Heterogeneous Nanocatalysis for Energy and Environmental Sustainability, Volume 1 E-Book

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 761

Veröffentlichungsjahr: 2022

Beschreibung

An essential companion for catalysis researchers and professionals studying economically viable and eco-friendly catalytic strategies for energy conversion In the two-volume Heterogeneous Nanocatalysis for Energy and Environmental Sustainability, a team of distinguished researchers deliver a comprehensive discussion of fundamental concepts in, and practical applications of, heterogeneous nanocatalysis for alternative energy production, biomass conversion, solar energy, green fuels, H2 production, fuel cells, electrochemical energy conversion processes, CO2 conversion, clean water, and environmental protection. The volumes cover the design and catalytic performance of various nanocatalysts, including nanosized metals and metal oxides, supported metal nanoparticles, inverse oxide-metal nanocatalysts, core-shell nanocatalysts, nanoporous zeolites, nanocarbon composites, and metal oxides in confined spaces. Each chapter contains a critical discussion of the opportunities and challenges posed by the use of nanosized catalysts for practical applications. Volume 1 - Energy Applications focuses on the conversion of renewable energy (biomass/solar) into green fuels and chemicals, ammonia synthesis, clean hydrogen production, and electrochemical energy conversion processes using a variety of nanosized catalysts. It also offers: * A thorough introduction to heterogeneous catalysis and nanocatalysis, as well as a discussion of catalytic active sites at nano-scale range * Comprehensive explorations of the methods for control and activation of nanosized catalysts * Practical discussions of C3N4-based nanohybrid catalysts for solar hydrogen production via water splitting * Nanosized catalysts in visible light photocatalysis for sustainable organic synthesis * Applications of MXenes in electrocatalysis Perfect for researchers, postgraduate students, chemists, and engineers interested in heterogeneous catalysis and nanocatalysis, Heterogeneous Nanocatalysis for Energy and Environmental Sustainability will also earn a place in the libraries of professionals working in alternative energy production, biomass conversion, solar energy, green fuels, H2 production, fuel cells, electrochemical energy conversion processes, CO2 conversion, clean water, and environmental protection.

Leseprobe

Heterogeneous Nanocatalysis for Energy and Environmental Sustainability

Volume 1 ‐ Energy Applications

Edited by

Putla Sudarsanam

Department of Chemistry

Indian Institute of Technology Hyderabad

Kandi, Telangana, India

Yusuke Yamauchi

Australian Institute for Bioengineering and Nanotechnology (AIBN)

School of Chemical Engineering

The University of Queensland

Brisbane, Queensland, Australia

Pankaj Bharali

Department of Chemical Sciences

Tezpur University

Nappam, Assam, India

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Library of Congress Cataloging‐in‐Publication DataNames: Sudarsanam, Putla, editor. | Yamauchi, Yusuke, editor. | Bharali, Pankaj, editor.Title: Heterogeneous nanocatalysis for energy and environmental sustainability / Putla Sudarsanam, Yusuke Yamauchi, Pankaj Bharali.Description: First edition. | Chichester, West Sussex, UK ; Hoboken, NJ, USA : Wiley, 2023. | Includes bibliographical references and index. | Contents: volume 1. Energy applications – volume 2. Environmental applications.Identifiers: LCCN 2022032470 (print) | LCCN 2022032471 (ebook) | ISBN 9781119771999 (cloth ; volume 1) | ISBN 9781119772026 (cloth ; volume 2) | ISBN 9781119772002 (adobe pdf ; volume 1) | ISBN 9781119772019 (epub ; volume 1) | ISBN 9781119772033 (adobe pdf ; volume 2) | ISBN 9781119772040 (epub ; volume 2)Subjects: LCSH: Catalysts. | Heterogeneous catalysis. | Nanochemistry–Industrial applications. | Green chemistry. | Electric power production from chemical action. | Biomass energy. | Environmental protection. | Pollution prevention.Classification: LCC TP159.C3 H48 2023 (print) | LCC TP159.C3 (ebook) | DDC 660/.2995–dc23/eng/20220720LC record available at https://lccn.loc.gov/2022032470LC ebook record available at https://lccn.loc.gov/2022032471

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Preface

Heterogeneous Nanocatalysis for Energy and Environmental Sustainability, Volume 1: Energy Applications

Indubitably, fossil fuels (coal, petroleum, and natural gas) are the primary sources of energy for modern society. Concurrently, there are several concerns associated with fossil fuels, including price volatility, long‐term availability, and environmental detrimental effects. Thus, utilizing alternative energy and technology (e.g. biomass/solar, clean hydrogen, fuel cells) has received tremendous attention to meet the increasing energy demand while controlling environmental pollution, thus moving toward a sustainable society.

