Theoretical and Computational Chemistry – serie

Properties and Functionalization of Graphene: Computational Chemistry Approaches, Volume 21 shows how computational chemistry can be used to explore molecular interactions when modeling and manipulating graphene's properties for varied applications. Sections compare results and experimental evidence, cover the experimental techniques employed in the functionalization of graphene and associated challenges, and delve into the properties of functionalized graphene. Under the guidance of its expert editor, this book shares insights from a global team of specialists, making it an authoritative, practical guide for all those studying, developing or applying graphene across a whole range of fields.

Provides practical insights into the latest computational approaches used in modeling the properties of functionalized graphene Includes detailed methods and step-by-step guidance on key processes that are supported throughout with examples Highlights the electronic properties of functionalized graphene

Molecular Modeling of the Sensitivities of Energetic Materials, Volume 22 introduces experimental aspects, explores the relationships between sensitivity, molecular structure and crystal structure, discusses insights from numerical simulations, and highlights applications of these approaches to the design of new materials. Providing practical guidelines for implementing predictive models and their application to the search for new compounds, this book is an authoritative guide to an exciting field of research that warrants a computer-aided approach for the investigation and design of safe and powerful explosives or propellants.

Much recent effort has been put into modeling sensitivities, with most work focusing on impact sensitivity and leading to a lot of experimental data in this area. Models must therefore be developed to allow evaluation of significant properties from the structure of constitutive molecules.

Highlights a range of approaches for computational simulation and the importance of combining them to accurately understand or estimate different parameters Provides an overview of experimental findings and knowledge in a quick and accessible format Presents guidelines to implement sensitivity models using open-source python-related software, thus supporting easy implementation of flexible models and allowing fast assessment of hypotheses

The Crystalline States of Organic Compounds is a broad survey of the techniques by which molecular crystals are investigated, modeled, and applied, starting with the fundamentals of intra- and intermolecular bonding supplemented by a concise tutorial on present-day diffraction methods, then proceeding to an examination of crystallographic databases with their statistics and of such fundamental and fast-growing topics as intermolecular potentials, polymorphism, co-crystallization, and crystal structure prediction by computer. A substantial part of the book is devoted to the techniques of choice in modern simulation, Monte Carlo and molecular dynamics, with their most recent developments and application to formed crystals and to the concomitant phases involved in nucleation and growth. Drawing on the decades-long experience of its author in teaching and research in the field of organic solid state, The Crystalline States of Organic Compounds is an indispensable source of key insights and future directions for students and researchers at any level, in academia and in industry. Condenses theoretical information and practical methods in a single resource Provides a guide on the use of crystallographic databases, structure statistics, and molecular simulations Includes a large number of worked examples and tutorials, with extensive graphics and multimedia

Density Functional Theory: Current Trends and Applications first examines the foundational knowledge surrounding DFT, examining some of its key concepts, such as the Thomas-Fermi model and the Hohenberg-Kohn-Sham theory; looking at the wealth of exchange-correlation functionals; and the advantages and disadvantages of DFT compared to the MO (molecular orbital ) theory and other methods, before exploring the areas of future DFT development. The second section then examines the practical methods and approaches for DFT, looking at the types of density functionals, such as LSDA (local spin-density approximation), GGA (generalized gradient approximation), and meta-GGA functionals; hybrid functionals; DFTB (density functional tight binding) methods; dispersion-corrected functionals; time-dependent DFT; and the plane-wave approach. It also looks at the relationships between DFT and ab initio molecular dynamics and the QM/MM (quantum mechanics/molecular mechanics) approach.This book is designed for graduate- and postgraduate-level students and postdoctoral researchers principally studying computational and physical chemistry, who want to obtain an up-to-date overview and understanding of density functional and its applications.

