still important to understand why these differences are present and which methods of analysis are most suitable for these systems.

### 5. Combustion velocity/temperature analysis

For typical systems, the points of differing heat release characteristics can be due to phase transitions, crystallization, or reactions; however, this section will only focus on SHS-reaction kinetics. In order to determine the reaction kinetics, the experiment is conducted multiple times with different heating rates. The classical method for determining the reaction kinetics, specifically the activation energy, is by use of the Kissinger method [27], however, many alternative methods for data analysis have been suggested and are widely utilized [28–34].

The DTA/DSC based methods are the most widely used for gasless SHS systems, with multiple studies into intermetallics, specifically the Ni/Al [35–43], Ti/Al [44–46], Co/Al [47], Al/Ru [48], Nb/Al [49], and Mg/Al [50] systems, in addition to other binary solid-solid compositions, i.e., the Si/C [51], Mo/Si [52], Zr/B [53], Fe/Se [54]. More complicated ternary systems were also investigated [54–61]. In general, a wide variety of factors can influence the measured kinetics, including variations in reactant microstructure, heating rates, among other factors. Although there are a number of studies into the same systems, it would be valuable for systematic work to be conducted where these factors are studied in depth across different systems to see what

2

) as a function of 1/Tp, where T<sup>p</sup>

The activation energy, Ea, can be computed by plotting ln(β/T<sup>p</sup>

Figure 2. Summary of data collected using isothermal kinetic analysis methods.

is the peak temperature (Figure 2).

172 Advanced Chemical Kinetics

There has been significant effort done to accurately correlate experimental combustion parameters, such as combustion wave velocity and temperature, with the kinetics parameters. Two major approaches have been developed to determine the activation energy by measuring the layer-by-layer combustion front combustion velocity. The first was suggested in 1977 by Merzhanov for 1D propagation [62]. The derived equation takes the form:

$$v^2 = \frac{\lambda}{(-\Delta H\_\text{t})\rho} \frac{RT\_\text{c}^2}{E} \frac{k\_0 \exp\left(-\frac{E}{RTc}\right)}{f(\eta\_\text{s})}\tag{8}$$

where f(ηs) is the selected kinetic law. This technique is most commonly used by adding diluent to the sample. This affects the combustion velocity and temperature; the change in both of these values is measured then compared, leading to the kinetic relationship being understood.

The other major approach to determining the kinetics based on the velocity was developed by Boddington et al. [63]. The relationship takes the form:

$$\frac{\partial \mathbf{r}}{\partial t} = \frac{\left[\frac{T - T\_0}{t\_d - t\_r} + \frac{\partial T}{\partial t} - \left(\frac{\alpha}{\alpha^2}\right) \left(\frac{\partial^2 T}{\partial t^2}\right)\right]}{\pi\_{\text{ad}}} \tag{9}$$

where td and tr, are the decay and rise times, with τad being the temperature rise under adiabatic conditions. More complete derivations of these two models can be found in the original articles [62–64]. Additionally, a more complete understanding of these models, including their relative merits, has been examined in a number of prior works [65–68]. In order to properly use these techniques, relatively simple equipment is required. Typically, sets of thermocouples are used to measure combustion wave propagation velocities, but there are many alternatives, such as IR or high-speed cameras, to measure the propagation velocity.

conditions similar to those in SHS wave. Additionally, because the wires are thin, the sample is quenched essentially as soon as the power is turned off. After the wire is cooled, cross-sections of the wire are collected and the width of the product films is measured, which allows for information on the kinetics of phase formation. This, when done at multiple temperatures and

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The electrothermography technique has been widely used to study gas-solid reactions. This is because the wires can be exposed to any sort of gaseous environment and also because of the equipment itself; the wires can be heated with any heating rate, mirroring those found in conventional SHS reactions. Because of this, a number of experiments were conducted in nitrogen environments. In specific, the Ta/N [94], Ti/N [95–98], Nb/N [98, 99], and Zr/N [8] systems have been studies. However, the technique has also be used to study carbides, including the Ti/C [100], Zr/C [100], W/C [101], Nb/C [102], along with other systems, including Mo/

Figure 4 shows the values of the activation energies obtained by this method in gas-solid systems. It can be seen that some reactions have limited steps relating to the gas pressure, while others are relatively independent, suggesting that there are different mechanisms for the

times, gives a more complete picture of the reaction mechanism.

Si [103–106], W/Si [107, 108], Ni/Al [109], and Ni/Ti [109].

Figure 4. Summary of data obtained using the electrothermography approach.

Figure 3. Summary of data collected using layer velocity analysis approached for (a) binary elemental and (b) thermite systems.

Because of the relative simplicity in using these techniques, they have found widespread use within SHS reactions. These layer velocity approaches have been used to describe the kinetics in the Ni/Al system [69, 70], in boride systems, including Nb/B [71–73], Ta/B [71], Zr/B [71, 74, 75], Hf/B [71], Ti/B [76], Mo/B [77], along with other binary systems such as Ti/C [78], Ti/Si [79, 80], thermites [81–89] and more complex ternary systems [78, 90–93].

The results obtained are presented in Figure 3. It can be seen that there are a wide variety of systems analyzed. It worth noting that these data were obtained through direct analysis of the combustion parameters, which were obtained at extremely high temperatures and rapid heating rates, which are difficult to accomplish by other kinetics methods. However, it is important to remember that the quasi-homogeneous approximation is utilized for this layerby-layer combustion front combustion velocity based method, which should be applied with caution [68]. Finally, because this method can be easily used for any type of system, a comparison between thermite and non-thermite type reactions can be analyzed. Comparing Figure 3a and b, it is obvious that the activation energies for thermites is significantly lower than nonthermite type reactions. This is interesting and is likely related to the specific reaction mechanism that occurs in thermites, compared to non-thermites.

### 6. Electrothermography

Electrothermography is a technique that utilizes metal wires in either a gaseous or clad environment [8]. The wire is resistively heated rapidly to the desired temperature, with the electric power being adjusted to compensate for the heat release due to the chemical reaction. The obtained data allows for extraction of the rate of heat generation during the reaction under conditions similar to those in SHS wave. Additionally, because the wires are thin, the sample is quenched essentially as soon as the power is turned off. After the wire is cooled, cross-sections of the wire are collected and the width of the product films is measured, which allows for information on the kinetics of phase formation. This, when done at multiple temperatures and times, gives a more complete picture of the reaction mechanism.

The electrothermography technique has been widely used to study gas-solid reactions. This is because the wires can be exposed to any sort of gaseous environment and also because of the equipment itself; the wires can be heated with any heating rate, mirroring those found in conventional SHS reactions. Because of this, a number of experiments were conducted in nitrogen environments. In specific, the Ta/N [94], Ti/N [95–98], Nb/N [98, 99], and Zr/N [8] systems have been studies. However, the technique has also be used to study carbides, including the Ti/C [100], Zr/C [100], W/C [101], Nb/C [102], along with other systems, including Mo/ Si [103–106], W/Si [107, 108], Ni/Al [109], and Ni/Ti [109].

Figure 4 shows the values of the activation energies obtained by this method in gas-solid systems. It can be seen that some reactions have limited steps relating to the gas pressure, while others are relatively independent, suggesting that there are different mechanisms for the

Figure 4. Summary of data obtained using the electrothermography approach.

Because of the relative simplicity in using these techniques, they have found widespread use within SHS reactions. These layer velocity approaches have been used to describe the kinetics in the Ni/Al system [69, 70], in boride systems, including Nb/B [71–73], Ta/B [71], Zr/B [71, 74, 75], Hf/B [71], Ti/B [76], Mo/B [77], along with other binary systems such as Ti/C [78], Ti/Si

Figure 3. Summary of data collected using layer velocity analysis approached for (a) binary elemental and (b) thermite

The results obtained are presented in Figure 3. It can be seen that there are a wide variety of systems analyzed. It worth noting that these data were obtained through direct analysis of the combustion parameters, which were obtained at extremely high temperatures and rapid heating rates, which are difficult to accomplish by other kinetics methods. However, it is important to remember that the quasi-homogeneous approximation is utilized for this layerby-layer combustion front combustion velocity based method, which should be applied with caution [68]. Finally, because this method can be easily used for any type of system, a comparison between thermite and non-thermite type reactions can be analyzed. Comparing Figure 3a and b, it is obvious that the activation energies for thermites is significantly lower than nonthermite type reactions. This is interesting and is likely related to the specific reaction mecha-

Electrothermography is a technique that utilizes metal wires in either a gaseous or clad environment [8]. The wire is resistively heated rapidly to the desired temperature, with the electric power being adjusted to compensate for the heat release due to the chemical reaction. The obtained data allows for extraction of the rate of heat generation during the reaction under

[79, 80], thermites [81–89] and more complex ternary systems [78, 90–93].

nism that occurs in thermites, compared to non-thermites.

6. Electrothermography

systems.

174 Advanced Chemical Kinetics

two classes of reactions. This is also true for the gasless systems investigated. This method provides a window into determining the mechanism and, due to the nature of the experiment, allows for control over the experimental conditions to the degree that individual steps in the reaction can be isolated.

### 7. Modern in situ high-speed high-resolution methods

There currently exist a number of techniques to study in situ reactions on the time and length scales that occur during SHS reactions; these techniques are incredibly valuable to determine the reaction mechanisms. The most widespread technique is time-resolved X-ray diffraction (TRXRD), and is used to determine the phases that are present during the reaction. It allows for information on the phases present at every stage of the reaction, depending on the time resolution. The lower the time resolution, the more information that can be attained. Depending on the specific setup, whether synchrotron or laboratory-scale based, time resolutions ranging from 10<sup>6</sup> to 10<sup>2</sup> s are reasonable, with the absolute limit being continually improved with improved synchrotron and detector technology. There has been significant work done with SHS systems due to their solid nature, which is simple to use in TRXRD systems. It is possible to measure solid solution formations, intermediate phases, any melting processes, and the general reaction progress. Through these data it should be possible to extract kinetic data on all reaction stages based on the growth rates of the peaks for the new phase formation coupled with the decomposition of peaks from the previous phase, however, there are currently no established models illustrating this.

There have been a wide variety of experiments conducted on SHS systems by a number of different groups. For intermetallic systems, groups have studied the Ni–Al [9, 110–116], Fe–Al [111, 117–121], Nb–Al [122–124], and numerous other systems [110, 125–127]. Additionally, many groups have examined other SHS based systems, such as carbides, including Ti–C [110, 128, 129], Ta–C [129, 130], and other carbides and cermets [129, 131–134], nitrides [135, 136], oxides [137–139], silicides, including Fe–Si [140, 141], Mo–Si [119, 123, 142, 143] and Ti–Si [144, 145], among a variety of other systems [113, 129, 146–155].

dynamics with nanosecond time resolution. The current DTEM performance shows a spatial resolution less than 10 nm for single-shot imaging, using 15 ns electron pulses. The solid-state reactions in NiAl reactive multilayer films, the martensitic transformations in nanocrystalline

Figure 5. Dynamic single-shot diffraction with 15-ns time resolution of regions before, during, and after the exothermic mixing reaction front has passed. The times indicated at right are in relation to the reaction front, set at t = 0 s. The crystal structure clearly changes from separate fcc Al/Ni and Ni/V layers to an intermetallic B2 structure NiAl phase within

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The above unique diagnostics, which are used to determine phase and structural transformations in situ, are incredibly valuable. Used alone, they provide information on the reaction progress and mechanism; however, there are two significant paths that would make these techniques more valuable. When coupled with current methods for determination of kinetics, the understanding of the reaction mechanisms in all systems will be improved. Furthermore, there is no current way to extract kinetic parameters from some techniques (TRXRD, DTEM, etc.);

There have been a number of studies shown that indicated that the structure of materials plays a role in the kinetics; multiple groups using a wide variety of techniques and approaches have confirmed this conclusion. For example, it was shown that by changing the internal structure

Ti, and the catalytic growth of Si nanowires were studied by DTEM [156].

