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- Herausgeber: Wiley-VCH
- Kategorie: Fachliteratur
- Sprache: Englisch
A singular resource for researchers seeking to apply artificial intelligence and robotics to materials science
In AI and Robotic Technology in Materials and Chemistry Research, distinguished researcher Dr. Xi Zhu delivers an incisive and practical guide to the use of artificial intelligence and robotics in materials science and chemistry. Dr. Zhu explains the principles of AI from the perspective of a scientific researcher, including the challenges of applying the technology to chemical and biomaterials design. He offers concise interviews and surveys of highly regarded industry professionals and highlights the interdisciplinary and broad applicability of widely available AI tools like ChatGPT.
The book covers computational methods and approaches from algorithms, models, and experimental data systems, and includes case studies that showcase the real-world applications of artificial intelligence and lab automation in a variety of scientific research settings from around the world.
You’ll also find:
- A thorough introduction to the challenges currently being faced by chemists and materials science researchers
- Comprehensive explorations of autonomous laboratories powered by artificial intelligence and robotics
- Practical discussions of a blockchain-powered anti-counterfeiting experimental data system in an autonomous laboratory
- In-depth treatments of large language models as applied to autonomous materials research
Perfect for materials scientists, analytical chemists, and robotics engineers, AI and Robotic Technology in Materials and Chemistry Research will also benefit analytical and pharmaceutical chemists, computer analysts, and other professionals and researchers with an interest in artificial intelligence and robotics.
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Seitenzahl: 356
Veröffentlichungsjahr: 2024
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Table of Contents
Cover
Table of Contents
Title Page
Copyright
Preface
About the Author
Acknowledgments
1 Survey of Challenges in Chemistry and Materials Science Research
1.1 Introduction
1.2 Energy Form
1.3 Data
References
2 Robots Technology Development in Modern Scientific Research
2.1 Introduction
2.2 Early Development of Laboratory Automation (Before 2000)
2.3 Preliminary Integration and Development of Laboratory Automation (2000–2019)
2.4 Latest Developments and Current Trends (2020–2023)
2.5 Outlook on Future Development
2.6 Conclusion
References
3 AI Algorithm for Chemical and Bio-material Design
3.1 Introduction
3.2 Molecular Representation and Encoding
3.3 The Formulation of Accessible and Searchable Data
3.4 AI for Molecular Structure–Property Relationship
3.5 AI for Chemical and Bio-material Design
References
4 Autonomous Laboratory Empowered by AI and Robotics
4.1 Evolution of Laboratory
4.2 Core Technologies in Autonomous Laboratories
4.3 Example Autonomous Laboratory Solution
4.4 Advanced Autonomous Laboratory Solutions
4.5 Future Prospects and Trends
References
5 Large Language Models for the Autonomous Material Research
5.1 Review of Large Language Models Development and Applications
5.2 Fundamentals of LLM for Material Research: Database and Knowledge Base Construction
5.3 Evaluation: Spider Matrix
5.4 Ideation: AI Supervisor and ScholarNet
5.5 Results and Discussion
5.6 Conclusion
References
Note
6 Toward a Blockchain-Powered Anti-Counterfeiting Experimental Data System in an Autonomous Laboratory
6.1 Blockchain Technology
6.2 Laboratory Chemical Management and Safety
6.3 The Problem of Data Integrity and Counterfeiting in Scientific Research
6.4 Blockchain in the Autonomous Laboratory
6.5 Symbolic Representation of Experiments
6.6 Challenges and Limitations
6.7 Conclusion
References
7 The Future Integrated Computational and Experimental Research in Metaverse
7.1 Introduction of Metaverse
7.2 Research Paradigm in Metaverse
7.3 Autonomous High-Throughput Experiments
7.4 H
2
O Phase Research in Metaverse
7.5 Aqueous System Research in Metaverse
7.6 Challenges and Future Directions
References
Index
End User License Agreement
List of Tables
Chapter 2
Table 2.1 Timeline of early automation technologies in chemical synthesis.
Table 2.2 Comparison of automation technologies in laboratory systems.
Table 2.3 Comprehensive comparison of AI and robotics integration in laborat...
Table 2.4 Summary of advanced automation systems.
Table 2.5 Timeline of smart laboratories evolution and future prospects.
Chapter 3
Table 3.1 Comparison of linear notations.
Table 3.2 Overview of datasets for molecular structure–property relationship...
Chapter 5
Table 5.1 The accuracy in reference paper prediction from 2016 to 2023.
Table 5.2 Predicts most popular research hotspot from 2016 to 2023, based on...
List of Illustrations
Chapter 1
Figure 1.1 The revolutionary invention of the steam engine marked a monument...
Figure 1.2 The advent of electricity ushered in an era of unprecedented inno...
Figure 1.3 (a) Renewable energy: embracing a diverse array of sources like w...