Heterogeneous catalysis is a key technology for various energy applications, for instance, renewable energy (solar/biomass) valorization, clean hydrogen production, and photo/electro/chemical energy conversion processes. Over the last two decades, a variety of heterogeneous solid catalysts (bare/mixed oxides, supported metals, zeolites, carbons, perovskites, metal‐organic frameworks, MXenes, hybrid materials, etc.) have been developed with desirable active sites and specific functionalities. The particle size of a solid catalyst is a key determining factor in improving the catalytic properties, such as specific surface area, active site density, and active site–reactant interactions. This breakthrough discovery has paved the way for the development of a new type of catalysis, i.e. nanocatalysis that plays a key role in bridging the gap between homogeneous and heterogeneous catalysis. Thus, the key focus of current catalysis research is to develop advanced nanocatalysts with well‐controlled particle sizes (1–100 nm in at least one dimension) and morphologies because they exhibit promising catalytic activities compared with bulk solid catalysts.

This book focuses on the synthesis, characterization, and applications of a variety of nanosized catalysts for the conversion of renewable energy (biomass/solar) into fuels and chemicals, clean hydrogen production, photoelectrochemical energy conversion processes, etc. Chapter 1 elucidates various factors intervening in oxide and oxide‐composite supports of nanocatalysts in energy conversion. Chapters 2 and 3 summarize the role of nanocatalysis for renewable aromatics from biomass and biodiesel production, respectively. Chapter 4 discusses the role of hybrid electrocatalysts for oxygen electrode reactions. The applications of porous graphitic carbon nitride nanostructures and 2D transition metal carbides (MXenes) for photocatalytic hydrogen evolution reaction and electrocatalysis are summarized in Chapters 5 and 6, respectively. Chapter 7 provides the advances and challenges in Pt‐free Pd‐based catalysts for oxygen electro‐reduction in alkaline media. Chapter 8 reports the applications of the morphology‐ and size‐selective Pd‐based electrocatalysts for fuel cell reactions. The significance of Prussian blue analogues and nanostructured graphene oxide‐based catalysts for H2O2 production and Fischer–Tropsch synthesis are highlighted in Chapters 9 and 10, respectively. Chapter 11 addresses the production of light olefin via catalytic oxidative cracking. The magic of heterogeneous nanocatalysis in VLPC for sustainable organic synthesis is discussed in Chapter 12. Hydrogen generation from ammonia borane using various metal nanoparticle‐based catalysts is summarized in Chapter 13.

The book covers various aspects of nanocatalysis and nanosized catalysts, including synthesis, characterization, and their role in achieving energy sustainability. Thus, the book will be of great interest to researchers/students and industrial chemists familiar with the fields of heterogeneous catalysis and nanocatalysis. We hope that catalysis researchers will find this book as a key reference for the fundamental understanding of surface science, rational catalyst design, and the applications of various nanocatalysts for energy applications. We would like to thank the authors for accepting the invitation and submitting the chapters to this book. We also thank the production team at Wiley for their invaluable assistance and support.

Dr. Putla Sudarsanam

Department of ChemistryIndian Institute of Technology HyderabadKandi, Telangana, India

Professor Yusuke Yamauchi

Australian Institute for Bioengineering and Nanotechnology (AIBN)School of Chemical EngineeringThe University of QueenslandBrisbane, Queensland, Australia

Dr. Pankaj Bharali

Department of Chemical SciencesTezpur UniversityNapaam, Assam, India

List of Contributors

Nicolas Alonso‐VanteIC2MP, UMR‐CNRS 7285University of PoitiersPoitiers Cedex, France

Harshitha N. AnchanDepartment of ChemistryNational Institute of Technology Karnataka (NITK)Mangalore, Karnataka, India

Bindu AntilDepartment of ChemistryUniversity of DelhiDelhi, India

Pankaj BharaliDepartment of Chemical SciencesTezpur UniversityNappam, Assam, India

Navya Subray BhatDepartment of ChemistryNational Institute of Technology Karnataka (NITK)Mangalore, Karnataka, India

Biraj Jyoti BorahDepartment of Chemical SciencesTezpur UniversityNappam, Assam, India

Rashmi ChetryDepartment of Chemical SciencesTezpur UniversityNappam, Assam, India

Bhugendra ChutiaDepartment of Chemical SciencesTezpur UniversityNappam, Assam, India

Sasanka DekaDepartment of ChemistryUniversity of DelhiDelhi, India

Saikat DuttaDepartment of ChemistryNational Institute of Technology Karnataka (NITK)Mangalore, Karnataka, India

Luis Alberto Estudillo‐WongIC2MP, UMR‐CNRS 7285University of PoitiersPoitiers Cedex, FranceandDepartamento de Biociencias e IngenieríaCIIEMADInstituto Politécnico NacionalCDMX, Mexico