300 ns after the arrival of the hot reaction front; a.u., arbitrary units. Adapted from Kim et al. [11].

it would be valuable to develop reliable approaches for these techniques.

8. Structure-kinetics relationship of SHS systems

In addition to TRXRD, there is a variety of other, less common, but still very useful techniques available. For example, high-speed X-ray phase-contrast imaging [10] utilizes a synchrotron source coupled with the fact that different phases absorb X-rays differently to determine which phase transformations occur during reaction, essentially high-speed X-ray phase contrast imaging. This technique was illustrated on the W-Si system at the Advanced Proton Source in Argonne National Laboratory. This method allowed for direct imaging of irreversible reactions in the W-Si reactive system at frame rates up to 36,000 frames per second with a 4-μs exposure time and spatial resolution of 10 μm. Another advanced technique is high-speed transmission electron microscopy (HSTEM) [11], which utilizes all abilities of conventional TEM, but at nanosecond time scales. This allows for direct observation of both the structural changes and crystal structure during the reaction with unprecedented resolution, as shown in Figure 5. Specifically, a high-time resolution dynamic transmission electron microscopy (DTEM) was developed in Lawrence Livermore National Laboratory (USA) and captures the material

two classes of reactions. This is also true for the gasless systems investigated. This method provides a window into determining the mechanism and, due to the nature of the experiment, allows for control over the experimental conditions to the degree that individual steps in the

There currently exist a number of techniques to study in situ reactions on the time and length scales that occur during SHS reactions; these techniques are incredibly valuable to determine the reaction mechanisms. The most widespread technique is time-resolved X-ray diffraction (TRXRD), and is used to determine the phases that are present during the reaction. It allows for information on the phases present at every stage of the reaction, depending on the time resolution. The lower the time resolution, the more information that can be attained. Depending on the specific setup, whether synchrotron or laboratory-scale based, time resolutions ranging from 10<sup>6</sup> to 10<sup>2</sup> s are reasonable, with the absolute limit being continually improved with improved synchrotron and detector technology. There has been significant work done with SHS systems due to their solid nature, which is simple to use in TRXRD systems. It is possible to measure solid solution formations, intermediate phases, any melting processes, and the general reaction progress. Through these data it should be possible to extract kinetic data on all reaction stages based on the growth rates of the peaks for the new phase formation coupled with the decomposition of peaks from the previous phase, however,

There have been a wide variety of experiments conducted on SHS systems by a number of different groups. For intermetallic systems, groups have studied the Ni–Al [9, 110–116], Fe–Al [111, 117–121], Nb–Al [122–124], and numerous other systems [110, 125–127]. Additionally, many groups have examined other SHS based systems, such as carbides, including Ti–C [110, 128, 129], Ta–C [129, 130], and other carbides and cermets [129, 131–134], nitrides [135, 136], oxides [137–139], silicides, including Fe–Si [140, 141], Mo–Si [119, 123, 142, 143] and Ti–Si [144,

In addition to TRXRD, there is a variety of other, less common, but still very useful techniques available. For example, high-speed X-ray phase-contrast imaging [10] utilizes a synchrotron source coupled with the fact that different phases absorb X-rays differently to determine which phase transformations occur during reaction, essentially high-speed X-ray phase contrast imaging. This technique was illustrated on the W-Si system at the Advanced Proton Source in Argonne National Laboratory. This method allowed for direct imaging of irreversible reactions in the W-Si reactive system at frame rates up to 36,000 frames per second with a 4-μs exposure time and spatial resolution of 10 μm. Another advanced technique is high-speed transmission electron microscopy (HSTEM) [11], which utilizes all abilities of conventional TEM, but at nanosecond time scales. This allows for direct observation of both the structural changes and crystal structure during the reaction with unprecedented resolution, as shown in Figure 5. Specifically, a high-time resolution dynamic transmission electron microscopy (DTEM) was developed in Lawrence Livermore National Laboratory (USA) and captures the material

7. Modern in situ high-speed high-resolution methods

there are currently no established models illustrating this.

145], among a variety of other systems [113, 129, 146–155].

reaction can be isolated.

176 Advanced Chemical Kinetics

Figure 5. Dynamic single-shot diffraction with 15-ns time resolution of regions before, during, and after the exothermic mixing reaction front has passed. The times indicated at right are in relation to the reaction front, set at t = 0 s. The crystal structure clearly changes from separate fcc Al/Ni and Ni/V layers to an intermetallic B2 structure NiAl phase within 300 ns after the arrival of the hot reaction front; a.u., arbitrary units. Adapted from Kim et al. [11].

dynamics with nanosecond time resolution. The current DTEM performance shows a spatial resolution less than 10 nm for single-shot imaging, using 15 ns electron pulses. The solid-state reactions in NiAl reactive multilayer films, the martensitic transformations in nanocrystalline Ti, and the catalytic growth of Si nanowires were studied by DTEM [156].

The above unique diagnostics, which are used to determine phase and structural transformations in situ, are incredibly valuable. Used alone, they provide information on the reaction progress and mechanism; however, there are two significant paths that would make these techniques more valuable. When coupled with current methods for determination of kinetics, the understanding of the reaction mechanisms in all systems will be improved. Furthermore, there is no current way to extract kinetic parameters from some techniques (TRXRD, DTEM, etc.); it would be valuable to develop reliable approaches for these techniques.

### 8. Structure-kinetics relationship of SHS systems

There have been a number of studies shown that indicated that the structure of materials plays a role in the kinetics; multiple groups using a wide variety of techniques and approaches have confirmed this conclusion. For example, it was shown that by changing the internal structure of the reactive composite by using high-energy ball milling (HEBM) in the same binary system, one can significantly change the measured effective activation energy [20]. There are two approaches to quantifying this effect; the first is by rigorous quantification of the already existing structures, and the second is by use of more simple, so-called model microstructures, typically manifested in reactive nanofoils with periodically fabricated layers of reactants.

Shuck et al. utilized two techniques for quantitative determination of HEBM-produced materials [5, 157]. The first technique, X-ray Nanotomography, works by passing high brilliance X-rays through the sample and collecting the transmitted X-rays. In order to convert this 2D projection into three dimensions, the sample is rotated and the same quality of X-rays is passed through again and the projections at different angles are collected; this collection of images can be combined, leading to a 3D map of the internal sample. The second technique, focused ion beam (FIB) sectioning, uses a FIB to serially section the HEBM-produced particles. The series of images were first shear corrected, contrast normalized, and then aligned using a least-squares method, with the reconstructions shown in Figure 6. After structure analysis, Shuck and

Mukasyan [20] further studied these effects on the kinetics in the Ni–Al system using the ETE approach. They showed, by use of the above 3D reconstruction techniques, that it is possible to control the activation energy by modification of the contact surface area between the reactants. Effectively, they lowered the effective activation energy from 79 to 137 kJ/mol, which corresponded to a change in the contact surface area/volume ratio between 0.0120 and

Figure 7. Dependence of effective activation energy of the reaction as a function specific contact surface area between Ni

suggested that, for SHS systems, the apparent activation energy is affected primarily by the contributions between the diffusion and intrinsic reaction activation energies. Additionally, they offered an explanation for the relationship, relating to the difference in contribution between the diffusive activation energies (volume, grain-boundary, and surface) in conjunction with the intrinsic activation energy. This suggests that the measured and reported activation energies presented in literature are effective, or apparent, activation energies that depend highly on the

In a very early study on the reaction mechanisms, Philpot et al. examined the effect of varying factors on the reaction rate [35]. In one study, they systematically varied the aluminum concentration, the heating rate, and the nickel particle size. Briefly, they showed that, depending on the applied heating rate, two different mechanisms could be initiated. The first, when using slower heating rates, was related to the melting of the aluminum metal, followed by spreading over the nickel particles. For their studies, they saw two definite peaks relating to the reaction.

9. Modification of the reaction mechanism depending on the

, respectively; this relationship is shown in Figure 7. Additionally, it was

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0.0032 nm<sup>1</sup>

structure and experimental conditions.

and Al phases. Adapted from Shuck and Mukasyan [20].

experimental conditions

Figure 6. Reconstructed internal volumes of the nanocomposites for different time (min) of WG: (a) 10, (b) 20, (c) 30, and (d) 40 (Ni is the gray phase, and Al is the void-space). Adapted from Shuck et al. [5].

of the reactive composite by using high-energy ball milling (HEBM) in the same binary system, one can significantly change the measured effective activation energy [20]. There are two approaches to quantifying this effect; the first is by rigorous quantification of the already existing structures, and the second is by use of more simple, so-called model microstructures, typically manifested in reactive nanofoils with periodically fabricated layers of reactants.

178 Advanced Chemical Kinetics

Shuck et al. utilized two techniques for quantitative determination of HEBM-produced materials [5, 157]. The first technique, X-ray Nanotomography, works by passing high brilliance X-rays through the sample and collecting the transmitted X-rays. In order to convert this 2D projection into three dimensions, the sample is rotated and the same quality of X-rays is passed through again and the projections at different angles are collected; this collection of images can be combined, leading to a 3D map of the internal sample. The second technique, focused ion beam (FIB) sectioning, uses a FIB to serially section the HEBM-produced particles. The series of images were first shear corrected, contrast normalized, and then aligned using a least-squares method, with the reconstructions shown in Figure 6. After structure analysis, Shuck and

Figure 6. Reconstructed internal volumes of the nanocomposites for different time (min) of WG: (a) 10, (b) 20, (c) 30, and

(d) 40 (Ni is the gray phase, and Al is the void-space). Adapted from Shuck et al. [5].

Figure 7. Dependence of effective activation energy of the reaction as a function specific contact surface area between Ni and Al phases. Adapted from Shuck and Mukasyan [20].

Mukasyan [20] further studied these effects on the kinetics in the Ni–Al system using the ETE approach. They showed, by use of the above 3D reconstruction techniques, that it is possible to control the activation energy by modification of the contact surface area between the reactants. Effectively, they lowered the effective activation energy from 79 to 137 kJ/mol, which corresponded to a change in the contact surface area/volume ratio between 0.0120 and 0.0032 nm<sup>1</sup> , respectively; this relationship is shown in Figure 7. Additionally, it was suggested that, for SHS systems, the apparent activation energy is affected primarily by the contributions between the diffusion and intrinsic reaction activation energies. Additionally, they offered an explanation for the relationship, relating to the difference in contribution between the diffusive activation energies (volume, grain-boundary, and surface) in conjunction with the intrinsic activation energy. This suggests that the measured and reported activation energies presented in literature are effective, or apparent, activation energies that depend highly on the structure and experimental conditions.