Figure 1.4 The chemistry lab in (a) 1960s (SinaEducation 2010) and (b) 2024....
Figure 1.5 (a) The number of graduate students in China has grown since 2004...
Figure 1.6 There have been ∼2 million papers published in materials science ...
Chapter 2
Figure 2.1 Advanced temperature control in chemical reactions using a coolin...
Figure 2.2 Overview of the automated chemical reactor system (Legrand and Bo...
Figure 2.3 Evolution of automated chemical synthesis systems (Okamoto and De...
Figure 2.4 Chemspeed’s automated batch and flow chemistry solution 1998 (Che...
Figure 2.5 Symyx tools benchtop system for coating analysis (NDSUResearchPar...
Figure 2.6 R-Series modular flow chemistry system (Vapourtec).
Figure 2.7 Symyx core module robot for the Synthesis of Metal–Organic Framew...
Figure 2.8 Emerald Cloud Lab (ECL) (EmeraldCloudLab).
Figure 2.9 Unchained labs’ Big Kahuna system (UnchainedLabs).
Figure 2.10 Microreactor technology and flow chemistry for green synthesis (...
Figure 2.11 Automated-flow solid-phase peptide synthesizer modules (Mijalis ...
Figure 2.12 IBM RXN for chemistry (IBM).
Figure 2.13 Advanced automated synthesis platform for complex organic molecu...
Figure 2.14 Advanced robotics in photocatalyst research (Burger et al. 2020)...
Figure 2.15 Integrating automation with scaling in nanomaterials research (L...
Figure 2.16 AlphaFlow: a self-driven fluidic lab for autonomous discovery (V...
Figure 2.17 Advanced automated laboratory equipment series by Kapok (Fine-Fa...
Figure 2.18 Timeline of smart laboratories evolution (Zhu 2023).
Chapter 3
Figure 3.1 General scheme of AI-assistant chemical and bio-material design. ...
Figure 3.2 The (a) SMILES, (b) SMARTS, and (c) InChI representations of acet...
Figure 3.3 Example graph representation for ethanol. The node feature matrix...
Figure 3.4 Example of geometry-enhanced molecular representation (GEM) (Fang...
Figure 3.5 General Scheme for the Kohn–Sham equation calculation.
Figure 3.6 Comparison of CNN (Gu et al. 2018) and GCN (Kipf and Welling 2016...
Figure 3.7 Illustrations of the SchNet (Schütt et al. 2018) architecture (le...
Figure 3.8 The overview of using AI to bypass the Kohn–Sham equation, which ...
Figure 3.9 Workflow of the AI molecular structure design scheme. Here the me...
Figure 3.10 Examples of AI-discovered chemical and bio-materials. Rivulariap...
Chapter 4
Figure 4.1 Annual publication volume in AI-related chemistry from 2000 to 20...
Figure 4.2 Illustration of the workflow of Phoenics. (a) Unknown, possibly h...
Figure 4.3 Overall approach for machine-assisted synthesis planning and proc...
Figure 4.4 Material optimization workflow integrated with ChemOS and experim...
Figure 4.5 Structure of SpecSNN: the SNN-based experiment optimizer. (a) The...
Figure 4.6 The measured spectrum undergoes processing to identify peaks, and...
Figure 4.7 Visualization of step-by-step component identification by TN.
Figure 4.8 The molecular structure predictor encompasses two components: (a)...
Figure 4.9 Symbolic representation of experiment schemes. In this representa...
Figure 4.10 The base element for the symbol experiment visualization.
Figure 4.11 More examples of symbol experiment visualization, which shows th...
Figure 4.12 The user interface demo for the user to monitor the device throu...
Chapter 5
Figure 5.1 Capabilities of LLM.
Figure 5.2 Overview of the datasets and tasks of LLMs predictive modeling. I...
Figure 5.3 The authors’ method employs a Language-Interfaced Fine-Tuning (LI...
Figure 5.4 The operational process of the MAPI-LLM system. This system emplo...
Figure 5.5 The process for deriving features and computing similarities amon...
Figure 5.6 Database Schema for Academic Article Storage and Analysis. This d...
Figure 5.7 Overview of Spider Matrix, a two-stage system for identifying and...
Figure 5.8 The creation of a detailed feature matrix to evaluate the similar...
Figure 5.9 The process of honing a Language Model (LLM) for the specialized ...
Figure 5.10 The process from article assessment to the generation of innovat...
Figure 5.11 The novelty rating methods and results. (a) The material science...
Figure 5.12 AI Supervisor’s prediction routine using a partial pre-2015 data...
Figure 5.13 A comprehensive visualization of knowledge progression via Schol...
Chapter 6
Figure 6.1 The oldest blockchain, which serves the purpose to prove the auth...
Figure 6.2 The Byzantine Generals Problem. All generals must receive correct...