Xianfeng FanSchool of EngineeringThe University of EdinburghEdinburgh, United Kingdom

Sarah FarrukhSchool of Chemical and Materials EngineeringNational University of Science and TechnologyIslamabad, Pakistan

Ujjal K. GautamDepartment of Chemical SciencesIndian Institute of Science Education and ResearchMohali, PunjabIndia

Chiranjita GoswamiDepartment of Chemical SciencesTezpur UniversityNappam, Assam, India

HarikrishnaSustainable Materials and Catalysis Research LaboratoryDepartment of ChemistryIndian Institute of Technology JodhpurKarwar, Rajasthan, India

Kumar Kashyap HazarikaDepartment of Chemical SciencesTezpur UniversityNappam, Assam, India

Nadeem IqbalCentre for Undergraduate StudiesUniversity of the PunjabLahore, Pakistan

Suresh IyerCSIR‐National Chemical LaboratoryPune, Maharashtra, India

Huda Sharbini KamaluddinDepartment of ChemistryFaculty of ScienceKing Abdulaziz UniversityJeddah, Saudi Arabia

Mala KhanBangladesh Reference Institute for Chemical Measurements (BRiCM)Dhaka, Bangladesh

R. KrishnapriyaSustainable Materials and Catalysis Research LaboratoryDepartment of ChemistryIndian Institute of Technology JodhpurKarwar, Rajasthan, India

Divya KumarSustainable Materials and Catalysis Research LaboratoryDepartment of ChemistryIndian Institute of Technology JodhpurKarwar, Rajasthan, India

Devika LaishramSustainable Materials and Catalysis Research LaboratoryDepartment of ChemistryIndian Institute of Technology JodhpurKarwar, Rajasthan, India

Xiugang LiKey Laboratory of Functional Small Molecules for Ministry of EducationCollege of Chemistry and Chemical EngineeringJiangxi Normal UniversityNanchang, ChinaandCollege of Material and Chemical EngineeringTongren UniversityTongren, China

Zhang‐Hui LuKey Laboratory of Functional Small Molecules for Ministry of EducationCollege of Chemistry and Chemical EngineeringJiangxi Normal UniversityNanchang, China

Sara MusaddiqDepartment of ChemistryThe Women University MultanMultan, Pakistan

Kiran MustafaDepartment of ChemistryThe Women University MultanMultan, Pakistan

Katabathini NarasimharaoDepartment of ChemistryFaculty of ScienceKing Abdulaziz UniversityJeddah, Saudi Arabia

Suranjana PatowaryDepartment of Chemical SciencesTezpur UniversityNappam, Assam, India

Alwar RamaniSchool of Energy, Geoscience, Infrastructure and SocietyHeriot‐Watt UniversityEdinburg, Scotland

Lipipuspa SahooDepartment of Chemical SciencesIndian Institute of Science Education and ResearchMohali, Punjab, India

Bhagirath SainiSustainable Materials and Catalysis Research LaboratoryDepartment of ChemistryIndian Institute of Technology JodhpurKarwar, Rajasthan, India

Swagotom SarkarBangladesh Reference Institute for Chemical Measurements (BRiCM)Dhaka, Bangladesh

Rakesh Kumar SharmaSustainable Materials and Catalysis Research LaboratoryDepartment of ChemistryIndian Institute of Technology JodhpurKarwar, Rajasthan, India

Kiran P. ShejaleSustainable Materials and Catalysis Research LaboratoryDepartment of ChemistryIndian Institute of Technology JodhpurKarwar, Rajasthan, India

Nittan SinghCatalysis and Inorganic Chemistry DivisionCSIR‐National Chemical LaboratoryPune, Maharashtra, IndiaandAcademy of Scientific and Innovative Research (AcSIR)Ghaziabad, Uttar Pradesh, India

Arumugam SudalaiCSIR‐National Chemical LaboratoryPune, Maharashtra, India

Putla SudarsanamDepartment of ChemistryIndian Institute of Technology HyderabadKandi, Telangana, India

Hiroyasu TabeDepartment of Chemistry and BioengineeringGraduate School of EngineeringOsaka Metropolitan UniversityOsaka, JapanandResearch Center for Artificial Photosynthesis (ReCAP)Osaka Metropolitan UniversityOsaka, Japan

Yusuke YamadaDepartment of Chemistry and BioengineeringGraduate School of EngineeringOsaka Metropolitan UniversityOsaka, JapanandResearch Center for Artificial Photosynthesis (ReCAP)Osaka Metropolitan UniversityOsaka, Japan