Provides a thorough and detailed explanation and overview of an important computational quantum mechanical modeling approach and its applications in chemistryIncorporates case studies of the practical applications of DFT and objectively weighs up its advantages and disadvantages and the recent and future potential advancesUp to date volume focused more heavily on the chemistry applications of DFT than most existing available literature

Quantum chemistry requires ever higher computational performance, with more and more sophisticated and dedicated Python scripts being required to solve challenging problems. Although resources for basic use of Python are widely (and often freely) available online and in literature, truly cohesive materials for advanced Python programming skills are lacking.Qiming Sun, a developer of the popular Python package PySCF, provides a comprehensive, end-to-end practical resource for researchers and engineers who have basic Python programming experiences chiefly in computational chemistry but want to take their use of the software forwards to the next level, the book provides an insightful exploration of Numpy, Pandas, and other data analysis tools. Readers will learn how to manage their Python computational projects in a professional way, with various tools and protocols for computational chemistry research and general scientific computing tasks exhibited and analysed from a technical perspective. Multiple programming paradigms including object-oriented, functional, meta-programming, dynamic, concurrent, and vector-oriented are illustrated in various technology scenarios allowing readers to properly use them to enhance their program projects. Readers will also learn how to use the presented optimization technologies to speed up their Python applications, even to the level as fast as a native C++ implementation. The applications of these technologies are then demonstrated using quantum chemistry Python applications.Python for Quantum Chemistry: A Full Stack Programming Guide is written primarily for graduate students, researchers and software engineers working primarily in the fields of theoretical chemistry, computational chemistry, condensed matter physics, material modelling, molecular simulations, and quantum computing.

End-to end guide for advanced Python programming skills and tools related to quantum chemistry researchTackles the following questions: How can you ensure the Python runtime is manageable when the preliminary implementation becomes complicated or evolves many branches? How do I ensure that others' Python program works properly in my project? How do I make my Python project reusable for others?Covers in depth the crucial topic of Python code optimization methods with high-performance computing technologiesProvides examples of Python applications with cutting-edge technologies such as automatic code generation, cloud computing, and GPGPUIncludes discussion of Python runtime mechanism and advanced Python technologies

Cheminformatics with Python provides a ground-up, practical introduction that helps reader make effective use of the software. In four parts, including programming, data, methods, and applications, the book provides a brief introduction to Python language and related scientific computing, cheminformatics, machine learning, and deep learning packages and presents a systematic study of the representation of instrumental data, including molecular structures and common chemical databases. The methods section covers analytical signal processing, multivariate calibration, multivariate resolution, classical machine learning, and deep learning methods. Finally, the application section presents case studies of successful applications of cheminformatics in analytical chemistry, metabolomics, drug discovery, and more.A supporting appendix section and the necessary mathematical, statistical, and information theory-related theories are provided, along with practical tips such as code editors and source code management. Online coding materials on GitHub and an individual Jupyter notebook for each chapter further support practical learning. This book will be a great resource for senior undergraduate students, graduate students, post-docs, and professors primarily in the field of computational and analytical chemistry.Provides an in-depth understanding of the application of deep learning in cheminformatics using Python softwareSimultaneously introduces the basic principles and implementations of deep learning algorithms, demonstrating how to apply deep learning models to chemical data for prediction and classification using PythonDelves into rich case studies and practical project examples to help readers apply what they have learned to real chemical problems and dataAccompanied by an online GitHub repository with relevant Python code for each chapterIncludes an accompanying Jupyter Notebook containing relevant data, methods, and application examples, which can be run directly to get the results

A Beginner's Guide to Computational Chemistry: Methods and Applications provides a basic discussion of computer functionality through operating systems, system administration, and programming followed by a look at key computational methods for electronic structure methods and molecular mechanics, hybrid methods, and solid-state materials. For each topic, essential non-mathematical information is provided so readers can immediately begin to effectively use computational chemistry software. Sections quickly present essential information regarding the fundamental approaches and applications in a down to earth and uncluttered manner.This book is ideal for is upper level undergraduate and entry level graduate students completely new to the field of computational chemistry, and those with little background knowledge. It is well-suited to entry level courses at this level.Provides upper level undergraduate and entry level graduate students with a basic knowledge of computational chemistry methods in a straightforward, non-mathematical formatHighlights the best and most useful computational chemistry, showing the reader how to access them, including software repositories, user groups, and online forumsExplores the way computational chemists think from historical, ethical, and sociological perspectives