### 9. Modification of the reaction mechanism depending on the experimental conditions

In a very early study on the reaction mechanisms, Philpot et al. examined the effect of varying factors on the reaction rate [35]. In one study, they systematically varied the aluminum concentration, the heating rate, and the nickel particle size. Briefly, they showed that, depending on the applied heating rate, two different mechanisms could be initiated. The first, when using slower heating rates, was related to the melting of the aluminum metal, followed by spreading over the nickel particles. For their studies, they saw two definite peaks relating to the reaction.

this system. Thus it is possible to compare the data collected across a large number of experimental conditions to give more complete understanding of this gasless reaction. Although this system has been extensively studied for over 40 years now, a consensus has not emerged on the exact activation energy, as can be seen in Figure 9. The data again illustrate the effect that differing experimental conditions play, whether in the material structure, heating rates, or

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In 1987, Philpot et al. did preliminary studies on the Ni/Al system kinetics using the Kissinger approach [35]. They showed that there is an effect of heating rate, the nickel particle size, as well as an effect of a varying Al content, on the reaction mechanism in this system [35], this work is highlighted in more detail in an above section. Hunt et al. examined the effect of particle size on the apparent activation energy using a CO2 laser to control the heating coupled with the DTA-based Kissinger approach. Using 800 nm size Ni particles coupled with 20 μm, 4 μm, 80 nm, and 40 nm Al particles, it was found that that these reactions had activation energies of: 103.5 10.5, 97.3 5, 21.2 2.5, and 17.4 2.85 kJ/mol, respectively [36]. They then increased the Ni size to 15 μm and measured with the four Al sizes, resulting in 162.5 1.4, 131.2 2.6, 103.6 5.2, and 80.1 6.3 kJ/mol, respectively [36]. This confirms that the initial reactant structure plays a significant impact on the kinetics. The size of either reactant significantly alters the effective kinetics. Kim et al. studied this reaction using nanolaminated composite micro-foils with different thickness ratios between Ni and Al at heating rates between 5 and 100 K/min. For 4:1 foils, they found that the formation of NiAl3 occurred, followed by Ni2Al3, with activation energies of 142 and 106 kJ/mol, respectively [37].

other experimental factors.

Figure 9. Summary of kinetic data collected for the Ni/Al system.

Figure 8. DTA-TG curves for the PTFE-Al2O3 system using heating rates of (a) 20, (b) 80, (c) 150, and (d) 160C min<sup>1</sup> under an argon atmosphere. The additional lines are showing the changes in heat flow and mass percentage values. Adapted from Hobosyan et al. [56].

However, when they increased the heating rate, they instead only witnessed a single peak. This peak was related to the solid state transition to the final product. For transitional values between the two extremes, they found that there were relative contributions of both different mechanisms. This is an important observation which should be accounted when investigating the reaction kinetics in highly exothermic systems. Indeed, it shows that it is possible to control the reaction mechanism depending on the applied experimental conditions. This effect was confirmed by many researchers both for gasless and gas-solid systems [36, 56, 158–162] and is illustrated in Figure 8. Furthermore, depending on the reaction mechanism, it is possible to control both the final product phases and their microstructures, thus producing materials with tailored properties.

#### 10. The Ni/Al system as a model for SHS kinetics

In the SHS community, the Ni/Al system has been widely used a model system. It was chosen because of its low ignition temperature, high oxidation resistance, and ease of processing. Because of this, all of the above mentioned techniques have been utilized to study kinetics in this system. Thus it is possible to compare the data collected across a large number of experimental conditions to give more complete understanding of this gasless reaction. Although this system has been extensively studied for over 40 years now, a consensus has not emerged on the exact activation energy, as can be seen in Figure 9. The data again illustrate the effect that differing experimental conditions play, whether in the material structure, heating rates, or other experimental factors.

In 1987, Philpot et al. did preliminary studies on the Ni/Al system kinetics using the Kissinger approach [35]. They showed that there is an effect of heating rate, the nickel particle size, as well as an effect of a varying Al content, on the reaction mechanism in this system [35], this work is highlighted in more detail in an above section. Hunt et al. examined the effect of particle size on the apparent activation energy using a CO2 laser to control the heating coupled with the DTA-based Kissinger approach. Using 800 nm size Ni particles coupled with 20 μm, 4 μm, 80 nm, and 40 nm Al particles, it was found that that these reactions had activation energies of: 103.5 10.5, 97.3 5, 21.2 2.5, and 17.4 2.85 kJ/mol, respectively [36]. They then increased the Ni size to 15 μm and measured with the four Al sizes, resulting in 162.5 1.4, 131.2 2.6, 103.6 5.2, and 80.1 6.3 kJ/mol, respectively [36]. This confirms that the initial reactant structure plays a significant impact on the kinetics. The size of either reactant significantly alters the effective kinetics. Kim et al. studied this reaction using nanolaminated composite micro-foils with different thickness ratios between Ni and Al at heating rates between 5 and 100 K/min. For 4:1 foils, they found that the formation of NiAl3 occurred, followed by Ni2Al3, with activation energies of 142 and 106 kJ/mol, respectively [37].

Figure 9. Summary of kinetic data collected for the Ni/Al system.

However, when they increased the heating rate, they instead only witnessed a single peak. This peak was related to the solid state transition to the final product. For transitional values between the two extremes, they found that there were relative contributions of both different mechanisms. This is an important observation which should be accounted when investigating the reaction kinetics in highly exothermic systems. Indeed, it shows that it is possible to control the reaction mechanism depending on the applied experimental conditions. This effect was confirmed by many researchers both for gasless and gas-solid systems [36, 56, 158–162] and is illustrated in Figure 8. Furthermore, depending on the reaction mechanism, it is possible to control both the final product phases and their microstructures, thus producing materials with

Figure 8. DTA-TG curves for the PTFE-Al2O3 system using heating rates of (a) 20, (b) 80, (c) 150, and (d) 160C min<sup>1</sup> under an argon atmosphere. The additional lines are showing the changes in heat flow and mass percentage values.

In the SHS community, the Ni/Al system has been widely used a model system. It was chosen because of its low ignition temperature, high oxidation resistance, and ease of processing. Because of this, all of the above mentioned techniques have been utilized to study kinetics in

10. The Ni/Al system as a model for SHS kinetics

tailored properties.

Adapted from Hobosyan et al. [56].

180 Advanced Chemical Kinetics

In order to more fully understand the relationship between structure and the kinetics, White et al. investigated the effect of mechanical activation (MA) on the Ni/Al system kinetics using the Kissinger approach. Two types of Ni/Al composites were used; Ni clad Al particles, as well as Ni/Al composite particles produced by high-energy ball milling (HEBM). The Ni clad Al particles were found to have an apparent activation energy of 352 8 kJ/mol, while after MA the particles had much lower activation energy of 117 4 kJ/mol [38]. Reeves et al. studied the thermal and impact reaction kinetics in the Ni/Al system for both MA and nano-sized reactants using the Kissinger approach. For the nano-mixture, the reactants were both ~80 nm in size and, for the MA particles, they underwent 15 minutes of HEBM. The nano-mixture exhibited a 230 21 kJ/mol activation energy, while the MA mixture was calculated to be 117 8 kJ/mol [39]. Manukyan et al. studied the Ni/Al system after MA and the effect of a coarse vs. nanolaminated nanostructure on the kinetics using the Kissinger approach. Using heating rates between 10 and 50 K/min, they found that the reaction proceeds in three steps, NiAl3, Ni2Al3, and then finally NiAl. For the coarse microstructure, these peaks corresponded to 99 4, 138 13, and 120 37 kJ/mol, while the nanolaminated microstructure corresponded to 93 2.5, 145 13, and 146 14 kJ/mol, respectively [40]. This illustrated that the activation energies depend on the microstructure, even after MA.

Kuk et al. studied compression bonded Ni/Al nanofoils with and without a BN lubricant using the Kissinger approach. With the BN lubricant, it was found that the reaction proceeded in two steps, with the activation energies being 224 and 272 kJ/mol, respectively, resulting in the formation of Al3Ni2 [42]. Without the lubricant, the reaction proceeded in a single step with activation energy of 470 kJ/mol, this difference was attributed to the oxide layer between the reactants [42]. Maiti and Ghoroi studied the Ni/Al system using the Friedman, Ozawa, and Kissinger approach, yielding activation energies of 437.0, 448.4, and 457.6 kJ/mol, respectively [43].

system using electrothermography. Their results showed that the reactions occur first through grain boundary diffusion, followed by diffusion of the solid metal into the liquid phase [109]. Finally, Mukasyan et al. examined the Ni/Al system using a combination of TRXRD and ETE, showing that the reaction mechanism itself changes based on the structure, this work is

Figure 10. Arrhenius plots for reactions in Al clad by Ni systems before and after high energy ball milling. Adapted from

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Thus we may conclude that although a wide variety of studies were conducted on the Ni/Al system with many different experimental and structural conditions, the reported values of activation energies vary drastically. Additionally, there would be great benefit to combining utilizing multiple methods simultaneously to bridge understanding between the different

More complete understanding on the kinetics of SHS reactions is vital for both fundamental science and also for practical or industrial reasons. To better understand the kinetics, combinations of techniques must be utilized, specifically coupling techniques that give information on the kinetics while simultaneously examining the phase transformations that are occurring. To further understand the reaction mechanisms, additional studies must be conducted on the relationship between the structure and the resulting kinetics. Additionally, work must be done to compare the different methods of studying kinetics and their interrelationships. In the limited cases where there is data available for the same system across different techniques,

highlighted in an above section [116].

11. Future directions in SHS kinetics

experimental techniques.

Shteinberg et al. [12].

Using the ETE approach, Shteinberg et al. and Mukasyan et al. confirmed that MA affects the activation energy in the Ni/Al system, as shown in Figure 10 [12, 19]. Initially, they studied the kinetics of the Ni clad Al system (which was also studied in [38]), which showed two distinct steps. The first step was related to the melting of Al and subsequent cracking of the Ni layer, which had an activation energy of 197 29 kJ/mol. The final step was the diffusion of Ni into Al, which was measured as 523 84 kJ/mol. In the MA system, they found that only a single step occurred and was measured to be 105 13 kJ/mol. Shuck and Mukasyan further studied the effects of MA on the kinetics in the Ni/Al system using the ETE approach [20]. Using 3D reconstruction techniques, they showed that the surface area contact between the reactions is directly related to the effective activation energy, which ranged from 79 to 137 kJ/mol, which corresponded to a change in the contact surface area/volume ratio between 0.0120 and 0.0032 nm<sup>1</sup> , respectively. This work is further highlighted in an above section. Finally, using the ETE approach, Filimonov et al. studied the effects of MA on the nonstoichiometric, 3Ni/Al system [21]. They utilized a criterion based on the minimum curvature of the heating rate logarithm, which resulted in an anomalously low measured activation energy of 9.5 2 kJ/mol.

Marin-Ayral et al. studied the Ni/Al system under different gas pressures using the Boddington-Laye method. They showed that for pressures of 100, 320, and 500 MPa, the measured activation energies were 47, 59, and 132 kJ/mol, respectively [68, 69]. Vadchenko et al. studied the Ni/Al

Figure 10. Arrhenius plots for reactions in Al clad by Ni systems before and after high energy ball milling. Adapted from Shteinberg et al. [12].

system using electrothermography. Their results showed that the reactions occur first through grain boundary diffusion, followed by diffusion of the solid metal into the liquid phase [109]. Finally, Mukasyan et al. examined the Ni/Al system using a combination of TRXRD and ETE, showing that the reaction mechanism itself changes based on the structure, this work is highlighted in an above section [116].

Thus we may conclude that although a wide variety of studies were conducted on the Ni/Al system with many different experimental and structural conditions, the reported values of activation energies vary drastically. Additionally, there would be great benefit to combining utilizing multiple methods simultaneously to bridge understanding between the different experimental techniques.