1Factors Intervening in Oxide and Oxide‐Composite Supports on Nanocatalysts in the Energy Conversion

Luis Alberto Estudillo‐Wong1,2 and Nicolas Alonso‐Vante1

1 IC2MP, UMR‐CNRS 7285, University of Poitiers, Poitiers Cedex, France

2 Departamento de Biociencias e Ingeniería, CIIEMAD, Instituto Politécnico Nacional, CDMX, México

Acronyms

AES

Auger Electron Spectroscopy

AST

Accelerated Stability Test

BET

Bruanuer‐Emmett–Teller

CCR

Carbonyl Chemical Route

DFA

Debye Function Analysis

DFT

Density Functional Theory

DPR

Derivate Peak fitting of diffuse Reflectance

EC ECSA

Electrocatalyst Electrochemical Surface‐active Area

EIS

Electrochemical Impedance Spectroscopy

FC FFT

Fuel Cell Fast Fourier Transform

FWHM

Full‐Width at Half Maximum

HER

Hydrogen Evolution Reaction

HOR

Hydrogen Oxidation Reaction

HR‐TEM

High Resolution ‐ Transmission Electron Microscopy

MA

Mass Surface Area

NPs

Nanoparticles

OBGE

Optical Band‐Gap Energy

OER

Oxygen Evolution Reaction

ORR

Oxygen Reduction Reaction

PDEIS

Potentiodynamic Electrochemical Impedance Spectroscopy

PDM

Photo‐assisted Deposition Method

PDOS

Projected Electronic Density of States

PXRD RDS

Powder X‐ray Diffraction Rate‐Determining Step

RF

Rietveld Refinement

SA

Specific Activity

SEM

Scanning Electron Microscopy

SMCI

Strong Metal–Carbon Interaction

SMSI

Strong Metal–Support Interaction

TIP

Titanium Isopropoxide

TEM

Transmission Electron Microscopy

TOF

Turnover Frequency

W‐H

Williamson–Hall

WMCI

Weak Metal–Carbon Interaction

WMSI

Weak Metal–Support Interaction

WPPF

Whole Powder Pattern Fitting

XAS

X‐ray Absorption Spectroscopy

XPS

X‐ray Photoelectron Spectroscopy

1.1 Overview in Materials Used as Supports in Electrocatalysis

The stability of the catalytic center has always been the biggest challenge in any reaction of technological interest. For example, precious materials, such as platinum (Pt), are used as electrocatalysts (ECs) and widely studied in fuel cell (FC) systems [1]. The nature of its degradation impacts the overall performance of the power generation system [2]. This degradation is due to the strength between the metal and the support, which compromises the stability of the catalytic center and consequently decreases the lifetime of the electrochemical system. The materials used as support and their interaction with the catalytic center play a substantial role in the degradation mechanisms.

Carbon‐based materials are widely used as support due to their high electrical conductivity and surface area [3]. The corrosion of this material occurs at potentials higher than 0.97 V (RHE) [4]. For this purpose, different carbon allotropies have been explored as supports, which are those with low or high graphitization levels, such as amorphous carbon (XC‐72) [5], carbon nanotube [1], and graphene [6]. On the other hand, oxide‐based materials have gained interest due to their stability under operating conditions [7]. However, they present low electrical conductivity and surface area compared to carbon‐based materials [8]. The oxide‐based materials that have been studied as supports are TiO2[9], SnO2[10], CeO2[11], WO3[12], TiO2, or SnO2 doped with Nb [13], Mo [14], Ru [15], Sb [16, 17], or mixed oxides such as CeO2‐TiO2[18]. The oxides can have different shapes, some of which, more typical, are spheres (0D) [19], nanowires, or nanotubes (1D) [20, 21].

For the supports presented in this chapter, we can classify them into two domains, which are (i) carbon‐based and (ii) oxide‐based materials. The combination of these materials has allowed designing hybrid materials (composites), which combine properties of oxide and carbon materials [22–27]. Here, the purpose is to show how the synthesis route used in the synthesis of these materials is based on the synthesis of carbon‐based materials.

We also intend to show how the synthesis route, used for the catalytic center, generates different interactions with the support. For this reason, the physicochemical characterization between the support and the catalytic center plays an important role. The latter aims to determine the structural parameters, which are modified by the hetero‐bonding between the catalytic center and the support. Additionally, the use of density functional theory (DFT) simulation on these catalysts, previously characterized physical‐chemically, allows the prediction and design of new materials applied to a model reaction.

The electrochemical characterization gives us the material fingerprint, and the photoelectrochemical characterization gives the degree of recombination of the electron–hole pairs (e−/h+) of the oxide materials used. Electrochemical parameters such as electrochemically active surface area (ECSA), mass surface area (MA), and specific activity (SA) as a function of structural and optoelectronic properties give clues to the performance applied to a reaction of interest.