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 involvedGives 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 calculationFeatures 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 appropriateIncludes timely, forward-looking chapters on crucial topic areas such as machine learning approaches and hydrogen storage aspectsShows how atomistic design can improve present energy storage materials, as well as help to create those technologies of the future

Theoretical and Physical Chemistry of Triel Bonding: Properties, Mechanisms, and Catalysis explores triel and their compounds, providing a detailed analysis of their molecular and electronic structures, areas often disputed and controversial. It offers a comprehensive description and explanation, emphasizing the unique differences between boron and heavier triel atoms. Key sections cover theoretical foundations, types of interactions, and examples of triel bonds and their characteristics. Additionally, the book highlights triel elements functioning as catalysts and boron compounds in hydrogen storage. Designed for advanced students and researchers in physical or theoretical/computational chemistry, it will also interest organic and inorganic chemists.Compounds of boron and other triel centres have been the subject of numerous studies for a long time, with their properties well-known and frequently discussed. However, the more detailed characteristics of triel compounds have not been well analyzed in existing research and their molecular and electronic structures have often been the subject of dispute and controversy. Triel bonds as a thematic area have garnered significant interest in recent years and this book provides a much broader description and explanation of their properties and characteristics than has previously been available, discussing aspects which are unique to triel bonds such as the differences between boron and the heavier triel atoms.Overviews the field of triel bonding, addressing the steady growth in interest in the topic and lack of existing dedicated book literatureProvides clear definitions and description of triel bonds, with presentation of their characteristics and the use of various theoretical approaches for themIncludes numerous examples of triel interactions taken from crystal structures and from theoretical ab initio and DFT calculationsProvides illustrative examples of triel elements functioning as catalysts and boron compounds as featured in hydrogen storage

Metamorphosis of Computational Chemistry Driven by Artificial Intelligence and Industry 5.0 explores the cutting-edge synergy among Computational Chemistry, Artificial Intelligence (AI), and the emerging paradigm of Industry 5.0. The book offers a comprehensive, introductory overview of how AI-driven techniques are revolutionizing the field of computational chemistry and transforming industries. Readers will explore the convergence of AI algorithms, big data analytics, and advanced computational methods such as Natural language Processing, Image Processing, and Machine Learning in the context of chemical research and industrial processes. The book also discusses how AI is accelerating Computational Chemistry, Materials Science, and Chemical Engineering by automating complex calculations, predicting molecular properties, and optimizing chemical processes. Furthermore, it provides a deep dive into the concept of Industry 5.0, which envisions a new era of manufacturing characterized by human-robot collaboration, intelligent factories, and decentralized production systems. The book illustrates how AI and Computational Chemistry play pivotal roles in realizing the vision of Industry 5.0 by optimizing manufacturing processes, quality control, and sustainability efforts.Encompasses both the technical aspects of computational chemistry and the broader implications for industries and society at largeOffers clear explanations of complex AI algorithms used in computational chemistry, making it accessible to both experts and newcomers to the fieldHelps readers gain insights into real-world applications of Industry 5.0 principles, where AI and automation are transforming manufacturingExplores how smart factories are enhancing efficiency, quality control, and sustainability, and how these innovations are reshaping the future of production in diverse sectorsDelves into case studies that showcase how AI is revolutionizing materials design, leading to the development of novel, high-performance materials for industries ranging from electronics to aerospace