### 11. Future directions in SHS kinetics

In order to more fully understand the relationship between structure and the kinetics, White et al. investigated the effect of mechanical activation (MA) on the Ni/Al system kinetics using the Kissinger approach. Two types of Ni/Al composites were used; Ni clad Al particles, as well as Ni/Al composite particles produced by high-energy ball milling (HEBM). The Ni clad Al particles were found to have an apparent activation energy of 352 8 kJ/mol, while after MA the particles had much lower activation energy of 117 4 kJ/mol [38]. Reeves et al. studied the thermal and impact reaction kinetics in the Ni/Al system for both MA and nano-sized reactants using the Kissinger approach. For the nano-mixture, the reactants were both ~80 nm in size and, for the MA particles, they underwent 15 minutes of HEBM. The nano-mixture exhibited a 230 21 kJ/mol activation energy, while the MA mixture was calculated to be 117 8 kJ/mol [39]. Manukyan et al. studied the Ni/Al system after MA and the effect of a coarse vs. nanolaminated nanostructure on the kinetics using the Kissinger approach. Using heating rates between 10 and 50 K/min, they found that the reaction proceeds in three steps, NiAl3, Ni2Al3, and then finally NiAl. For the coarse microstructure, these peaks corresponded to 99 4, 138 13, and 120 37 kJ/mol, while the nanolaminated microstructure corresponded to 93 2.5, 145 13, and 146 14 kJ/mol, respectively [40]. This illustrated that the activation

Kuk et al. studied compression bonded Ni/Al nanofoils with and without a BN lubricant using the Kissinger approach. With the BN lubricant, it was found that the reaction proceeded in two steps, with the activation energies being 224 and 272 kJ/mol, respectively, resulting in the formation of Al3Ni2 [42]. Without the lubricant, the reaction proceeded in a single step with activation energy of 470 kJ/mol, this difference was attributed to the oxide layer between the reactants [42]. Maiti and Ghoroi studied the Ni/Al system using the Friedman, Ozawa, and Kissinger approach,

Using the ETE approach, Shteinberg et al. and Mukasyan et al. confirmed that MA affects the activation energy in the Ni/Al system, as shown in Figure 10 [12, 19]. Initially, they studied the kinetics of the Ni clad Al system (which was also studied in [38]), which showed two distinct steps. The first step was related to the melting of Al and subsequent cracking of the Ni layer, which had an activation energy of 197 29 kJ/mol. The final step was the diffusion of Ni into Al, which was measured as 523 84 kJ/mol. In the MA system, they found that only a single step occurred and was measured to be 105 13 kJ/mol. Shuck and Mukasyan further studied the effects of MA on the kinetics in the Ni/Al system using the ETE approach [20]. Using 3D reconstruction techniques, they showed that the surface area contact between the reactions is directly related to the effective activation energy, which ranged from 79 to 137 kJ/mol, which corresponded to a change in the contact surface area/volume ratio between 0.0120 and

, respectively. This work is further highlighted in an above section. Finally, using

the ETE approach, Filimonov et al. studied the effects of MA on the nonstoichiometric, 3Ni/Al system [21]. They utilized a criterion based on the minimum curvature of the heating rate logarithm, which resulted in an anomalously low measured activation energy of 9.5 2 kJ/mol. Marin-Ayral et al. studied the Ni/Al system under different gas pressures using the Boddington-Laye method. They showed that for pressures of 100, 320, and 500 MPa, the measured activation energies were 47, 59, and 132 kJ/mol, respectively [68, 69]. Vadchenko et al. studied the Ni/Al

yielding activation energies of 437.0, 448.4, and 457.6 kJ/mol, respectively [43].

energies depend on the microstructure, even after MA.

0.0032 nm<sup>1</sup>

182 Advanced Chemical Kinetics

More complete understanding on the kinetics of SHS reactions is vital for both fundamental science and also for practical or industrial reasons. To better understand the kinetics, combinations of techniques must be utilized, specifically coupling techniques that give information on the kinetics while simultaneously examining the phase transformations that are occurring. To further understand the reaction mechanisms, additional studies must be conducted on the relationship between the structure and the resulting kinetics. Additionally, work must be done to compare the different methods of studying kinetics and their interrelationships. In the limited cases where there is data available for the same system across different techniques, there is a wide range of published kinetic data. It is imperative to continue to study SHS kinetics in a more systematic, fundamental fashion.

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### Acknowledgements

This work was supported by the Department of Energy, National Nuclear Security Administration, under the award number DE-NA0002377 as part of the Predictive Science Academic Alliance Program II. We also acknowledge the Ministry of Education and Science of the Russian Federation specifically Increase Competitiveness Program of NUST 'MISiS' (No. K2- 2016-065), implemented by a governmental decree dated 16th of March 2013, N 211. Finally, this work was also supported by the U.S. Department of State through the Fulbright program.

### Author details

Christopher E. Shuck<sup>1</sup> and Alexander S. Mukasyan1,2\*

\*Address all correspondence to: amoukasi@nd.edu

1 Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana, United States

2 University of Notre Dame and National University of Science and Technology MISiS, Moscow, Russia

### References


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there is a wide range of published kinetic data. It is imperative to continue to study SHS

This work was supported by the Department of Energy, National Nuclear Security Administration, under the award number DE-NA0002377 as part of the Predictive Science Academic Alliance Program II. We also acknowledge the Ministry of Education and Science of the Russian Federation specifically Increase Competitiveness Program of NUST 'MISiS' (No. K2- 2016-065), implemented by a governmental decree dated 16th of March 2013, N 211. Finally, this work was also supported by the U.S. Department of State through the Fulbright program.

1 Department of Chemical and Biomolecular Engineering, University of Notre Dame,

2 University of Notre Dame and National University of Science and Technology MISiS,

tory compounds. Doklady Chemistry. 1972;204(2):429-431

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Christopher E. Shuck<sup>1</sup> and Alexander S. Mukasyan1,2\*

\*Address all correspondence to: amoukasi@nd.edu

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Notre Dame, Indiana, United States

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Author details

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[149] Contreras L, Turrillas X, Vaughan GBM, Kvick Å, Rodrıguez MA. Time-resolved XRD study of TiC-TiB2 composites obtained by SHS. Acta Materialia. 2004;52(16):4783-4790

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[152] Mas-Guindal MJ, Turrillas X, Hansen T, Rodríguez MA. Time-resolved neutron diffraction study of Ti-TiC-Al2O3 composites obtained by SHS. Journal of the European

[153] Kovalev DY, Prokudina VK, Ratnikov VI, Ponomarev VI. Thermal decomposition of TiH2: A TRXRD study. International Journal of Self-Propagating High-Temperature

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[134] Boutefnouchet H, Curfs C, Triki A, Boutefnouchet A, Vrel D. Self-propagating hightemperature synthesis mechanisms within the Ti-C-Ni system: A time resolved X-ray

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**Chapter 11**

Provisional chapter

H NMR).

**Ultrasound as a Metrological Tool for Monitoring**

DOI: 10.5772/intechopen.70501

Ultrasound as a Metrological Tool for Monitoring

Ultrasound has been widely used as a technological alternative way to analyse noninvasively an assortment of materials. It includes liquids with dissimilar physical characteristics, including mono- and multi-phasic mixtures, suspension formation and dissolution, in-line processing, among other practical applications. Regardless the huge spread of uses, so far ultrasound has not been proved to be able to quantify transesterification kinetics with a metrological approach. The aim of this chapter is to demonstrate that a properly designed ultrasonic experiment can be developed to identify remarkable stages of a transesterification reaction to produce biodiesel. The method was compared both with gas chromatography and hydrogen nuclear magnetic resonance (1

For an in-line application, ultrasound has been proved to work properly as a monitoring

Keywords: ultrasound, metrology, chemical kinetics, monitoring, biodiesel production

Currently, in the chemical, food, petrochemical and other industries, there is a considerable demand for measuring instruments that are able to characterize liquids with high sensitivity, robustness and precision. An instrument that is able to perform the process accurately, ranging from chemical reactions (production) to quality control (final product), is necessary. Due to the automation of processes, in-line measurements are increasingly being studied to ensure that

> © The Author(s). Licensee InTech. 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 eproduction in any medium, provided the original work is properly cited.

© 2018 The Author(s). Licensee InTech. 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.

**Transesterification Kinetics**

Transesterification Kinetics

Raphaela M. Baêsso, Pâmella A. Oliveira, Gabriel C. Moraes, André V. Alvarenga and

Raphaela M. Baêsso, Pâmella A. Oliveira, Gabriel C. Moraes, André V. Alvarenga and

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.70501

tool for chemical reaction kinetics.

the product is in conformity to technical requirements [1–5].

Rodrigo P.B. Costa-Félix

Rodrigo P.B. Costa-Félix

Abstract

1. Introduction


Provisional chapter

### **Ultrasound as a Metrological Tool for Monitoring Transesterification Kinetics** Ultrasound as a Metrological Tool for Monitoring

DOI: 10.5772/intechopen.70501

Raphaela M. Baêsso, Pâmella A. Oliveira, Gabriel C. Moraes, André V. Alvarenga and Rodrigo P.B. Costa-Félix Raphaela M. Baêsso, Pâmella A. Oliveira, Gabriel C. Moraes, André V. Alvarenga and

Transesterification Kinetics

Additional information is available at the end of the chapter Rodrigo P.B. Costa-Félix

http://dx.doi.org/10.5772/intechopen.70501 Additional information is available at the end of the chapter

#### Abstract

[160] Moore JJ, Feng HJ. Combustion synthesis of advanced materials: Part I. Reaction param-

[161] Yi HC, Moore JJ. Self-propagating high-temperature (combustion) synthesis (SHS) of powder-compacted materials. Journal of Materials Science. 1990;25(2):1159-1168 [162] Yum JT, Moon JT, Lee YH, Kim YS. Synthesis and microstructure control of TiAl via

combustion synthesis. Metals and Materials International. 1995;1(1):19-27

eters. Progress in Materials Science. 1995;39(4–5):243-273

196 Advanced Chemical Kinetics

Ultrasound has been widely used as a technological alternative way to analyse noninvasively an assortment of materials. It includes liquids with dissimilar physical characteristics, including mono- and multi-phasic mixtures, suspension formation and dissolution, in-line processing, among other practical applications. Regardless the huge spread of uses, so far ultrasound has not been proved to be able to quantify transesterification kinetics with a metrological approach. The aim of this chapter is to demonstrate that a properly designed ultrasonic experiment can be developed to identify remarkable stages of a transesterification reaction to produce biodiesel. The method was compared both with gas chromatography and hydrogen nuclear magnetic resonance (1 H NMR). For an in-line application, ultrasound has been proved to work properly as a monitoring tool for chemical reaction kinetics.

Keywords: ultrasound, metrology, chemical kinetics, monitoring, biodiesel production

### 1. Introduction

Currently, in the chemical, food, petrochemical and other industries, there is a considerable demand for measuring instruments that are able to characterize liquids with high sensitivity, robustness and precision. An instrument that is able to perform the process accurately, ranging from chemical reactions (production) to quality control (final product), is necessary. Due to the automation of processes, in-line measurements are increasingly being studied to ensure that the product is in conformity to technical requirements [1–5].

© 2018 The Author(s). Licensee InTech. 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.

© The Author(s). Licensee InTech. 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 eproduction in any medium, provided the original work is properly cited.

The competitiveness of companies for which the core business is the production of consumer goods is directly linked to their production process. Quality and productivity, once seen as dissociated elements, now are joined together, strongly impacting business competitiveness, improving process performance, product quality and reducing costs. In this way, the study of the kinetics of chemical processes allows the optimization of the process, avoiding the waste not only of raw materials, but also of energy and time [6].

Within this chapter, we will disclose the recent outcomes of a research in which ultrasound has been used as a way of monitoring the progress of the reaction of transesterification of soybean oil with methanol in the presence of KOH as basic catalyst. The pulse/echo technique was used to monitor acoustic velocity throughout the reaction, composed as an in-line scheme. The results were related to the reference method based on gas chromatography (EN 14103 stan-

Ultrasound as a Metrological Tool for Monitoring Transesterification Kinetics

http://dx.doi.org/10.5772/intechopen.70501

199

Let us consider the reaction TAG + 6 MeOH ! 3 FAME + G, where TAG (triglyceride) is soybean oil, MeOH is methanol, FAME is the ester mixture and G is glycerol. To simplify the study, there are some considerations before starting the process of monitoring the transesterification reaction by ultrasound. As there is excess alcohol, we can consider TAG as a limiting reagent, i.e., when it is totally consumed the reaction will finish. With the excess of methanol, the reaction becomes irreversible, which means that the whole equilibrium of the reaction is displaced to produce biodiesel. Another important consideration is to admit a batch reactor in which reagents are mixed at the beginning of the reaction, without any inlet or outlet flow of

Thus, we determine the amount of TAG consumed ðNTAGc Þ, quantified in mol, through Eq. (1), in which NTAG<sup>0</sup> represents the amount of TAG inserted in the reactor at time 0 (in mol), and X is the relationship between the TAG that reacted with the TAG inserted into the reactor at time 0.