Under this context, the case studies confirm how different metal–support interactions allow to modify the catalytic center being a precious metal or its substitution by a non‐precious material.

1.2 Chemical Synthesis of Materials

Synthesis and design of materials are the most crucial part to undertake for different applications, such as medicine [28, 29], electronics [30], energy conversion [31], remediation [32], and pharmaceutical [33]. Here, we review three support and catalytic center synthesis routes, the physicochemical characterization, the support interaction with the catalytic center, and the theoretical approach that has been done so far.

1.2.1 Routes of Synthesis

1.2.1.1 Sol–Gel

This technique focuses on the hydrolysis of different precursors and their conversion into an inorganic solid induced by inorganic polymerization in water to the synthesis of oxide supports. The sol–gel process generally follows four or five steps [34], namely: (i) dissolution of the chemical precursor in an organic solvent, (ii) conversion of the mixture solution into a sol by adding water/acid–base solution, (iii) aging/shaping, and (iv) thermal treatment.

A sol–gel reaction starts with hydrolysis and continues with a condensation of the precursors. According to the precursor, the sol–gel method can be classified into (i) inorganic salt and (ii) metal–organic compound [34]. Different metal oxide materials can be synthesized via the sol–gel method, such as TiO2[35], SnO2[36], and ZnO [37]. Also, the sol–gel route's main advantage is modifying steps or combining methods to tailor novel materials [38–40]. In this latter case, a composite is a combination of properties from two (or more) individual materials incorporated into one material. For example, electrical conductivity is the most critical issue on catalysts support for electrochemical applications. Therefore, the oxide‐carbon composite commits to increase its electrical conductivity and avoid carbon corrosion [23, 26, 41]. As a result, the central oxide can also be doped by a second element in the composite material [42, 43]. Figure 1.1 shows a modified sol–gel method for the preparation of M:TiO2‐C composites.

Figure 1.1 is a setup where a modified sol–gel route to synthesize oxide‐carbon composites is shown. In the beginning, the MClx precursor is mixed with isopropanol solvent in an ice bath. Thereafter, the titanium isopropoxide (TIP) is added and mixed for 16 hours. The steps followed are (i) increase of temperature to 80 °C under nitrogen atmosphere, (ii) addition of XC‐72 carbon support, and (iii) addition of 2 ml of a solution of 0.7 M H2SO4.

The synthesis conditions are continued, and after 12 hours, the solvent is evaporated at 98 °C. The as‐prepared material is thereafter heat treated at 400 °C in an air atmosphere. Lastly, the support is washed with deionized water and dried at 60 °C for 12 hours [42]. This synthesis chemical route leads to a change in the optoelectronic properties of the oxide.

1.2.1.2 Carbonyl Chemical Route

This method has been applied to prepare a wide range of electrocatalytic materials, namely, noble [25, 26, 44], non‐noble metals [45], alloys [46–48], and semiconductors [49]. The Pt cluster complex was initiated by Longoni et al. [50], and the reduction of several Pt precursors and various reducing agents to produce various dianions was subsequently reported using catalytic materials supports [51]. Figure 1.2 shows this route to obtain carbon supported Pt or Pt‐nanoalloys materials. Here, three essential aspects can be identified [51]: (i) the ideal carbonyl complex formation, (ii) the optimal temperature, and (iii) the support material.

Figure 1.1 Modified sol–gel route for the synthesis of M:TiO2/C composites.

Figure 1.2 (a) Flowchart of Pt‐based material low‐temperature synthesis under CO atmosphere. M refers to Cu, Ni, or Cr elements. (b) Simple setup scheme.

Concerning the first aspect, the carbonyl chemical route starts with the reaction (1.1), i.e. the preparation of Pt carbonyl cluster complexes in methanol solvent, step 2, Figure 1.2[50].

(1.1)

The easiest carbonyl complex consists of n = 5, step 2; when the solution turned green. This property depends on the molar ratio between CH3COONa + 3H2O and Na2PtCl6 + 6 H2O. In our group, this molar ratio was fixed to 6 [48, 50].

For Pt‐alloys, reaction (1.1) is modified by the addition of the metallic salt, MClm, Eq. (1.2) [48, 51].

(1.2)

The molar ratio, Pt: M (M = Cu, Ni, Cr), is linked to x and y[48]. Therefore, the carbonyl complex is converted to PtxMy(CO)z, Eq. (1.3)[51].

(1.3)

In the second aspect, the optimal temperature corresponds to the formation or decomposition of the carbonyl complex. For, the optimal synthesis of Pt‐based carbonyl complex temperature lies between 50 and 55 °C, Figure 1.2.