Figure 6.3 In PoW consensus mechanisms, miners are required to solve a crypt...
Figure 6.4 Material scientists have adopted blockchain in molecular dynamics...
Figure 6.5 A bumper year for retractions.
Figure 6.6 The BiaeP system. The system comprises Ethereum, a cloud storage ...
Figure 6.7 The working methodology of BiaeP. (a) Storage of demo files on AW...
Figure 6.8 The symbolic BIP instruction, denoted by an abbreviation in the t...
Figure 6.9 The basis of the CubeRoot. (a) Introduction of the parameters in ...
Figure 6.10 An example for the CubeRoot for a template experiment. The exper...
Chapter 7
Figure 7.1 Comparison of the research paradigm between the conventional para...
Figure 7.2 Detail framework unifying human-in-loop optimization and experime...
Figure 7.3 (a) Comparisons of current calculation paradigm and the VR-based ...
Figure 7.4 Network architecture of the physics-endorsed diffusion-like model...
Figure 7.5 General diagram of HIL optimization in water force field. An indi...
Figure 7.6 Ice phase diagram for TIP4P-Meta compared with original TIP3P, TI...
Figure 7.7 Implementation of physics-endorsed model and human-in-loop force ...
Figure 7.8 Solvation prediction of CuSO
4
in the metaverse lab. (a) The diagr...
Figure 7.9 Property calculation of general aqueous solution. (a) Scaling sch...
Guide
Cover
Table of Contents
Title Page
Copyright
Preface
About the Author
Acknowledgments
Begin Reading
Index
End User License Agreement
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AI and Robotic Technology in Materials and Chemistry Research
Xi Zhu
Author
Prof. Xi ZhuSchool of Science and EngineeringThe Chinese University of Hong KongShenzhenChina
Cover: © Andriy Onufriyenko/Getty Images
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Prinrt ISBN: 978-3-527-35428-3ePDF ISBN: 978-3-527-84882-9ePub ISBN: 978-3-527-84881-2oBook ISBN: 978-3-527-84883-6
Preface
This book is a systematic summary of my observations of the industry and my own scientific research since I began studying chemical experiment automation at the Chinese University of Hong Kong – Shenzhen in 2017. The research process for many disciplines, including chemistry and materials science, generally consists of two parts: idea generation and idea execution. In traditional chemical and materials research, the three components of theory, computation, and experimentation each have their own unique characteristics, and researchers in each of these areas often have different philosophical views and their own specialized languages for communication. When I was studying for my doctorate in materials computation in Singapore, I would often discuss the theoretical images behind experimental data with my experimental collaborators, and there would often be situations where I thought more experiments should be done, but the other party thought it would be too difficult.
Therefore, since 2010, I have believed that the use of robotics technology in chemical and materials synthesis is a pressing need, especially for those engaged in theoretical and computational chemistry research, as they often need to understand the physical images behind a spectrum from more and denser experimental data, which is beyond the capabilities of human experimental researchers. It was not until July 2016, when I met Professor Yangsheng Xu, the president of the Chinese University of Hong Kong – Shenzhen and a renowned expert in robotics, in the lobby of the Swissotel The Stamford in Singapore, that I expressed my desire to study chemical experiment robots at The Chinese University of Hong Kong (Shenzhen). President Xu quickly expressed his support, and even though I did not have any relevant research experience at the time, I was given the valuable opportunity to conduct independent research in this field in Shenzhen.
Subsequently, I designed the architectures for various intelligent chemical experiment robots, including AIR-Chem (Authentic Intelligent Robotics for Chemistry), MAOS (Materials Acceleration Operation System) and MAOSIC (MAOS in Cloud), BiaeP (Blockchain Integrated Automatic Experiment Platform), and AIM (Authentic Intelligent Machine). The logic behind these is first solve the automation of experimental operations (AIR-Chem), then we need an Internet of Things system to control more robots (MAOSIC), and at the same time, we hope that our experimental data can be anti-counterfeit under the new architecture, so we can introduce blockchain technology (BiaeP), and finally, when we have a sufficient amount of real and effective experimental data, we may be able to challenge some past theories through the Scaling Law approach (AIM).
In fact, our machines cannot execute the ideas of just one or a few people. At the end of 2022, the technology of large language models, represented by ChatGPT, provided an imaginative space for idea generation. Therefore, I have made all of my experimental data, meeting reports, and other textual materials from the past few years, as well as all of my machines, into a large database that can be connected to any large model system, including ChatGPT. In a sense, this is a system that can achieve autonomous research. I am constantly exploring this matter. After the closed loop of idea generation and idea execution is realized, the technology of the digital metaverse may become one of the platforms for the presentation of materials chemistry, which may seem a bit vague and elusive at present, but if we can know the weather conditions around us a few hours in advance, can we also predict chemical reactions? The last few chapters of this book will also provide a detailed introduction to this project.