The TAG in a given time (NTAGt ) is obtained by the difference of the TAG inserted in the reactor

The disappearance of the TAG must be accompanied by the appearance of the FAME. However, a question arises: how the actual concentration of FAME throughout the reaction can be assessed? Complementary, one could ask how to know that in fact the reaction has ended and it has already reached the maximum conversion? There are several techniques proposed in the literature, but few can make this determination in an in-line scheme with an accurate way

and the TAG consumed, according to Eq. (2) (all values expressed in mol).

Thus, Eqs. (1) and (2) lead to Eq. (3), as depicted elsewhere [6, 9].

From stoichiometry, one can derive to CTAG <sup>¼</sup> NTAG

evolving to Eq. (4).

NTAGc ¼ NTAG<sup>0</sup> � X (1)

NTAGt ¼ NTAG<sup>0</sup> � NTAG<sup>0</sup> � X (2)

NTAGt ¼ NTAG<sup>0</sup> ð Þ 1 � X (3)

CTAG ¼ CTAG<sup>0</sup> ð Þ 1 � X (4)

<sup>V</sup> , and for liquids V = V<sup>0</sup> (volume is constant),

H NMR technique [13–18].

2. Fundamental of the transesterification reaction

reagents further than those mixed at time 0.

dard) and to the <sup>1</sup>

Establishing the kinetics of a chemical reaction can be very complex depending on the chemical route. An in-depth study requires a series of experiments and simulations that can predict when the reaction has reached the optimal state. For reactions in which the converting mechanism is not well established, several kinetic models may be proposed, arising from countless reaction monitoring techniques. Thus, the combination of techniques, well described in the literature and easily accessible, allows a more precise conclusion of the object of study [6, 7].

To illustrate, let us take one of the chemical reactions responsible for biodiesel production, the transesterification reaction, disclosed in Figure 1.

Figure 1 discloses that an oil can react with a small chain alcohol in the presence of a catalyst and produce biodiesel. Biodiesel, also known as fatty acid methyl ester (FAME), is nothing more than a mixture of esters.

The transesterification reaction to produce biodiesel is reversible and, therefore, usually works with excess of alcohol. A typical proportion is 6:1 (alcohol:oil) ratio, so that the equilibrium displacement is forced towards the conversion of biodiesel. However, the oil and alcohol are not miscible, establishing two phases. In this stage, when there are two phases within the mixture, one can say that the mass transfer controls the kinetics of the reaction. Nevertheless, as biodiesel (methyl ester) is formed, it works as a co-solvent, facilitating the miscibility. Upon reaching the homogeneity of the system, the chemical reaction starts to control the system. A reaction in which an exchange of mechanism occurs makes difficult to define the kinetics and, consequently, the establishment of optimal reaction conditions [7–12].

Figure 1. Transesterification of vegetable oil for biodiesel production.

Within this chapter, we will disclose the recent outcomes of a research in which ultrasound has been used as a way of monitoring the progress of the reaction of transesterification of soybean oil with methanol in the presence of KOH as basic catalyst. The pulse/echo technique was used to monitor acoustic velocity throughout the reaction, composed as an in-line scheme. The results were related to the reference method based on gas chromatography (EN 14103 standard) and to the <sup>1</sup> H NMR technique [13–18].

### 2. Fundamental of the transesterification reaction

The competitiveness of companies for which the core business is the production of consumer goods is directly linked to their production process. Quality and productivity, once seen as dissociated elements, now are joined together, strongly impacting business competitiveness, improving process performance, product quality and reducing costs. In this way, the study of the kinetics of chemical processes allows the optimization of the process, avoiding the waste

Establishing the kinetics of a chemical reaction can be very complex depending on the chemical route. An in-depth study requires a series of experiments and simulations that can predict when the reaction has reached the optimal state. For reactions in which the converting mechanism is not well established, several kinetic models may be proposed, arising from countless reaction monitoring techniques. Thus, the combination of techniques, well described in the literature and easily accessible, allows a more precise conclusion of the object of study [6, 7]. To illustrate, let us take one of the chemical reactions responsible for biodiesel production, the

Figure 1 discloses that an oil can react with a small chain alcohol in the presence of a catalyst and produce biodiesel. Biodiesel, also known as fatty acid methyl ester (FAME), is nothing

The transesterification reaction to produce biodiesel is reversible and, therefore, usually works with excess of alcohol. A typical proportion is 6:1 (alcohol:oil) ratio, so that the equilibrium displacement is forced towards the conversion of biodiesel. However, the oil and alcohol are not miscible, establishing two phases. In this stage, when there are two phases within the mixture, one can say that the mass transfer controls the kinetics of the reaction. Nevertheless, as biodiesel (methyl ester) is formed, it works as a co-solvent, facilitating the miscibility. Upon reaching the homogeneity of the system, the chemical reaction starts to control the system. A reaction in which an exchange of mechanism occurs makes difficult to define the kinetics and,

consequently, the establishment of optimal reaction conditions [7–12].

Figure 1. Transesterification of vegetable oil for biodiesel production.

not only of raw materials, but also of energy and time [6].

transesterification reaction, disclosed in Figure 1.

more than a mixture of esters.

198 Advanced Chemical Kinetics

Let us consider the reaction TAG + 6 MeOH ! 3 FAME + G, where TAG (triglyceride) is soybean oil, MeOH is methanol, FAME is the ester mixture and G is glycerol. To simplify the study, there are some considerations before starting the process of monitoring the transesterification reaction by ultrasound. As there is excess alcohol, we can consider TAG as a limiting reagent, i.e., when it is totally consumed the reaction will finish. With the excess of methanol, the reaction becomes irreversible, which means that the whole equilibrium of the reaction is displaced to produce biodiesel. Another important consideration is to admit a batch reactor in which reagents are mixed at the beginning of the reaction, without any inlet or outlet flow of reagents further than those mixed at time 0.

Thus, we determine the amount of TAG consumed ðNTAGc Þ, quantified in mol, through Eq. (1), in which NTAG<sup>0</sup> represents the amount of TAG inserted in the reactor at time 0 (in mol), and X is the relationship between the TAG that reacted with the TAG inserted into the reactor at time 0.

$$N\_{TAG\_c} = N\_{TAG\_0} \cdot X \tag{1}$$

The TAG in a given time (NTAGt ) is obtained by the difference of the TAG inserted in the reactor and the TAG consumed, according to Eq. (2) (all values expressed in mol).

$$N\_{TAG\_0} = N\_{TAG\_0} - N\_{TAG\_0} \cdot X \tag{2}$$

Thus, Eqs. (1) and (2) lead to Eq. (3), as depicted elsewhere [6, 9].

$$N\_{TAG\_l} = N\_{TAG\_0}(1 - X) \tag{3}$$

From stoichiometry, one can derive to CTAG <sup>¼</sup> NTAG <sup>V</sup> , and for liquids V = V<sup>0</sup> (volume is constant), evolving to Eq. (4).

$$\mathbb{C}\_{TAG} = \mathbb{C}\_{TAG\_0}(1 - X) \tag{4}$$

The disappearance of the TAG must be accompanied by the appearance of the FAME. However, a question arises: how the actual concentration of FAME throughout the reaction can be assessed? Complementary, one could ask how to know that in fact the reaction has ended and it has already reached the maximum conversion? There are several techniques proposed in the literature, but few can make this determination in an in-line scheme with an accurate way without demanding exorbitant expenses. To sort out that drawback, ultrasound methods emerge as a tool capable of assisting in the biodiesel manufacturing process.

material, the faster the ultrasonic wave will propagate within it. It is important to keep in mind

Mathematically, the speed of sound is computed dividing the distance travelled by the pulse

<sup>υ</sup> <sup>¼</sup> <sup>2</sup> � <sup>Δ</sup><sup>s</sup>

Here, Δs is the distance separating the ultrasonic surface and the reflecting interface (the travelling distance is twice this value) and t is the time required for the ultrasonic pulse to transpose that distance and return to the transducer. This process can be repeated many times, depending on the attenuation and the distance from the transducer and the reflecting surface. After each subsequent reflection, the pulse amplitude will decrease, as a consequence of attenuation. The multiple reflections will remain until the sound energy is completely

While planning the experimental set-up for the pulse/echo method, one must be aware about the absorption of the liquid under investigation, as well as the distance between the transducer and the reflecting surface. The pulse frequency plays a key role, as ultrasonic attenuation is exponentially proportional to the frequency. In general, water is used as reference once its

behaviour both for attenuation and ultrasonic velocity are very well known [26–29].

<sup>t</sup> (5)

http://dx.doi.org/10.5772/intechopen.70501

201

Ultrasound as a Metrological Tool for Monitoring Transesterification Kinetics

that the ultrasonic velocity changes significantly with temperature [26–29].

absorbed in the process. Figure 2 exhibits that multi-reflection behaviour.

Figure 2. Ultrasonic pulse and reflections.

by the time spent to travel it (time of flight), as disclosed in Eq. (5).

### 3. Ultrasound as a tool for liquid characterization

Ultrasound is a mechanical wave that propagates in fluids or solid materials at frequencies greater than 20 kHz, i.e., out of the audible range for healthy humans [19–25].

An often used ultrasonic measurement method consists on a pulse/echo arrangement. Basically, it consists on

EMISSION ! PROPAGATION ! REFLECTION ! PROPAGATION ! RECEPTION

Two important quantities are easily assessed from the pulse/echo ultrasonic measurement method: time of flight and pulse (or signal) amplitude. Both are measured after the reception of the ultrasound wave. Whenever an acoustic impedance mismatch occurs, the ultrasonic wave is partially reflected in the discontinuity boundary. The amount of reflection depends on the acoustic impedance difference between the two media, due to what is called the reflection coefficient of the interface. In a typical pulse/echo experimental set-up in sonochemistry, the propagation medium is fluid and the reflection takes place in an interface with a solid object, generically denominated reflecting target. Similarly, the liquid-air interface is a reflecting target, as well.

Throughout the propagation, other physical phenomena diminish the ultrasonic amplitude due to different mechanisms. Mainly, scattering and absorption are in charge for ultrasonic attenuation, mitigating the capability of free propagation. All those phenomena are natural and unavoidable. Nevertheless, a proper experimental ultrasonic set-up will either concern on its quantification, or will deal with other quantities that are not undesirably affected.

The speed of sound is a quantity that is not related to attenuation phenomena, or at least is not the case in a linear range of frequencies and in infinite-like three-dimensional propagation medium, even if there is a constraint in one dimension. In the linear range of ultrasonic propagation, the sound velocity in any determined medium or material varies as a function of the temperature, density and viscosity. As a matter of fact, those quantities are not absolutely correlated to each other, what makes the establishment of a mathematical function a virtually unrealisable task for complex mixtures of fluids. For monophasic simple liquids, such as pure water or hydro carbonates, it is easier to define a function relating those quantities, but it is not the case for a transesterification process.

To assess the speed of sound, the typical approach is to measure the time of flight of an ultrasonic pulse within a vessel with a pre-determined distance from the surface to the emitting ultrasonic transducer and a properly designed reflecting target. It is the so-called pulse/ echo experimental method. Materials in different macrophysics states transmit ultrasonic waves with different velocities. In general, but not in a universal way, the more rigid is a material, the faster the ultrasonic wave will propagate within it. It is important to keep in mind that the ultrasonic velocity changes significantly with temperature [26–29].