This carbonyl complex can decompose at room temperature in a nitrogen atmosphere, to generate supported nanoparticles (NPs), step 4, Figure 1.2. For non‐metals or semiconductors, the optimal temperature is the solvent's boiling point (T = 140 °C or 180 °C) [52]. The carbonyl complex and another precursor, e.g. selenium, can react to yield chalcogenide nanoalloys in a nitrogen atmosphere.

Carbon black is the standard material used for support because of its electrical conductivity and high surface area [46, 53, 54]. The catalytic center's dispersion and stability are also a design criterion [2, 42]. Thus, the carbonyl chemical route has the importance of providing a good dispersion on the carbon XC‐72 support, step 3, Figure 1.2. The metal–support interaction is discussed in Section 1.2.3. Finally, the synthesis of the as‐prepared carbon‐supported Pt‐alloys NPs are heat treated at 400 °C in H2‐N2 atmosphere, for 2 hours.

1.2.1.3 Photo‐assisted Deposition Method

In 1965, Clark et al. [55] reported a black end product (i.e. metallic silver) due to a photoreaction between TiO2 and Ag+ ions. Whereas Kraeutler and Bard [56] revealed the synthesis of platinized TiO2 material in 1978. Consequently, the PDM took a crucial role to prepare supported metal catalysts. In general, a large‐gap semiconductor under ultraviolet (UV) illumination reduces the metal cations due to photogenerated electron–hole pairs. Therefore, different metals have been synthesized, such as Rh, Pt [9], Pd‐alloys [57], Au [58], Ag [59], Ru [60], and Co‐based [61] to be used in photocatalysis [62, 63].

For the energy conversion and design of novel materials, the PDM is considered as an economical method. For the sake of comparison, this synthesis method favors the metal–support interaction [27]. Figure 1.3 shows the process of preparing Pt‐based materials and supported onto oxide‐carbon composite materials.

From Figure 1.3, two critical aspects can be identified in this type of synthesis, such as (i) the support material and (ii) the nature of the hole scavenger.

On the semiconducting material used as support, the first reaction consists of electron–hole (e−/h+) pairs generation under UV illumination, Eq. (1.4) step 2, Figure 1.3[64].

(1.4)

The photogenerated electrons, transferred from the conduction band, reduce the metal ion precursor at the support's surface, reactions (1.5)–(1.6).

(1.5)

(1.6)

Semiconductors (e.g. TiO2) and carbon materials (C‐sp2 domains) have been proposed as supports. In this connection, oxide‐carbon composite materials have been considered due to the increase of conductivity [65]. The investigated composite materials are TiO2/C [22, 26, 43], SnO2/C [23, 41], and M:TiO2/C [42]. It is important to note that the photoreduction of [PtCl6]2− can, in addition, be activated by photolysis, in the absence of semiconducting material. Indeed, in the bulk solution, the hole scavenger and the [PtCl6]2− precursor can produce [PtCl6]3−, in the presence of UV illumination, Eq. (1.7).

Figure 1.3 (a) Flowchart showing the Pt‐based material synthesis via the photo‐assisted deposition method. (b) Diagram of the experimental setup.

(1.7)

In turn, [PtCl6]3− in equilibrium can produce [PtCl5]2−, Eq. (1.8).

(1.8)

Whereas [PtCl5]2− in the presence of RCH2O* transforms to [PtCl4]2−, Eq. (1.9).

(1.9)

The disproportionation reaction takes place to form [PtCl6]2−, Eq. (1.10), and the cycle of photoreduction proceeds via Eq. (1.9).

(1.10)

This mechanism has been proposed by Einaga et al. [66, 67], and the formation of Pt metal particles takes place only after more than 90% of [PtCl4]2− ions (i.e. Pt2+ ions) is formed, Eq. (1.6)[66].

Different alcohols have been used as hole scavenger for the PDMs, as shown in Figure 1.3[68]. These small organic compounds, serving as hole scavengers, inhibit the semiconductor's recombination process, Eq. (1.4), thus, favoring the electrons to be transferred to [PtCl4]2− ions at the conduction band, Eq. (1.6). The obtained product is further heat treated at 400 °C in H2‐N2 atmosphere, for 2 hours [22].

1.2.2 Physical–chemical characterization of supports

Different techniques and methods of analysis of materials have been employed to generate the so‐called metal–support interaction. Here, we can consider a classification shown in Figure 1.4 [31, 69].

Figure 1.4 considers the compositional, structural, and optical or magnetic characterization as a first step. The principal evaluation in the physicochemical characterization is the surface and/or morphology analyses. This stage involves the analysis of the technique and the method as a second step. In general, transmission electron microscopy (TEM) and powder X‐ray diffraction (PXRD) data are used to obtain the microstructural properties of the material. For further calculation details, the following references are suggested [31, 70, 71].