I often ponder what my contribution to this field is, and I am slowly beginning to understand the answer to this question: I have expanded a simple scalar chemical equation, composed of a few symbols, into a tensor chemical equation that includes the reactants, reaction conditions, reaction vessels, the concentration and performance of the products, and full data visualization of the reaction process. I am working on the architecture of chemical digitization. The chapters in this book are a testament to the progress I have made in this endeavor.
22 September 2024
Xi Zhu
The Chinese University of Hong KongShenzhen
About the Author
Professor Xi Zhu graduated from the University of Science and Technology of China and Nanyang Technological University in Singapore. He is now an associate professor at The Chinese University of Hong Kong, Shenzhen, and has served as the Deputy Director of the Universal Artificial Intelligence Application Research Center at the Shenzhen Institute of Artificial Intelligence and Robotics for Society.
Professor Xi Zhu’s research field is the development of AI robotic systems in the experimental science domain that are capable of proposing scientific hypotheses and executing experimental operations. He leads a team that has developed AI-Supervisor, a knowledge analysis and recommendation system in the field of material chemistry, and MAOSIC, a cloud-based material chemistry laboratory utilizing intelligent robots and cloud computing technology. His research focuses on developing a digital system for material science that is led by theoretical frameworks.
Acknowledgments
I am immeasurably thankful for the unwavering support and encouragement of Professor Yi Xie at the University of Science and Technology of China. Since 2005, her guidance in the field of chemical science has been invaluable. My heartfelt gratitude also extends to Professor David Tong and Professor Zhigang Zou at CUHK-Shenzhen. Their continuous backing of my research projects and the wealth of ideas they have shared with me have significantly contributed to my work.
Moreover, I express my deepest appreciation to President Yangsheng Xu at CUHK-Shenzhen. The opportunity to conduct research at this prestigious institution, under his leadership, has been a great privilege. His inspiring ideas in the fields of artificial intelligence and robotics have been a source of motivation for me.
1Survey of Challenges in Chemistry and Materials Science Research
1.1 Introduction
Chemistry and materials science constitute a profoundly complex and ancient discipline that has faced entirely distinct challenges across different eras. Without delving into the distant past, let us consider the scenario 20 years ago when the author was engaged in undergraduate research within a chemistry laboratory at the University of Science and Technology of China. A formidable challenge at that time was the complete unpredictability of experimental outcomes, which sometimes left the researchers in the dark about the nature of their work. The standard procedure involved mixing prepared solids and liquids in a hydrothermal autoclave, followed by heating in an oven at 180 °C for approximately 24 hours. Subsequently, the mixture was extracted, separated, washed, and prepared for analysis. This involved observations under various electron microscopes to examine the morphology, along with routine completion of other tests, such as X-ray diffraction (XRD) and spectroscopy. Occasionally, tests for lithium-ion battery performance were also conducted. Perhaps one of the most gratifying experiences at that time was observing the artistic beauty of transmission electron microscopy (TEM) images.
Today, we have grown accustomed to the ubiquity of artificial intelligence, big data, and robotics in our daily lives. Looking back at academic papers from the field of chemistry and materials science twenty years ago, especially those concerning nanomaterials, they appear as collections of data interspersed among images, text, tables, and references. During that era, the publication of, or contribution to, an academic paper was often a source of great joy for many. This retrospective underscores not only the dramatic evolution of technology and methodology within the field but also highlights the fundamental nature of scientific inquiry, which remains constant: a quest for understanding and innovation. The transition from manual experimentation and analysis to the integration of advanced computational tools and methodologies has significantly enhanced the capacity for prediction, analysis, and application in materials science. Yet, the essence of discovery, characterized by moments of joy and frustration, the painstaking gathering of data, and the meticulous interpretation of results, continues to define the discipline. This evolution reflects a broader narrative of progress in science and technology, where the accumulation of knowledge and the development of new tools mutually reinforce each other, driving the boundaries of what is possible ever forward.
1.2 Energy Form
When we discuss “new energy” today, it is invariably linked to another term, “new materials,” and vice versa. The relationship between materials chemistry and energy is one of mutual promotion and complementarity. The generation, storage, transport, and utilization of energy are all reliant on specific functional materials, while more advanced energy systems have enhanced the precision of our observations of the world, significantly propelling the technological progress of materials science. Concurrently, the continuous accumulation of human scientific and technological knowledge further promotes the emergence and application of new technologies. As described by the “materials big data” projects in recent years, combined with the current “generative” artificial intelligence technologies, we seem to have discovered a new domain for more efficient exploration and discovery from existing data toward incremental innovation. Of course, this is predicated on having sufficient computational power, which is itself a part of energy, underscoring the growing importance of technology in the new energy sector. Thus, we observe that today’s materials science can be viewed as the process where theory or algorithms drive data through energy to achieve incremental innovation, which represents our primary competitive direction. This improved and expanded version positions the interdependence of new energy and new materials within a broader scientific and technological context, emphasizing the role of computational power and artificial intelligence. It sets the stage for a detailed historical analysis, hinting at the evolution of these fields and their impact on contemporary scientific research and technological development. I will proceed to analyze this process from a historical perspective.