The need to develop innovative solar cell technologies beyond traditional silicon is becoming ever more central to efficient and scalable solar-to-electrical energy conversion. Computational Modeling for Advanced Photovoltaics: Materials, Interfaces, and Phenomena for Beyond-Silicon Solar Cells provides a structured approach to understanding key post-silicon solar cell technologies, including Perovskite Solar Cells (PSC), Organic Solar Cells (OSS), Dye-Sensitized Solar Cells (DSSC), and tandem cells. It outlines the computational challenges and opportunities associated with each technology, providing insights into the modeling techniques best suited for analyzing light absorption, electron transport, and material properties. The chapters feature clear explanations of various modeling methods, from Density Functional Theory (DFT) to emerging techniques like time-dependent DFTB and orbital-free DFT, which promise enhanced accuracy in solar cell applications. The book also highlights the role of data-based methods and materials informatics, bridging the gap between computational chemistry and practical solar cell research. The volume emphasizes didactic value, ensuring that readers can navigate the complexities of computational modeling with ease. It provides a comprehensive guide to the fundamental computational methodologies driving advancements in what is a hugely dynamic field. Modelling of Materials and Processes for Post-Silicon Photovoltaics is written primarily for graduate students and researchers at the intersection of solar energy technologies and computational materials chemistry and science, as well as being accessible to undergraduate students in advanced courses related to these fields. It will be invaluable for computational chemists and faculty seeking to expand their knowledge of modeling techniques in photovoltaics.Connects various types of post-silicon solar cells with their specific modeling needs and contemporary computational capabilities, filling a critical gap in existing literatureSelf-contained and didactic resource ideal for both independent study and as a quasi- textbook for advanced courses designed to ensure readers grasp complex concepts with easeMethodological clarity ensures readers will benefit from clear explanations of what different computational methods can and cannot model, along with guidance on when to use each method based on effort-benefit analysis, simplifying the navigation of available techniquesIncludes advanced modeling methods such as time-dependent DFTB and orbital-free DFT at the forefront of computational chemistry, preparing readers for future applications in solar cell researchExplores data-based methods and materials informatics, providing insights into their applications in solar cell research, equipping readers with the latest tools and techniques in the field

Quantum computing is revolutionizing our approach to solving complex problems in physics, chemistry, and biology. Among its most promising applications is the ability to determine quantum ground states-essential for understanding the fundamental properties of molecular systems, materials, and quantum systems. Historically, accessing these ground states has been computationally challenging, particularly for large and complex systems. Existing resources often focus on specific algorithms in isolation, leaving readers without a broader context or comparative insights. This book not only introduces the theoretical underpinnings of quantum algorithms but also provides practical guidance on their implementation and use cases (within budget).The chapters cover a broad spectrum of quantum algorithms for quantum state preparation, including foundational techniques like the Quantum Phase Estimation (QPE) and Variational Quantum Eigensolver (VQE), as well as advanced approaches such as the Quantum Krylov Subspace Diagonalization (QKSD), Quantum Filter Diagonalization (QFD), and quantum filter approaches. The text also provides other methods like Quantum Imaginary Time Evolution (QITE), resonant transition method, and dissipative quantum algorithm. Quantum Algorithms for Molecular Systems is primarily intended for researchers in the fields of quantum computing and quantum chemistry, with a particular focus on quantum algorithms for noisy intermediate-scale quantum (NISQ) computers and early fault-tolerant quantum computing (EFTQC).It is especially tailored to graduate students and post-doctoral fellows seeking to gain a strong foundation in the concepts and applications of quantum computing for chemistry. Additionally, researchers working on eigenvalue problems will benefit from the methodologies and insights provided.Single resource that brings together a wide range of quantum algorithms under a unified frameworkProvides a deeper understanding of each algorithm's capabilities and constraints, helping readers to make informed decisions for algorithm selection and implementationBridges theory and practice through clear explanations and examples, making it a useful guide for specific applicationsProvides examples with sample source codes for the quantum algorithms