1.2.2.1 Transmission Electron Microscopy Analysis

The electron microscope aids in analyzing the morphology and the microstructural properties of the material in the nano‐sized domain. Since the advent of electron microscopes in the 1930s [70], various improvements in the analysis have been made in this domain. So, high‐resolution transmission electron microscopy (HRTEM) is used to determine the planes and the electron diffraction pattern [72]. Here, the fast Fourier transform (FFT) of the image indexes the planes according to the X‐ray diffraction (XRD) analysis [73]. For example, Figure 1.5 shows the anatase phase from the TiO2 sample with three directions.

Figure 1.4 Physicochemical classification overview for the characterization of materials.

Figure 1.5 TEM image of a TiO2 sample. (a) (101) and (b) (004) plane reconstructed from FFT from square region, and (c) profile on the (101) plane, see double sided arrow, in (a).

Source: From [74] / with permission of Elsevier.

According to Figure 1.5, it is possible to identify the TiO2 (101) plane with an interplanar distance of 3.5460 ± 0.0091 Å (measured from Figure 1.5c. This is slightly in contrast to 3.52 Å, from the Joint Committee on Powder Diffraction Standards (JCPDS) database [74]. Besides, HRTEM images can elucidate the morphology and the phases present. Figure 1.6 shows the morphology of Pt NPs supported on Y‐doped TiO2 support. As shown in the figure, Pt and anatase phases are both identified in the sample. The dispersion of Pt suits the heterogeneous dispersion of the oxide. This observation assesses the fact that the photo‐deposited Pt is selective on the oxide sites of the support. The HRTEM analysis shows that the particles' size is within the interval from 7 to 19 nm, for Pt in agreement with XRD data analysis [43]. Thus, HRTEM and XRD analyses are complementary techniques to characterize materials. However, a robust interpretation can be delivered by an XRD refinement to complement HRTEM analysis. In some cases, however, it is also possible to simulate HRTEM images using a computer program [75–77].

1.2.2.2 X‐ray Powder Diffraction Analysis

The diffraction pattern can be analyzed and indexed in three different ways [78], which are: (i) the reported patterns used to compare with the experimental profile; (ii) a diffraction standard of a sample, given in JCPDS or crystallographic open database (COD) [79], used to index the peaks; and (iii) a calculated and background spectrum used to extract the microstructural properties (whole powder pattern fitting, WPPF). The conditions (i) and (ii) can help to implement the integral range method (Williamson–Hall [W‐H]) [80]. For the condition (iii), Rietveld‐like [80] and Debye Function Analysis (DFA) method [81] are used with a robust refinement analysis. The W‐H, Rietveld Refinement (RF), and DFA methods are described next.

Figure 1.6 HRTEM images and particle size histograms deduced from TEM images for Pt/C (a‐c), Pt/TiO2‐C (d‐f), and Pt/Y: TiO2‐C (g‐i). Insets in b, e, and h are the fast Fourier transform (FFT) on high‐resolution images.

Source: From [43] / with permission of Elsevier.

1.2.2.3 Williamson–Hall Method

The W‐H method is the first approach to obtain microstructural properties in XRD analysis, which considers the line broadening and is applied as an integral amplitude method. First, this analysis finds that the peak width is a function of 2θ. Each Bragg diffraction peak is deconvoluted to extract the size induced and strain‐induced effects. Eq. (1.11) defines the line broadening parameter (db).

(1.11)

(1.12)

(1.13)

where λ is the wavelength, K is a constant that depends on the shape [82], <d> is the crystallite size, ε is the micro‐strain in the Bragg diffraction angle at the hkl‐plane (θhkl). The full‐width at half maximum (FWHM) βf, hkl is to correct the instrumental broadening, Eq. (1.14).

(1.14)

is the experimental broadening for each Bragg diffraction peak, whose value is obtained to be used as a peak function [43]. Besides, is measured with a standard sample, and used with a Caglioti pseudo‐Voigt (PV) function [83]. The θhkl, the lattice constant (a), and parameters are obtained with the weighted sum of squared residuals (WSSR) [84], Eq. (1.15)[43].

(1.15)

Then, the microstructural properties are applied in Eq. (1.11), and the obtained graph is named the W‐H plot.

1.2.2.4 Rietveld Refinement Method

This method has been widely applied as a standard analysis method to obtain microstructural properties from PXRD data. This refinement requires the modeling of the entire dispersion spectrum, i.e. WPPF. This weighted sum of squares (χ2) is the first quantity to minimize with the Levenberg–Marquardt algorithm, Eq. (1.16).

(1.16)

Where the parameter wi is defined in Eq. (1.17).