1.2.1 Steam Power
In analyzingthe trajectory of materials chemistry within the broader context of societal development and energy paradigms, it becomes evident that the evolution of this field is deeply intertwined with the predominant energy sources of its respective eras. The progression from a society reliant primarily on human and animal labor to one powered by steam, and eventually to our current age of electricity and emerging renewable energies, has had profound implications for the advancement of materials chemistry.
During the pre-industrial era, characterized by manual labor, the field of materials chemistry was in its nascent stages. The absence of sophisticated instrumentation and analytical techniques meant that researchers’ understanding of chemical phenomena was limited to observable reactions and processes that could be achieved without the aid of advanced technology. This period’s knowledge base was foundational yet primitive by today’s standards, focusing on the basic properties of materials and their simple transformations.
Figure 1.1 The revolutionary invention of the steam engine marked a monumental leap from manual labor to mechanized production, symbolizing a pivotal moment in human history. The Steam Age stands as a crucial milestone in human history, catalyzing industrialization and modernization, reshaping production methods, social structures, and lifestyles, exerting profound and enduring influence on the world.
The Industrial Revolution marked a pivotal shift, with the invention and widespread adoption of the steam engine catalyzing an unprecedented expansion in industrial capabilities and scientific inquiry. The steam engine, a marvel of engineering and materials science, necessitated the development of materials that could withstand high pressures and temperatures. This requirement spurred significant advancements in metallurgy, exemplified by the Bessemer process, which revolutionized steel production by making it more efficient and cost-effective. The ability to produce stronger, more durable materials was not just a technological achievement but also a cornerstone in the edifice of modern industrial society, enabling the construction of railroads, bridges, and machinery that powered the nineteenth century’s economic expansion (Figure 1.1).
Furthermore, the steam era’s influence extended into the realm of chemical production and analysis. The coal industry, a key driver of the steam engine, became a vital source of raw materials for the burgeoning chemical industry. Coal tar, a byproduct of coal gasification, was the precursor for an array of chemical dyes, initiating a new era in the textile industry and laying the groundwork for synthetic organic chemistry. The development of analytical chemistry was equally crucial, with innovations such as spectroscopy and chemical thermodynamics emerging in response to the industrial and scientific challenges of the time.
The establishment of dedicated research institutions and the systematic approach to materials chemistry research were also hallmarks of this era. The professionalization of chemistry as a distinct scientific discipline, coupled with the enhanced collaboration between scientists and engineers, led to a more methodical and empirical approach to research. This collaborative ethos was instrumental in bridging the gap between theoretical chemistry and its practical applications, fostering a culture of innovation that would pave the way for the next century’s scientific breakthroughs. The steam power era’s legacy is its role in promoting the global spread of chemical knowledge. The advent of steam-powered printing presses made scientific literature more accessible, while improved transportation facilitated the exchange of ideas and materials between researchers across the globe. This era laid the foundational principles of materials chemistry as we understand it today, setting the stage for the subsequent development of polymers, composites, and nanomaterials that are essential to modern technology.
As steam technology advanced, scientists gained a deeper understanding of thermodynamics, marking a period of significant progress in the field. This era was also characterized by burgeoning theoretical research in reaction kinetics, reflecting an increasing sophistication in the comprehension of the forces and principles governing chemical reactions. Concurrently, the chemical engineering industry experienced sustained growth, driven by these scientific advancements and the demand for industrial applications of chemical processes. In parallel, the field of reaction kinetics emerged, focusing on the rates at which chemical reactions occur and the factors influencing these rates. This area of study is vital for understanding how reactions can be optimized for industrial processes, including those used in the chemical engineering industry. Theories related to reaction kinetics, such as the Arrhenius equation (Arrhenius 1889), which describes how reaction rates increase with temperature, became instrumental in the design and improvement of chemical reactors and processes.
The expansion of the chemical engineering industry during this time can be attributed to the integration of these scientific insights into practical applications. Chemical engineers leveraged the principles of thermodynamics and reaction kinetics to develop processes that are more efficient, cost-effective, and capable of producing materials and chemicals at a larger scale. This not only facilitated the growth of the chemical industry itself but also had a wide-reaching impact on sectors such as pharmaceuticals, energy, and materials science, contributing to the advancement of society as a whole. Thus, the advancement of steam technology and the deepening understanding of thermodynamics and reaction kinetics played pivotal roles in the scientific and industrial growth of the 19th and early 20th centuries, marking a period of remarkable innovation and expansion in the chemical engineering field.