Introduction to Computational Electrochemistry: Modelling Methods and Applications in Interfacial Phenomena, Electrocatalysis, and Energy Storage addresses the various methodologies and intricate processes involved in electrochemical energy interconversion. Recent advancements in incorporating both the electronic responses of electrodes and the molecular dynamic responses of electrolytes are highlighted, thus enabling a deeper understanding of the physicochemical processes occurring at electrode-electrolyte interfaces. The book also introduces applications of modern computational chemistry to various electrochemical systems, including electrocatalytic systems for efficient energy conversion and energy storage systems such as batteries and supercapacitors. Emphasis is placed on state-of-the-art multiscale approaches for the advanced simulation of electrochemical interfaces.By presenting case studies that illustrate underlying mechanisms, explaining experimental observations, and guiding the design of improved systems, the book shows how computational electrochemistry increasingly interplays with experiments in the field of electrochemistry. This book aims to help pave the way for near-future developments that will unravel the atomic details of electrochemical interfaces and foster the growth of non-conventional methodological approaches.Provides a multidisciplinary resource that includes access to the field from various perspectives, unifying ideas and conceptsCovers quantum chemistry, describing chemical reactions, surface science to study processes at catalyst surfaces, materials science to optimize catalysts, and chemical engineering to optimize mass transport and multi-scale factorsIntroduces recent advances in modeling electrochemical interfaces as electrochemical systems have recently gained significant attention due to the growing importance of renewable energy technologiesHelps students gain understanding of the field by mixing cutting-edge research developments in both methods and applications in an educational context to create an up-to-date introduction to computational electrochemistry

This book covers applications of computational techniques to biological problems. These techniques are based by an ever-growing number of researchers with different scientific backgrounds - biologists, chemists, and physicists.

The rapid development of molecular biology in recent years has been mirrored by the rapid development of computer hardware and software. This has resulted in the development of sophisticated computational techniques and a wide range of computer simulations involving such methods. Among the areas where progress has been profound is in the modeling of DNA structure and function, the understanding at a molecular level of the role of solvents in biological phenomena, the calculation of the properties of molecular associations in aqueous solutions, computationally assisted drug design, the prediction of protein structure, and protein - DNA recognition, to mention just a few examples. This volume comprises a balanced blend of contributions covering such topics. They reveal the details of computational approaches designed for biomoleucles and provide extensive illustrations of current applications of modern techniques.

A broad group of readers ranging from beginning graduate students to molecular biology professions should be able to find useful contributions in this selection of reviews.

Theoretical chemistry has been an area of tremendous expansion and development over the past decade; from an approach where we were able to treat only a few atoms quantum mechanically or make fairly crude molecular dynamics simulations, into a discipline with an accuracy and predictive power that has rendered it an essential complementary tool to experiment in basically all areas of science. This volume gives a flavour of the types of problems in biochemistry that theoretical calculations can solve at present, and illustrates the tremendous predictive power these approaches possess.A wide range of computational approaches, from classical MD and Monte Carlo methods, via semi-empirical and DFT approaches on isolated model systems, to Car-Parinello QM-MD and novel hybrid QM/MM studies are covered. The systems investigated also cover a broad range; from membrane-bound proteins to various types of enzymatic reactions as well as inhibitor studies, cofactor properties, solvent effects, transcription and radiation damage to DNA.

Valence bond (VB) theory, which builds the descriptions of molecules from those of its constituent parts, provided the first successful quantum mechanical treatments of chemical bonding. Its language and concepts permeate much of chemistry, at all levels. Various modern formulations of VB theory represent serious tools for quantum chemical studies of molecular electronic structure and reactivity. In physics, there is much VB-based work (particularly in semi-empirical form) on larger systems. Importance of TopicThe last decade has seen significant advances in methodology and a vast increase in the range of applications, with many new researchers entering the field.Why This TitleValence Bond Theory succeeds in presenting a comprehensive selection of contributions from leading valence bond (VB) theory researchers throughout the world. It focuses on the vast increase in the range of applications of methodology based on VB theory during the last decade and especially emphasizes recent advances.