Mathematically, the speed of sound is computed dividing the distance travelled by the pulse by the time spent to travel it (time of flight), as disclosed in Eq. (5).

$$\upsilon = \frac{2 \cdot \Delta \text{s}}{t} \tag{5}$$

Here, Δs is the distance separating the ultrasonic surface and the reflecting interface (the travelling distance is twice this value) and t is the time required for the ultrasonic pulse to transpose that distance and return to the transducer. This process can be repeated many times, depending on the attenuation and the distance from the transducer and the reflecting surface. After each subsequent reflection, the pulse amplitude will decrease, as a consequence of attenuation. The multiple reflections will remain until the sound energy is completely absorbed in the process. Figure 2 exhibits that multi-reflection behaviour.

While planning the experimental set-up for the pulse/echo method, one must be aware about the absorption of the liquid under investigation, as well as the distance between the transducer and the reflecting surface. The pulse frequency plays a key role, as ultrasonic attenuation is exponentially proportional to the frequency. In general, water is used as reference once its behaviour both for attenuation and ultrasonic velocity are very well known [26–29].

Figure 2. Ultrasonic pulse and reflections.

without demanding exorbitant expenses. To sort out that drawback, ultrasound methods

Ultrasound is a mechanical wave that propagates in fluids or solid materials at frequencies

An often used ultrasonic measurement method consists on a pulse/echo arrangement. Basi-

EMISSION ! PROPAGATION ! REFLECTION ! PROPAGATION ! RECEPTION

Two important quantities are easily assessed from the pulse/echo ultrasonic measurement method: time of flight and pulse (or signal) amplitude. Both are measured after the reception of the ultrasound wave. Whenever an acoustic impedance mismatch occurs, the ultrasonic wave is partially reflected in the discontinuity boundary. The amount of reflection depends on the acoustic impedance difference between the two media, due to what is called the reflection coefficient of the interface. In a typical pulse/echo experimental set-up in sonochemistry, the propagation medium is fluid and the reflection takes place in an interface with a solid object, generically denominated reflecting target. Similarly, the liquid-air interface

Throughout the propagation, other physical phenomena diminish the ultrasonic amplitude due to different mechanisms. Mainly, scattering and absorption are in charge for ultrasonic attenuation, mitigating the capability of free propagation. All those phenomena are natural and unavoidable. Nevertheless, a proper experimental ultrasonic set-up will either concern on

The speed of sound is a quantity that is not related to attenuation phenomena, or at least is not the case in a linear range of frequencies and in infinite-like three-dimensional propagation medium, even if there is a constraint in one dimension. In the linear range of ultrasonic propagation, the sound velocity in any determined medium or material varies as a function of the temperature, density and viscosity. As a matter of fact, those quantities are not absolutely correlated to each other, what makes the establishment of a mathematical function a virtually unrealisable task for complex mixtures of fluids. For monophasic simple liquids, such as pure water or hydro carbonates, it is easier to define a function relating those quantities, but it is not

To assess the speed of sound, the typical approach is to measure the time of flight of an ultrasonic pulse within a vessel with a pre-determined distance from the surface to the emitting ultrasonic transducer and a properly designed reflecting target. It is the so-called pulse/ echo experimental method. Materials in different macrophysics states transmit ultrasonic waves with different velocities. In general, but not in a universal way, the more rigid is a

its quantification, or will deal with other quantities that are not undesirably affected.

emerge as a tool capable of assisting in the biodiesel manufacturing process.

greater than 20 kHz, i.e., out of the audible range for healthy humans [19–25].

3. Ultrasound as a tool for liquid characterization

cally, it consists on

200 Advanced Chemical Kinetics

is a reflecting target, as well.

the case for a transesterification process.

### 4. Validation of the experimental ultrasonic method

In previous studies, the value of the propagation speed in soybean oil in a range of 20–50�C was determined [20]. For the practical application presented within this paper, all reactions were performed at 40�C. At this temperature, soybean oil has a velocity of 1418.3 m s�<sup>1</sup> , with expanded uncertainty (p = 0.95) Uexp = 5.2 m s�<sup>1</sup> [21]. As soon as the oil starts to react with methanol and the catalyst, variation on the speed of sound will indicate that something is happening within the medium. Despite it is easy to measure speed of sound, it is not trivial to relate this variation with anything that is going on in the reaction. The chemical kinetics is not directly assessed, unless some methodological study is conducted. That was the case, insofar we conducted an experimental method validation. The idea was to compare the speed of sound measured throughout the transesterification process with a quantification of the reaction stoichiometric situation at different moments. The worldwide accepted reference method for determination of ester content is based on gas chromatography (GC), according to the standard EN 14103. However, this method, besides being time-consuming, it is not applicable in the process line and demands expensive equipment, supplies, and specific technical training. Thus, less costly methods have emerged as an alternative for determining the conversion, as is the case with <sup>1</sup> H NMR. Despite it is not a cheap technique, it is much less time-consuming than the GC analysis [13, 14, 21, 22, 30–32].

In establishing parameters for the reactions that will be analysed, an isothermal batch reactor (T = 40�C) is chosen. The validation experiment was restricted to two concentrations for the catalyst (0.2% and 1.5% w/w) and two mechanical stirring rotational speeds (200 and 520 rpm). The reaction time was set to a limit of 40 min.

There are several studies that propose equations that take into account the number of hydrogens present in the molecules consumed (TAG) in relation to the number of hydrogens present in the formed molecule (FAME). Figures 3 and 4 disclose the <sup>1</sup> H NMR spectra for the pure soybean oil and the biodiesel made from this oil, respectively.

The formation of methyl ester (methylic biodiesel) can be noticed by the appearance of the signal of the methylic hydrogen from the methoxyl group at 3.7 ppm (chemical shift represented per B in Figure 4), while occurs the disappearance of the methylene hydrogens from glycerol in the triacylglycerol from 4.0 to 4.4 ppm (chemical shift represented per B in Figure 3). Eq. (6) presents a method described in the literature [14] used to determine the conversion of TAG.

$$X\_{TAG}(\%) = 100 \cdot \left(\frac{2A\_1}{3A\_2}\right) \tag{6}$$

Figure 3. <sup>1</sup>

Figure 4. <sup>1</sup>

(H) CH3.

(E) CH2dC]C; (F) CH2dCdC]O; and (G) dCH2d; (H) CH3.

H NMR spectra for pure soybean oil: (A) HC]CH; (B) CH2dO; (C) C]CdCH2dC]C; (D) CH2dC]O;

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H NMR spectra of methyl biodiesel obtained on the homogeneous transesterification of soybean oil: (A)

HC]CH; (B) CH3dO; (C) C]CdCH2dC]C; (D) CH2dC]O; (E) CH2dC]C; (F) CH2dCdC]O; and (G) dCH2d;

Here, XTAG (%) is the amount of TAG that has been converted into biodiesel, A<sup>1</sup> and A<sup>2</sup> are areas of the methylic hydrogens (δ = 3.7 ppm) of methoxyl group, the methyl ester and the glycerol methylene hydrogens (δ = 4–4.4 ppm), respectively. Calculation of the <sup>1</sup> H NMR conversion was compared to the reference method (GC) for the two reactions with 200 rpm (see Figure 5).

4. Validation of the experimental ultrasonic method

as is the case with <sup>1</sup>

202 Advanced Chemical Kinetics

conversion of TAG.

(see Figure 5).

than the GC analysis [13, 14, 21, 22, 30–32].

The reaction time was set to a limit of 40 min.

in the formed molecule (FAME). Figures 3 and 4 disclose the <sup>1</sup>

soybean oil and the biodiesel made from this oil, respectively.

In previous studies, the value of the propagation speed in soybean oil in a range of 20–50�C was determined [20]. For the practical application presented within this paper, all reactions were performed at 40�C. At this temperature, soybean oil has a velocity of 1418.3 m s�<sup>1</sup>

expanded uncertainty (p = 0.95) Uexp = 5.2 m s�<sup>1</sup> [21]. As soon as the oil starts to react with methanol and the catalyst, variation on the speed of sound will indicate that something is happening within the medium. Despite it is easy to measure speed of sound, it is not trivial to relate this variation with anything that is going on in the reaction. The chemical kinetics is not directly assessed, unless some methodological study is conducted. That was the case, insofar we conducted an experimental method validation. The idea was to compare the speed of sound measured throughout the transesterification process with a quantification of the reaction stoichiometric situation at different moments. The worldwide accepted reference method for determination of ester content is based on gas chromatography (GC), according to the standard EN 14103. However, this method, besides being time-consuming, it is not applicable in the process line and demands expensive equipment, supplies, and specific technical training. Thus, less costly methods have emerged as an alternative for determining the conversion,

In establishing parameters for the reactions that will be analysed, an isothermal batch reactor (T = 40�C) is chosen. The validation experiment was restricted to two concentrations for the catalyst (0.2% and 1.5% w/w) and two mechanical stirring rotational speeds (200 and 520 rpm).

There are several studies that propose equations that take into account the number of hydrogens present in the molecules consumed (TAG) in relation to the number of hydrogens present

The formation of methyl ester (methylic biodiesel) can be noticed by the appearance of the signal of the methylic hydrogen from the methoxyl group at 3.7 ppm (chemical shift represented per B in Figure 4), while occurs the disappearance of the methylene hydrogens from glycerol in the triacylglycerol from 4.0 to 4.4 ppm (chemical shift represented per B in Figure 3). Eq. (6) presents a method described in the literature [14] used to determine the

XTAGð Þ¼ % <sup>100</sup> � <sup>2</sup>A<sup>1</sup>

Here, XTAG (%) is the amount of TAG that has been converted into biodiesel, A<sup>1</sup> and A<sup>2</sup> are areas of the methylic hydrogens (δ = 3.7 ppm) of methoxyl group, the methyl ester and the

conversion was compared to the reference method (GC) for the two reactions with 200 rpm

glycerol methylene hydrogens (δ = 4–4.4 ppm), respectively. Calculation of the <sup>1</sup>

3A<sup>2</sup> 

H NMR. Despite it is not a cheap technique, it is much less time-consuming

, with

H NMR spectra for the pure

(6)

H NMR

Figure 3. <sup>1</sup> H NMR spectra for pure soybean oil: (A) HC]CH; (B) CH2dO; (C) C]CdCH2dC]C; (D) CH2dC]O; (E) CH2dC]C; (F) CH2dCdC]O; and (G) dCH2d; (H) CH3.

Figure 4. <sup>1</sup> H NMR spectra of methyl biodiesel obtained on the homogeneous transesterification of soybean oil: (A) HC]CH; (B) CH3dO; (C) C]CdCH2dC]C; (D) CH2dC]O; (E) CH2dC]C; (F) CH2dCdC]O; and (G) dCH2d; (H) CH3.

Figure 5 shows that the <sup>1</sup> H NMR method is very similar to the reference method (GC). After this straightforward validation, comparing both technics, we used <sup>1</sup> H NMR to assess the conversion of analytical curves as described in Eq. (6) for the four reactions (see Figure 6).

As disclosed in Figure 6, one can note that each reaction reaches the maximum conversion at a given moment. But how to know during the reaction that the maximum conversion has already been reached and there is no longer any need to continue the process? NMR analyses, as well as GC, require the sample to be pure, which means free of other substances that may interfere with the analysis. In this way, ultrasonic monitoring stands out, being able to determine the maximum point of the reaction even in the presence of excess reagents and by-products. Figures 7 and 8 depict a set of results for all chemical routes employed in the present study.