1.2.2 Electricity Power
The transition from steam to electric power marked a revolutionary period in human history, heralding the second industrial revolution. This era, spanning the late 19th and early 20th centuries, was not just about the adoption of electricity as a primary energy source but also about the profound impact it had on materials chemistry. The electrification of society demanded new materials with specific properties, fostering a wave of innovation in chemistry and material science.
An understanding confined solely to gases is significantly inadequate for the field of materials chemistry, which also heavily involves the study of condensed phases such as solids and liquids. These phases arguably represent a more prevalent subject of research. In the domain of solid-state physics, electrons emerge as one of the pivotal research subjects. The study of electrons is indissolubly linked to the understanding of electricity and the socio-economic context of the era. By the late nineteenth century, the exploration and application of electricity had made considerable strides, with the advent of technologies like the light bulb, telephone, and electrical power distribution witnessing a qualitative leap and achieving widespread practical application. Many scientists of that period began to leverage electricity as a tool for scientific investigation. For instance, in 1895, Röntgen (1896) discovered X-rays while experimenting with a Crookes tube – an early experimental electrical discharge tube – during his studies on cathode rays. This discovery underscored the pivotal role of electrical technology in facilitating scientific breakthroughs.
The unveiling of X-rays opened the door to observing the microscopic structure of materials, further broadening the horizons of material chemistry through the advent of quantum mechanics. Quantum mechanics has introduced concepts such as momentum space into contemporary solid-state physics, significantly expanding our cognitive and exploratory scope in materials chemistry. This progression underscores the interdisciplinary nature of materials science, highlighting how advances in one area can propel understanding and innovation across multiple scientific domains. It exemplifies the profound impact of electrical studies and technological advancements on the evolution of materials chemistry, enabling the detailed examination of material properties at the atomic and molecular levels. Consequently, these insights have paved the way for the development of new materials and technologies, underscoring the integral role of a comprehensive understanding of all states of matter – solid, liquid, and gas – in the advancement of materials science and engineering (Figure 1.2).
Figure 1.2 The advent of electricity ushered in an era of unprecedented innovation and connectivity, fundamentally transforming human civilization and laying the groundwork for the modern technological landscape. The Electrical Era represents a paradigm shift in human history, sparking revolutions in communication, transportation, and industry, fostering global interconnectedness, and fostering the birth of countless inventions that continue to shape our daily lives.
With the maturation of solid-state physics (Ashcroft and Mermin 1976) and the conceptual framework of momentum space, the intricate relationship between structure and properties has been catapulted to the forefront of tangible research inquiries, particularly in the realms of electrical conductivity and band gap analysis. Solid-state physics, as a discipline, seeks to elucidate the physical properties of solids from a microscopic perspective, leveraging quantum mechanics as a fundamental theoretical underpinning. This approach has profoundly enriched our understanding of how the atomic and electronic structures of materials influence their macroscopic properties.
The concept of band theory, a cornerstone of solid-state physics, offers a comprehensive explanation for the electrical conductivity of materials. Band theory posits that the energy levels of electrons in a solid form bands of energy rather than discrete levels. The presence of band gaps, or energy ranges in which no electron states can exist, plays a crucial role in determining a material’s conductivity. For instance, insulators are characterized by a wide band gap, preventing electrons from easily moving across the energy barrier, whereas conductors exhibit little to no band gap, facilitating free electron movement and, consequently, electrical conductivity. Semiconductors, pivotal in modern electronics, possess a narrow band gap that allows their conductive properties to be finely tuned through doping or environmental changes.
Moreover, the advent of quantum mechanics has enabled the prediction and manipulation of material properties with unprecedented precision. Quantum mechanics (Griffiths and Schroeter 2018) introduces the principle of wave-particle duality, which asserts that particles such as electrons exhibit both particle-like and wave-like properties. This principle is instrumental in understanding the quantum mechanical behavior of electrons in solids, which directly influences material properties such as electrical conductivity, magnetism, and optical absorption.
The exploration of momentum space, a quantum mechanical construct where positions and momenta are conjugate variables, has further deepened our comprehension of solid-state phenomena. The analysis of electronic states within momentum space facilitates a more nuanced understanding of band structures and electron dynamics, contributing to advancements in material design and application. These scientific advancements underscore the crucial role of solid-state physics in the modern technological landscape. The ability to engineer materials with tailored electrical, optical, and magnetic properties has been a driving force behind the development of advanced technologies, ranging from semiconductor devices and solar cells to quantum computing. The ongoing research into the structure–property relationship not only enriches our theoretical knowledge but also paves the way for the innovation of new materials and technologies that address the complex challenges of the twenty-first century.
