Elsevier Computational Modelling Approaches to Energy Storage Materials: Operating Mechanisms, State-of-the-Art Methods, and Applications to the Atomistic ... (Theoretical and Computational Chemistry)

One of the most important goals in sustainable energy management is the design of new energy storage materials capable of increasing battery performance, durability, and at the same time, taking up the global challenge of increasing the energy saving capabilities through sustainable solutions. Atomistic design has experienced a tremendous boost in the last two decades thanks to the implementation and application of quantum mechanics and molecular dynamics-based approaches coupled, very recently, to artificial intelligent/machine learning algorithms. Such methods pave the way for the discovery and design of new materials for energy storage technologies. Computational Modelling Approaches to Energy Storage Materials: Operating Mechanisms, State-of-the-Art Methods, and Applications to the Atomistic Modelling of Batteries and Capacitors demonstrates how theoretical and computational chemistry methods can be applied in describing and predicting the properties of energy storage materials. Part I of the book introduces the reader to this heterogeneous topic, providing a general overview of the different types of batteries and capacitors, highlighting (from both historical and mechanistic points of view) the physical and operating principles of such systems. Part II contains the methodological core of the book, in terms of theoretical and computational methods. Most existing books includes a similar section where the formalisms of different methods are given, such as by explaining the theoretical concepts. Although this approach is certainly valid, this book goes a step further by giving more relevance to the computational side. Part III concerns the application of the methods described in Part II (as standalones or as a combination of those methods) to study mechanisms, processes, properties, and working principles of several energy storage systems, all based on the initial description in Part I. Computational Modelling Approaches to Energy Storage Materials is written primarily for chemists, physicists and materials scientists at graduate, post-doc, and researcher level (with both theory and experimental background), wishing to apply computational methods to model the complexity of energy storage materials. The book will be highly relevant to researchers interested in applying different atomistic methods to the topic of energy materials, as well as specialists across the fields of physics, chemistry, materials science, and related engineering areas who require a better understanding of materials modelling. Provides a novel introduction and overview of the diverse methodologies and applications of computational chemistry that can be used for investigating and modelling materials for energy storage and addressing the state-of-the art technological and scientific challenges involved Gives concise and easy-to-understand explanations for each methodology with physico-mathematical formalisms, followed by a selection of the most relevant types of calculations and an explanation of the computational protocols that should be followed, helping the reader to understand which strategies and steps must be followed for a certain type of calculation Features up to date results concerning the design and application of energy storage compounds and materials, from both chemical and physical perspectives, including comparisons with experiments where appropriate Includes timely, forward-looking chapters on crucial topic areas such as machine learning approaches and hydrogen storage aspects Shows how atomistic design can improve present energy storage materials, as well as help to create those technologies of the future