The first volume of this two part series is concerned with the fundamental aspects of relativistic quantum theory, outlining the enormous progress made in the last twenty years in this field. The aim was to create a book such that researchers who become interested in this exciting new field find it useful as a textbook, and do not have to rely on a rather large number of specialized papers published in this area.�No title is currently available that deals with new developments in relativistic quantum electronic structure theory�Interesting and relevant to graduate students in chemistry and physics as well as to all researchers in the field of quantum chemistry�As treatment of heavy elements becomes more important, there will be a constant demand for this title

The field of relativistic electronic structure theory is generally not part of theoretical chemistry education, and is therefore not covered in most quantum chemistry textbooks. This is due to the fact that only in the last two decades have we learned about the importance of relativistic effects in the chemistry of heavy and superheavy elements. Developments in computer hardware together with sophisticated computer algorithms make it now possible to perform four-component relativistic calculations for larger molecules. Two-component and scalar all-electron relativistic schemes are also becoming part of standard ab-initio and density functional program packages for molecules and the solid state. The second volume of this two-part book series is therefore devoted to applications in this area of quantum chemistry and physics of atoms, molecules and the solid state. Part 1 was devoted to fundamental aspects of relativistic electronic structure theory whereas Part 2 covers more of the applications side. This volume opens with a section on the Chemistry of the Superheavy Elements and contains chapters dealing with Accurate Relativistic Fock-Space Calculations for Many-Electron Atoms, Accurate Relativistic Calculations Including QED, Parity-Violation Effects in Molecules, Accurate Determination of Electric Field Gradients for Heavy Atoms and Molecules, Two-Component Relativistic Effective Core Potential Calculations for Molecules, Relativistic Ab-Initio Model Potential Calculations for Molecules and Embedded Clusters, Relativistic Pseudopotential Calculations for Electronic Excited States, Relativistic Effects on NMR Chemical Shifts, Relativistic Density Functional Calculations on Small Molecules, Quantum Chemistry with the Douglas-Kroll-Hess Approach to Relativistic Density Functional Theory, and Relativistic Solid State Calculations.- Comprehensive publication which focuses on new developments in relativistic quantum electronic structure theory- Many leaders from the field of theoretical chemistry have contributed to the TCC series- Will no doubt become a standard text for scientists in this field.

Computational tools have been permanently deposited into the toolbox of theoretical chemists. The impact of new computational tools can hardly be overestimated, and their presence in research and applications is overwhelming. Theoretical methods such as quantum mechanics, molecular dynamics, and statistical mechanics have been successfully used to characterize chemical systems and to design new materials, drugs, and chemicals. This volume on Computational Material Sciences covers selected examples of notable applications of computational techniques to material science. The chapters contained in this volume include discussions of the phenomenon of chaos in chemistry, reaction network analysis, and mechanisms of formation of clusters. Details of more practical applications are also included in the form of reviews of computational design of new materials and the prediction of properties and structures of well known molecular assemblies. Current developments of effective computational methods, which will help in understanding, predicting, and optimizing periodic systems, nanostructures, clusters and model surfaces are also covered in this volume. Reviews of current computational methods applied in material science Reviews of practical applications of modelling of structures and properties of materials Cluster and periodical approaches

This volume provides an overview of current research and recent advances in the area of energetic materials, focusing on explosives and propellants. The contents and format reflect the fact that theory, experiment and computation are closely linked in this field. The challenge of developing energetic materials that are less sensitive to accidental stimuli continues to be of critical importance. This volume opens with discussions of some determinants of sensitivity and its correlations with various molecular and crystal properties. The next several chapters deal in considerable detail with different aspects and mechanisms of the initiation of detonation, and its quantitative description. The second half of this volume focuses upon combustion. Extensive studies model ignition and combustion, with applications to different propellants. The final chapter is an exhaustive computational treatment of the mechanism and kinetics of combustion initiation reactions of ammonium perchlorate.Overall, this volume illustrates the progress that has been made in the field of energetic materials and some of the areas of current activity. It also indicates the challenges involved in characterizing and understanding the properties and behaviour of these compounds. The work is a unique state-of-the-art treatment of the subject, written by pre-eminent researchers in the field.- Overall emphasis is on theory and computation, presented in the context of relevant experimental work - Presents a unique state-of-the-art treatment of the subject - Contributors are preeminent researchers in the field