During the steam era, the focus was largely on macroscopic physical properties and the statistical behaviors of gases and vapors. This period was marked by the development of thermodynamics, which provided a framework for understanding energy conversion and efficiency in steam engines and other heat-driven systems. The limitations of steam power, however, were evident in its reliance on bulky machinery, the inefficiency of heat engines, and the localized nature of power generation and distribution. The advent of the electrical age represented a quantum leap forward, not just in terms of energy production and utilization, but also in the granularity and precision of scientific research. Electricity offered an unprecedented level of control and versatility, enabling the study of individual atoms and molecules and the electronic properties of materials. This shift was pivotal for the field of materials chemistry, where the focus expanded from the collective behavior of particles in gases to the intricate details of solid materials, including their atomic and electronic structures.
Moreover, the electrical age has brought about significant advancements in energy sustainability and efficiency. Unlike the steam age, which was heavily dependent on coal and other fossil fuels, electrical power can be generated from a variety of sources, including renewable energy such as solar, wind, and hydroelectric power. This diversification of energy sources is crucial for addressing the environmental challenges of the twenty-first century, highlighting the role of electrical power not only in advancing scientific knowledge and technological capabilities but also in promoting sustainable development.
It’s essential to emphasize that in the electrical age, the demands of the industrial sector have significantly propelled advancements in materials chemistry. This symbiotic relationship between industrial needs and scientific innovation has led to remarkable progress in materials development, directly influencing the efficiency, sustainability, and capabilities of modern technologies. The industrial demands for better performance, reduced costs, and enhanced sustainability have been key drivers in the evolution of materials chemistry. Industries reliant on electrical technologies, such as electronics, automotive, aerospace, and energy, have continuously pushed the boundaries of what’s possible with current materials, urging scientists to innovate and develop new materials with superior properties.
In the electronics industry, for instance, the relentless pursuit of miniaturization and higher performance has driven the development of advanced semiconductor materials beyond silicon, including gallium arsenide (GaAs) and graphene. These materials offer superior electrical conductivity and electron mobility, enabling faster and more energy-efficient electronic devices. The quest for more efficient photovoltaic cells has similarly spurred research into novel materials that can convert sunlight into electricity more efficiently, such as perovskite solar cells, which offer a promising alternative to traditional silicon-based cells with the potential for higher efficiency and lower manufacturing costs.
The automotive and aerospace industries have also been instrumental in advancing materials chemistry, particularly in the development of lightweight and high-strength materials. The shift toward electric vehicles (EVs) and the need for longer battery life have intensified research into advanced battery technologies, including lithium-ion batteries with improved energy density and charging speeds. Materials such as carbon fiber composites and aluminum alloys have become crucial for reducing vehicle weight, enhancing fuel efficiency, and improving performance.
Moreover, the energy sector’s shift toward renewable sources has catalyzed the development of materials that can efficiently capture, store, and convert energy. Innovations in materials chemistry have led to more efficient wind turbines, safer nuclear reactors, and more durable hydroelectric power facilities. The advancement of energy storage technologies, including supercapacitors and next-generation batteries, is critical for addressing the intermittency of renewable energy sources and ensuring a stable and sustainable energy supply.
This industrial push for innovation has not only led to the development of new materials but has also necessitated advancements in materials characterization and manufacturing techniques. Techniques such as atomic layer deposition, 3D printing of functional materials, and advanced microscopy and spectroscopy methods have evolved to meet the intricate demands of materials synthesis and analysis, enabling the precise engineering of materials at the atomic and molecular levels.
1.2.3 Other Energy Forms
Following the unprecedented technological progress made through the first two industrial revolutions, the field of materials chemistry has seen significant advancements. Subsequently, there emerged a variety of new energy forms, including nuclear power, lithium-ion batteries, hydrogen energy, and even renewable sources such as hydroelectric and wind power. Cleanliness and environmental sustainability have become the new benchmarks for future energy sources. However, from the perspective of researchers in the field of materials chemistry, the ultimate forms of new energy, regardless of the specific application scenarios, remain thermal and electrical energy. Although fundamentally, new energy sources have not revolutionized the basic modalities of materials science research from a theoretical or experimental standpoint, the development of new energy and its related industries has propelled significant growth in the discipline of materials chemistry, enabling a synergistic empowerment with other societal sectors.
The advent of these new energy sources has introduced complex challenges and opportunities for materials chemistry. The development and optimization of materials for nuclear reactors, for example, require an intricate understanding of radiation resistance, thermal conductivity, and mechanical strength. Similarly, the proliferation of lithium-ion batteries has spurred extensive research into electrode materials, electrolytes, and separators to improve energy density, charge rates, and safety profiles (Figure 1.3).
The development of both renewable and nuclear energy has significantly advanced the field of materials chemistry by creating a demand for new materials with unique properties. These materials are tailored to efficiently harness solar, wind, geothermal, and other renewable sources, as well as to withstand the demanding conditions of nuclear reactors. This dual drive toward sustainable and powerful energy solutions has led to a surge in research and innovation within materials chemistry, focusing on improving energy conversion, storage, and transmission.