(1.17)

The theoretical intensity is evaluated with Eqs. (1.18) and (1.19).

(1.18)

(1.19)

Here, SF, fj, Vj, Lk, Fk, j, S(2θi − 2θk, j) parameters are the beam intensity, the phase volume fraction, the phase cell volume, the Lorentz‐polarization factor, the structure factor, and the profile shape function, at the k‐peak, and bkgi is the background function, respectively. Hence, each phase's mass weight fraction can be calculated with the phase volume fraction according to Eqs. (1.20) and (1.21).

(1.20)

(1.21)

Here, ρj, nA, j, Aj, and NA parameters are: (i) the theoretical phase density, (ii) the number of atoms associated with the unit cell, (iii) the atomic weight for each phase, and (iv) the Avogadro number.

Finally, the R‐indices, calculated with Eqs. (1.22)–(1.24), are used to obtain a good refinement.

(1.22)

(1.23)

(1.24)

Therefore, n and P are the numbers of points and parameters, respectively. Some free computer software [80], such as Maud [85], Profex [86], and FullProf [87] programs, perform the RF method.

1.2.2.5 Debye Function Analysis Method

Debye first proposed his Debye Function in 1915 [88, 89], implemented as DFA. The DFA method has been employed by different groups. For example, Vogel et al. applied the DFA method on surface oxidation–reduction of small Pt clusters in 1989 [90]. In the same year, Hall et al. reported DFA results in experimental electron diffraction patterns of unsupported silver NPs [91]. However, Vogel provided hints on how to apply the DFA method on noble metal groups in 1998 [92]. Hence, the Debye Function is shown in Eq. (1.25).

(1.25)

I0 is the incident beam intensity for i and j atoms, fi(q), fj(q), and rij are the scattering factors, and the distance between i and j. Therefore, Eq. (1.26) defines the length of the dispersion factor.

(1.26)

Where θ and λ are the Bragg diffraction angle and the wavelength. The DFA simulation spectrum is done by Debye scattering equation (DSE), Eq. (1.27).

(1.27)

The cluster size distribution n up to a size Sχ is Dχ(n), xχ is the fraction number of each phase (χ), whose total sum is equal to 1. The mass fraction distribution is calculated from Eq. (1.28).

(1.28)

Here, Eq. (1.29) defines Mχ, and Nχ(n) represents the number of atoms in the cluster.

(1.29)

The Rwp and GofF are calculated from Eqs. (1.30) and (1.31).

(1.30)

(1.31)

The chi‐square (χ2) has the same definition in Eq. (1.16). In addition, since there are not many computer programs that apply the DFA or DSE method, the Debussy software is the only program, developed by Cervellino et al. [89, 93, 94], that allows it.

1.2.2.6 Microstructural Properties from X‐ray diffraction Analysis

The main microstructural properties are the lattice constant, a; the crystallite size, < d >; the micro‐strain, ε; and stacking fault, α. RF and DFA analysis can help obtain all these parameters. As an example, Figure 1.7 shows the RF and DFA analysis performed on the TiO2 sample. The anatase phase (PDF#84–1286) is the main phase that was only present in the powder material.

Figure 1.7 (a) RF and (b) DFA method applied on TiO2 sample. The spheric morphology was considered in both refinement methods.

From this figure, we can observe that WPPF fits the experimental diffraction pattern in both methods. For the analysis with RF, the S(2θi − 2θk, j) parameter considers the profile shape function at the k‐peak, where 2θk, j depends on the Bravais' lattice (crystal systems). For example, Eq. (1.32) represents a tetragonal system (e.g. the anatase phase) with the provided crystallographic information file (CIF), as a first approximation.

(1.32)

Here, λ and a and c parameters are the wavelength and lattice parameters. Besides, the S(2θi) function describes the peak broadening, which is related to the finite size of crystallites, <d>, and the micro‐strain, ε. The broadening of the peak associates these two components to extract FWHM, using Lorentzian (L) and Gaussian (G) functions. The crystallite size and micro‐strain are obtained with FWHM implemented in Eq. (1.33) and (1.34), like that of the W‐H method, Eq. (1.11).

(1.33)

(1.34)

With the help of the CIF file, the Debussy software builds the population for the morphology with different crystallite sizes for the DFA analysis and implements six lattice expansion cases for each morphology [94]. Hence, Eq. (1.34) considers a spheric morphology, see Eq. (1.11), and the same spherical morphology is performed in the DFA analysis. Table 1.1 summarizes the microstructural properties for the TiO2 sample (cf. Figure 1.7).

One can conclude that similar results from both RF and DFA analysis can be obtained. Moreover, the DFA analysis is the most versatile method, where different morphologies can be explored.