Figure 7 shows that each reaction has a propagation velocity configuration. They all start with a value close to the pure soybean oil velocity. However, during the reaction time, the speed of

Figure 5. Variation of biodiesel conversion during the homogeneous transesterification of soybean oil with methanol and 200 rpm of mechanical stirring.

sound decreases until stabilized, demonstrating that the maximum conversion was reached. This variation can be better observed in Figure 8, which is a zoomed part of Figure 7 restricted to the first few minutes. Considering that the idea is to obtain pure biodiesel, independent of the reaction conditions, it is quite natural that the final velocities (when the highest concentra-

Figure 8. First 7.5 min of the variation of the propagation velocity along the transesterification of soybean oil with

Figure 7. Variation of the propagation velocity along the transesterification reaction of soybean oil with methanol in the

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Let us analyse the effect of each parameter (catalyst and rotation) on the final biodiesel

tion of biodiesel is present) are close to each other.

5. Looking into the results in details

conversion.

methanol in the presence of KOH.

presence of KOH.

Figure 6. Conversion rate calculated by <sup>1</sup> H NMR for four transesterification reactions of soybean oil using KOH as the basic catalyst.

Ultrasound as a Metrological Tool for Monitoring Transesterification Kinetics http://dx.doi.org/10.5772/intechopen.70501 205

Figure 7. Variation of the propagation velocity along the transesterification reaction of soybean oil with methanol in the presence of KOH.

Figure 8. First 7.5 min of the variation of the propagation velocity along the transesterification of soybean oil with methanol in the presence of KOH.

sound decreases until stabilized, demonstrating that the maximum conversion was reached. This variation can be better observed in Figure 8, which is a zoomed part of Figure 7 restricted to the first few minutes. Considering that the idea is to obtain pure biodiesel, independent of the reaction conditions, it is quite natural that the final velocities (when the highest concentration of biodiesel is present) are close to each other.

#### 5. Looking into the results in details

Figure 5 shows that the <sup>1</sup>

204 Advanced Chemical Kinetics

200 rpm of mechanical stirring.

Figure 6. Conversion rate calculated by <sup>1</sup>

basic catalyst.

After this straightforward validation, comparing both technics, we used <sup>1</sup>

depict a set of results for all chemical routes employed in the present study.

conversion of analytical curves as described in Eq. (6) for the four reactions (see Figure 6).

As disclosed in Figure 6, one can note that each reaction reaches the maximum conversion at a given moment. But how to know during the reaction that the maximum conversion has already been reached and there is no longer any need to continue the process? NMR analyses, as well as GC, require the sample to be pure, which means free of other substances that may interfere with the analysis. In this way, ultrasonic monitoring stands out, being able to determine the maximum point of the reaction even in the presence of excess reagents and by-products. Figures 7 and 8

Figure 7 shows that each reaction has a propagation velocity configuration. They all start with a value close to the pure soybean oil velocity. However, during the reaction time, the speed of

Figure 5. Variation of biodiesel conversion during the homogeneous transesterification of soybean oil with methanol and

H NMR for four transesterification reactions of soybean oil using KOH as the

H NMR method is very similar to the reference method (GC).

H NMR to assess the

Let us analyse the effect of each parameter (catalyst and rotation) on the final biodiesel conversion.

#### 5.1. Analysis of the effect of catalyst concentration

The presence of catalyst helps to accelerate the reaction, reducing the activation energy required to start it. Thus, catalyst concentration is one of the main factors that can affect the reaction kinetics.

Looking at Table 1 and Figure 9, one can note that there is a large difference in CTAG and υ decay between both reactions, what reflects in the conversion rate (XTAG). The uncertainty bars calculated for the velocity are disclosed to determine the accuracy of the study [33]. The behaviour observed in the reaction with 0.2% KOH and 200 rpm presents a slow decay in the concentration of TAG in the first 10 min of reaction, which is expected for reactions in which mechanism exchange occurs. That region on the graphics of Figure 9 (first 10 minutes of reaction) is in which the rate of consumption and conversion rate are slow, and it occurs due to the low miscibility between alcohol and oil. Thus, as the methyl ester is produced, the chemical reaction starts to control the kinetics of the reaction and, therefore, a large jump between 10 and 20 min of reaction is observed. After 20 min of reaction, it is clearly noticeable that there is stability between the conversion values and propagation velocity. This result indicates that the ultrasound can determine the maximum point of conversion even in the

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On the other hand, when the reaction with 1.5% KOH and 200 rpm is on focus, yet in Figure 9, it is observed an expressive consumption of TAG in the first 10 min of reaction. After that time, the stability in the values of the conversion as well as in the propagation velocity is evident. Reactions like that, in which there is a rapid conversion, the region controlled by mass transfer can be considered insignificant. Here, it is observed that for reactions with 200 rpm stirring, the increase in catalyst concentration not only accelerates the transesterification process but also increases the final conversion as well, and consequently decreases the remaining TAG in the reaction medium. Let us check if the same will occur analysing the results presented in Table 2 and Figure 10, in

For the reaction with 0.2% of KOH and 520 rpm of stirring, it is noticeable that there is a slow decrease in the TAG concentration in the first 10 min and stability of the values after 20 min. On the other hand, the reaction with 1.5% of KOH and 520 rpm reaches the maximum conversion as fast as 5 min after the reaction had begun. In the same way as observed in Figure 9, the mass transfer controls the start of the reaction for the reaction with 0.2% of catalyst, independently of the rotational speed employed. With the increase of KOH concentration by 7.5 times, there is a 300% decrease in reaction time for the reaction with 520 rpm of

] υ [m s<sup>1</sup>

 0 0.83 1426.8 0 0.83 1421.3 0.3 0.81 1342.9 52.8 0.65 1363.2 5.5 0.78 1353.0 85.9 0.12 1358.8 8.7 0.76 1354.0 87.7 0.10 1357.6 78.6 0.22 1357.3 88.7 0.09 1356.3 82.1 0.18 1360.0 89.1 0.09 1356.9

0.2% and 520 rpm 1.5% and 520 rpm

] XTAG [%] CTAG [mol L<sup>1</sup>

] υ [m s<sup>1</sup>

]

presence of secondary substances (by-products).

which the rotation speed was increased to 520 rpm.

Time [min] XTAG [%] CTAG [mol L<sup>1</sup>

Table 2. Results for reactions at 520 rpm.

In order to analyse the effect of the variation of the catalyst concentration, it is necessary to separately analyse different rotation values.

For an initial concentration of soybean oil equal to 0.83 mol L<sup>1</sup> and by the Eqs. (4) and (6), the consumption of TAG and conversion into FAME were calculated. The velocity (υ) was calculated according to Eq. (5).


Table 1 and Figure 9 disclose the results for the reactions with 200 rpm of rotational speed.

Table 1. Results for reactions at 200 rpm.

Figure 9. Variation of (a) TAG concentration, (b) propagation velocity and (c) TAG conversion for the reactions with 200 rpm of rotation.

Looking at Table 1 and Figure 9, one can note that there is a large difference in CTAG and υ decay between both reactions, what reflects in the conversion rate (XTAG). The uncertainty bars calculated for the velocity are disclosed to determine the accuracy of the study [33]. The behaviour observed in the reaction with 0.2% KOH and 200 rpm presents a slow decay in the concentration of TAG in the first 10 min of reaction, which is expected for reactions in which mechanism exchange occurs. That region on the graphics of Figure 9 (first 10 minutes of reaction) is in which the rate of consumption and conversion rate are slow, and it occurs due to the low miscibility between alcohol and oil. Thus, as the methyl ester is produced, the chemical reaction starts to control the kinetics of the reaction and, therefore, a large jump between 10 and 20 min of reaction is observed. After 20 min of reaction, it is clearly noticeable that there is stability between the conversion values and propagation velocity. This result indicates that the ultrasound can determine the maximum point of conversion even in the presence of secondary substances (by-products).

On the other hand, when the reaction with 1.5% KOH and 200 rpm is on focus, yet in Figure 9, it is observed an expressive consumption of TAG in the first 10 min of reaction. After that time, the stability in the values of the conversion as well as in the propagation velocity is evident. Reactions like that, in which there is a rapid conversion, the region controlled by mass transfer can be considered insignificant. Here, it is observed that for reactions with 200 rpm stirring, the increase in catalyst concentration not only accelerates the transesterification process but also increases the final conversion as well, and consequently decreases the remaining TAG in the reaction medium.

Let us check if the same will occur analysing the results presented in Table 2 and Figure 10, in which the rotation speed was increased to 520 rpm.

For the reaction with 0.2% of KOH and 520 rpm of stirring, it is noticeable that there is a slow decrease in the TAG concentration in the first 10 min and stability of the values after 20 min. On the other hand, the reaction with 1.5% of KOH and 520 rpm reaches the maximum conversion as fast as 5 min after the reaction had begun. In the same way as observed in Figure 9, the mass transfer controls the start of the reaction for the reaction with 0.2% of catalyst, independently of the rotational speed employed. With the increase of KOH concentration by 7.5 times, there is a 300% decrease in reaction time for the reaction with 520 rpm of


Table 2. Results for reactions at 520 rpm.

5.1. Analysis of the effect of catalyst concentration

separately analyse different rotation values.

Time [min] XTAG [%] CTAG [mol L<sup>1</sup>

Table 1. Results for reactions at 200 rpm.

200 rpm of rotation.

reaction kinetics.

206 Advanced Chemical Kinetics

lated according to Eq. (5).

The presence of catalyst helps to accelerate the reaction, reducing the activation energy required to start it. Thus, catalyst concentration is one of the main factors that can affect the

In order to analyse the effect of the variation of the catalyst concentration, it is necessary to

For an initial concentration of soybean oil equal to 0.83 mol L<sup>1</sup> and by the Eqs. (4) and (6), the consumption of TAG and conversion into FAME were calculated. The velocity (υ) was calcu-

Table 1 and Figure 9 disclose the results for the reactions with 200 rpm of rotational speed.

0.2% and 200 rpm 1.5% and 200 rpm

] υ [m s<sup>1</sup>

 0 0.83 1428.1 0 0.83 1424.3 0.3 0.83 1385.7 8.3 0.75 1368.7 1.1 0.82 1355.8 71.5 0.24 1358.0 10.0 0.75 1347.9 81.6 0.15 1356.1 48.5 0.43 1353.2 82.5 0.15 1355.4 51.6 0.40 1355.2 83.4 0.14 1353.9

Figure 9. Variation of (a) TAG concentration, (b) propagation velocity and (c) TAG conversion for the reactions with

] XTAG [%] CTAG [mol L<sup>1</sup>

] υ [m s<sup>1</sup>

]

Figure 10. Variation of (a) TAG concentration, (b) propagation velocity and (c) TAG conversion for the reactions with 520 rpm of rotation.

rotation. However, the maximum values reached by the conversion for the two reactions described in Figure 10 are very close (89 and 82%).

system. However, there is a significant increase in the conversion value from 52% (200 rpm) to 82% (520 rpm), which shows that for reactions like those, with low catalyst concentration, the rotation does not interfere in the reaction velocity, but at the maximum conversion value.

Figure 11. Variation of (a) TAG concentration, (b) propagation velocity and (c) TAG conversion for the reactions with

And what happens increasing 7.5 times the concentration of the catalyst? Does this pattern

Increasing the concentration of KOH clearly increases the rate of TAG consumption and, consequently, formation of FAME. While the reaction with 200 rpm reaches the maximum conversion and the equilibrium with 10 min of reaction, the reaction at 520 rpm only requires half the time, 5 min. However, despite the decrease in time, we observed that the values for the

1.5% and 200 rpm 1.5% and 520 rpm

] υ [m s<sup>1</sup>

 0 0.83 1424.3 0 0.83 1421.3 8.3 0.75 1368.7 52.8 0.65 1363.2 71.5 0.24 1358.0 85.9 0.12 1358.8 81.6 0.15 1356.1 87.7 0.10 1357.6 82.5 0.15 1355.4 88.7 0.09 1356.3 83.4 0.14 1353.9 89.1 0.09 1356.9

] XTAG [%] CTAG [mol L<sup>1</sup>

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209

] υ [m s<sup>1</sup>

]

hold? Table 4 and Figure 12 show the answers.

maximum conversion are very close.