Renewable energy development has promoted materials chemistry through the quest for more efficient and cost-effective solar panels, leading to research into novel photovoltaic materials like thin-film technologies, organic, and perovskite solar cells. In wind energy, advancements have been crucial in developing stronger, more durable materials for turbine blades to increase efficiency and lifespan. The integration of renewable sources into the power grid has also necessitated advancements in energy storage technologies, with materials chemistry playing a pivotal role in developing advanced electrolytes and electrode materials.
Figure 1.3 (a) Renewable energy: embracing a diverse array of sources like wind, hydro, and solar, renewable energy stands at the forefront of the global shift toward sustainable practices. It offers a promising avenue for reducing greenhouse gas emissions and minimizing our ecological footprint. As a key player in combating climate change, renewable energy not only contributes to a cleaner environment but also supports economic stability by creating jobs and reducing dependency on fossil fuels, encapsulating the dynamic progress and potential of sustainable development. (b) Nuclear power: with its immense potential and controversial implications, nuclear energy represents a double-edged sword, offering vast amounts of carbon-free power while posing significant challenges in terms of safety, waste management, and proliferation concerns, highlighting the complexities of navigating our energy future.
Photovoltaic Materials for Solar Energy
. The quest for more efficient and cost-effective solar panels has spurred research into novel photovoltaic materials. Beyond traditional silicon-based solar cells, materials chemists have been exploring thin-film technologies, organic and perovskite solar cells, aiming to increase efficiency, reduce costs, and offer flexible, lightweight options for solar energy generation. This research directly responds to the renewable energy sector’s demands for more versatile and efficient solar technologies.
Materials for Wind Energy
. Advancements in materials chemistry have been crucial for the wind energy sector, particularly in developing stronger, more durable materials for wind turbine blades. Research into composites and polymers aims to create blades that are not only lighter and stronger but also capable of withstanding harsh environmental conditions, thereby increasing efficiency and lifespan of wind turbines.
Electrolytes and Electrodes for Energy Storage
. The integration of renewable energy sources into the power grid has necessitated advancements in energy storage technologies, such as batteries and supercapacitors. Materials chemistry plays a pivotal role in developing advanced electrolytes and electrode materials that offer higher energy densities, faster charging times, and longer life cycles. Innovations in lithium-ion batteries, solid-state batteries, and beyond are directly driven by the needs of the renewable energy sector.
Materials for Hydrogen Production and Fuel Cells
. The shift toward hydrogen as a clean energy carrier has promoted research in materials chemistry for efficient hydrogen production, storage, and utilization in fuel cells. Developing catalysts for water electrolysis, materials for hydrogen storage, and proton-exchange membranes for fuel cells are critical areas where materials chemistry contributes directly to advancing hydrogen as a renewable energy source.
Thermoelectric and Piezoelectric Materials
. Renewable energy development has also accelerated research into thermoelectric and piezoelectric materials, which convert waste heat and mechanical energy into electricity, respectively. These materials offer potential for energy harvesting in a variety of settings, contributing to the efficiency and sustainability of energy systems.
Similarly, the development of nuclear power has necessitated the creation and improvement of materials capable of handling the extreme conditions of nuclear reactors, such as high temperatures and radiation. This need for specialized materials has spurred substantial research and innovation in materials chemistry, focusing on enhancing the safety, efficiency, and longevity of nuclear energy systems.
Radiation-Resistant Materials
. The operation of nuclear reactors involves exposure to intense radiation, which can degrade many materials over time. This challenge led to the development of radiation-resistant materials, including specific alloys and ceramics that can maintain structural integrity and functionality in high-radiation environments. Research in understanding how materials interact with radiation has been a direct outcome of the nuclear power industry’s requirements.
High-Temperature Materials
. Nuclear reactors operate at high temperatures, necessitating materials that can withstand these conditions while maintaining strength and corrosion resistance. This requirement has driven advancements in high-temperature materials science, including the development of superalloys and advanced ceramics that can perform under the extreme thermal conditions found in reactors.
Fuel Cladding Materials
. The development of materials for fuel cladding, which encases the nuclear fuel to prevent the release of radioactive particles, is another area where nuclear power has propelled materials chemistry. Innovations in zirconium alloys, for example, have been critical in creating effective fuel cladding that minimizes corrosion and allows for efficient heat transfer.
Coolant and Moderator Materials
. The search for efficient coolant and moderator materials, which play crucial roles in the operation of nuclear reactors by managing reactor temperatures and neutron flux, respectively, has led to significant research in materials chemistry. This includes the development of liquid metals, gases, and graphite with specific properties tailored to nuclear applications.
Waste Management and Containment