Time [min] XTAG [%] CTAG [mol L<sup>1</sup>

Table 4. Results for 1.5% (w/w) of KOH reactions.

0.2% (w/w) of KOH.

#### 5.2. Analysis of the effect of system stirring

If the same concentration of catalyst is used, would the stirring of the system interfere with the kinetics of the reaction? The answer is: Surely enough!

Firstly, the lowest catalyst concentration, 0.2% KOH, will be analysed. The impact due the change in rotational speed will be variable in those reactions. Table 3 and Figure 11 show the results for the reactions with 0.2% catalyst.

From Table 3 and Figure 11, we note that the two reactions with 0.2% of catalyst need the same reaction time to reach their maximum conversion, regardless of the rotation applied to the


Table 3. Results for 0.2% (w/w) of KOH reactions.

Figure 11. Variation of (a) TAG concentration, (b) propagation velocity and (c) TAG conversion for the reactions with 0.2% (w/w) of KOH.

system. However, there is a significant increase in the conversion value from 52% (200 rpm) to 82% (520 rpm), which shows that for reactions like those, with low catalyst concentration, the rotation does not interfere in the reaction velocity, but at the maximum conversion value.

And what happens increasing 7.5 times the concentration of the catalyst? Does this pattern hold? Table 4 and Figure 12 show the answers.

Increasing the concentration of KOH clearly increases the rate of TAG consumption and, consequently, formation of FAME. While the reaction with 200 rpm reaches the maximum conversion and the equilibrium with 10 min of reaction, the reaction at 520 rpm only requires half the time, 5 min. However, despite the decrease in time, we observed that the values for the maximum conversion are very close.


Table 4. Results for 1.5% (w/w) of KOH reactions.

rotation. However, the maximum values reached by the conversion for the two reactions

Figure 10. Variation of (a) TAG concentration, (b) propagation velocity and (c) TAG conversion for the reactions with

If the same concentration of catalyst is used, would the stirring of the system interfere with the

Firstly, the lowest catalyst concentration, 0.2% KOH, will be analysed. The impact due the change in rotational speed will be variable in those reactions. Table 3 and Figure 11 show the

From Table 3 and Figure 11, we note that the two reactions with 0.2% of catalyst need the same reaction time to reach their maximum conversion, regardless of the rotation applied to the

0.2% and 200 rpm 0.2% and 520 rpm

] υ [m s<sup>1</sup>

 0 0.83 1428.1 0 0.83 1426.8 0.3 0.83 1385.7 0.3 0.81 1342.9 1.1 0.82 1355.8 5.5 0.78 1353.0 10.0 0.75 1347.9 8.7 0.76 1354.0 48.5 0.43 1353.2 78.6 0.22 1357.3 51.6 0.40 1355.2 82.1 0.18 1360.0

] XTAG [%] CTAG [mol L<sup>1</sup>

] υ [m s<sup>1</sup>

]

described in Figure 10 are very close (89 and 82%).

kinetics of the reaction? The answer is: Surely enough!

5.2. Analysis of the effect of system stirring

520 rpm of rotation.

208 Advanced Chemical Kinetics

results for the reactions with 0.2% catalyst.

Time [min] XTAG [%] CTAG [mol L<sup>1</sup>

Table 3. Results for 0.2% (w/w) of KOH reactions.

It was possible to observe purely from the ultrasonic velocity measurement that the faster the mechanical stirring acts, the faster is the transesterification kinetics. Moreover, it is possible to identify the elapsed time when the reaction reaches its maximum possible conversion, dictated by the amount of catalyst. For all cases, ultrasonic monitoring has disclosed a causal relation to

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211

Raphaela M. Baêsso, Pâmella A. Oliveira, Gabriel C. Moraes, André V. Alvarenga and

Laboratory of Ultrasound – National Institute of Metrology, Quality and Technology

[1] Greenwood MS, Bamberger JA. Measurement of viscosity and shear wave velocity or slurry for on-line process control. Ultrasonics. 2002;39(9):623-630. DOI: https://doi.org/

[2] Saggin R, Coupland JN. Oil viscosity measurement by ultrasonic reflectance. Journal of the American Oil Chemists' Society. 2001;78(5):509-511. DOI: https://doi.org/10.1007/

[3] Saggin R, Coupland JN. Concentration measurement by acoustic reflectance. Journal of Food Science. 2001;66(5):681-685. DOI: https://doi.org/10.1111/j.1365-621.2001.tb04621.x

[4] Richard R, Li Y, Dubreuil B, Thiebaud-Roux S, Prat L. On-line monitoring of the transesterification reaction between triglycerides and ethanol using near infrared spectroscopy combined with gas chromatography. Bioresource Technology. 2011;102(2):6702-

[5] Dubé MA, Zheng S, McLean DD, Kates M. A comparison of attenuated total reflectance-FTIR spectroscopy and GPC for monitoring biodiesel production. Journal of the American Oil Chemists' Society. 2004;81(6):599-603. DOI: https://doi.org/10.1007/s11746-006-0948-x

[6] Fogler HS. Elementos de Engenharia das Reações Químicas. 4th ed. São Paulo, SP: Editora

[7] Kusdiana D, Saka S. Kinetics of transesterification in rapeseed oil to biodiesel fuel as treated in supercritical methanol. Fuel. 2001;80:693-698. DOI: https://doi.org/10.1016/S0016-2361

6709. DOI: https://doi.org/10.1016/j.biortech.2011.03.111

the gold standard analytical methods.

(Inmetro), Duque de Caxias, RJ, Brazil

10.1016/S0041-624X(02)00372-4

s11746-001-0294-z

LTC; 2009

(00)00140-X

\*Address all correspondence to: rpfelix@inmetro.gov.br

Author details

References

Rodrigo P.B. Costa-Félix\*

Figure 12. Variation of (a) TAG concentration, (b) propagation velocity and (c) TAG conversion for the reactions with 1.5% (w/w) of KOH.

Thus, an economic analysis is necessary to evaluate to what extent an increase of the rotation used, or of the catalyst concentration, to the detriment of the reduction in the reaction time, is economically feasible. But the use of ultrasound as a tool for monitoring chemical reactions has been shown to be efficient [33].

### 6. Final remarks

Ultrasound is widely used for more than a century for diagnosis applications. The state of the technology is vast on applications for non-destructive testing and biomedical equipment. The use of ultrasound in chemistry is more common as a tool to accelerate reactions or enhance the performance of established methods. However, the technology is not so widely developed and spread around regarding the use of ultrasound as a monitoring tool for chemical reactions.

As a tool, ultrasound is remarkably simple to use. Nevertheless, one must be aware that the apparent straightforwardness undercovers a complex physical process that takes place in the generation, propagations, reflection and reception of ultrasound in both the transmit/receive and pulse/echo approaches. Unless an experiment is carefully designed, carried out, and analysed, the outcome of any ultrasonic proposed method could be of no technical usefulness.

In the present chapter, the use of an ultrasound pulse/echo scheme was validated as a monitoring procedure of the transesterification kinetics of soybean oil into biodiesel. The sensibility of the method was good enough to compare different catalyst concentrations (0.2 and 1.5%) and different rotational speed of mechanical stirring (200 and 520 rpm). The comparison was done using as gold standard the gas chromatography and <sup>1</sup> H RMN. The validation leads to quite interesting outcomes.

It was possible to observe purely from the ultrasonic velocity measurement that the faster the mechanical stirring acts, the faster is the transesterification kinetics. Moreover, it is possible to identify the elapsed time when the reaction reaches its maximum possible conversion, dictated by the amount of catalyst. For all cases, ultrasonic monitoring has disclosed a causal relation to the gold standard analytical methods.

### Author details

Raphaela M. Baêsso, Pâmella A. Oliveira, Gabriel C. Moraes, André V. Alvarenga and Rodrigo P.B. Costa-Félix\*

\*Address all correspondence to: rpfelix@inmetro.gov.br

Laboratory of Ultrasound – National Institute of Metrology, Quality and Technology (Inmetro), Duque de Caxias, RJ, Brazil

### References

Thus, an economic analysis is necessary to evaluate to what extent an increase of the rotation used, or of the catalyst concentration, to the detriment of the reduction in the reaction time, is economically feasible. But the use of ultrasound as a tool for monitoring chemical reactions has

Figure 12. Variation of (a) TAG concentration, (b) propagation velocity and (c) TAG conversion for the reactions with

Ultrasound is widely used for more than a century for diagnosis applications. The state of the technology is vast on applications for non-destructive testing and biomedical equipment. The use of ultrasound in chemistry is more common as a tool to accelerate reactions or enhance the performance of established methods. However, the technology is not so widely developed and spread around regarding the use of ultrasound as a monitoring tool for chemical reactions. As a tool, ultrasound is remarkably simple to use. Nevertheless, one must be aware that the apparent straightforwardness undercovers a complex physical process that takes place in the generation, propagations, reflection and reception of ultrasound in both the transmit/receive and pulse/echo approaches. Unless an experiment is carefully designed, carried out, and analysed, the outcome of any ultrasonic proposed method could be of no technical usefulness. In the present chapter, the use of an ultrasound pulse/echo scheme was validated as a monitoring procedure of the transesterification kinetics of soybean oil into biodiesel. The sensibility of the method was good enough to compare different catalyst concentrations (0.2 and 1.5%) and different rotational speed of mechanical stirring (200 and 520 rpm). The comparison was

H RMN. The validation leads to

done using as gold standard the gas chromatography and <sup>1</sup>

been shown to be efficient [33].

6. Final remarks

1.5% (w/w) of KOH.

210 Advanced Chemical Kinetics

quite interesting outcomes.


[8] Galvan D, Orives JR, Coppo RL, Silva ET, Angilelli KG, Borsato D. Determination of the kinetics and thermodynamics parameters of biodiesel oxidation reaction obtained from an optimized mixture of vegetable oil and animal fat. Energy Fuels. 2013;27(11):6866- 6871. DOI: https://doi.org/10.1021/ef401927x

[20] Oliveira PA, Baêsso RM, Morais GC, Alvarenga AV, Costa-Félix RPB. Speed of sound as a function of temperature for ultrasonic propagation in soybean oil. Journal of Physics Conference Series (Online). 2016;733:012040. DOI: http://dx.doi.org/10.1088/1742-6596/

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### *Edited by Muhammad Akhyar Farrukh*

The book on *Advanced Chemical Kinetics* gives insight into different aspects of chemical reactions both at the bulk and nanoscale level and covers topics from basic to high class. This book has been divided into three sections: (i) "Kinetics Modeling and Mechanism," (ii) "Kinetics of Nanomaterials," and (iii) "Kinetics Techniques." The first section consists of six chapters with a variety of topics like activation energy and complexity of chemical reactions; the measurement of reaction routes; mathematical modeling analysis and simulation of enzyme kinetics; mechanisms of homogeneous charge compression ignition combustion for the fuels; photophysical processes and photochemical changes; the mechanism of hydroxyl radical, hydrate electron, and hydrogen atom; and acceptorless alcohol dehydrogenation. The understanding of the kinetics of nanomaterials, to bridge the knowledge gap, is presented in the second section. The third section highlights an overview of experimental techniques used to study the mechanism of reactions.

Advanced Chemical Kinetics

*Edited by Muhammad Akhyar Farrukh*

Advanced Chemical Kinetics

ISBN 978-953-51-4031-3 ISBN 978-953-51-3815-0