Computational Photochemistry, Volume 16 provides an overview of general strategies currently used to investigate photochemical processes. Whilst contributing to establishing a branch of computational chemistry that deals with the properties and reactivity of photoexcited molecules, the book also provides insight into the conceptual and methodological research lines in computational photochemistry. Packed with examples of applications of modelling of basic photochemical reactions and the computer-aided development of novel materials in the field of photodegradation (paints), photoprotection (sunscreens), color regulation (photochromic devices) and fluorescent probes, this book is particularly useful to anyone interested in the effect of light on molecules and materials.* Provides an overview of computational photochemistry, dealing with principles and applications* Demonstrates techniques that can be used in the computer-aided design of novel photo responsive materials* Written by experts in computational photochemistry

Theoretical Aspects of Chemical Reactivity provides a broad overview of recent theoretical and computational advancements in the field of chemical reactivity. Contributions have been made by a number of leaders in the field covering theoretical developments to applications in molecular systems and clusters. With an increase in the use of reactivity descriptors, and fundamental theoretical aspects becoming more challenging, this volume serves as an interesting overview where traditional concepts are revisited and explored from new viewpoints, and new varieties of reactivity descriptors are proposed. Includes applications in the frontiers of reactivity principles, and introduces dynamic and statistical viewpoints to chemical reactivity and challenging traditional concepts such as aromaticity.* Written by specialists in the field of chemical reactivity* An authoritative overview of the research and progress * An essential reference material for students

The aim of Molecular and Nano Electronics: Analysis, Design and Simulation is to draw together contributions from some of the most active researchers in this new field in order to illustrate a theory guided-approach to the design of molecular and nano-electronics. The field of molecular and nano-electronics has driven solutions for a post microelectronics era, where microelectronics dominate through the use of silicon as the preferred material and photo-lithography as the fabrication technique to build binary devices (transistors). The construction of such devices yields gates that are able to perform Boolean operations and can be combined with computational systems, capable of storing, processing, and transmitting digital signals encoded as electron currents and charges. Since the invention of the integrated circuits, microelectronics has reached increasing performances by decreasing strategically the size of its devices and systems, an approach known as scaling-down, which simultaneously allow the devices to operate at higher speeds.* Provides a theory-guided approach to the design of molecular and nano-electronics* Includes solutions for researchers working in this area* Contributions from some of the most active researchers in the field of nano-electronics

Over the past few decades, several approaches have been developed for designing nano-structured or molecularly-structured materials. These advances have revolutionized practically all fields of science and engineering, providing an additional design variable, the feature size of the nano-structures, which can be tailored to provide new materials with very special characteristics. Nanomaterials: Design and Simulation explores the role that such advances have made toward a rational design of nanostructures and covers a variety of methods from ab initio electronic structure techniques, ab initio molecular dynamics, to classical molecular dynamics, also being complemented by coarse-graining and continuum methods. Also included is an overview of how the development of these computational tools has enabled the possibility of exploring nanoscopic details and using such information for the prediction of physical and chemical properties that are not always possible to be obtained experimentally.* Provides an overview of approaches that have been developed for designing nano-structured or molecularly-structured materials.* This volume covers several aspects of the simulation and design of nanomaterials analyzed by a selected group of active researchers in the field. * Looks at how the advancement of computational tools have enabled nanoscopic prediction of physical and chemical properties

The primary objective of this volume, the first in a new series entitled Theoretical and Computational Chemistry, is to survey some effective approaches to understanding, describing and predicting ways in which solutes and solvents interact and the effects they have upon each other. The treatment of solute/solvent interactions that is presented emphasizes a synergism between theory and experiment. Data obtained experimentally are used as a basis for developing quantitative theoretical models that permit the correlation and interpretation of the data, and also provide a predictive capability. The latter being of course a key motivation for these efforts. Linear solvation energy relationships have been quite successful in this respect and accordingly receive considerable attention. Other effective approaches, including computational ones, are also being pursued, and are discussed in several chapters. This is an area that is continually evolving, and it is hoped that the present volume will convey a sense of its dynamic nature.

Over the past 25 years, the molecular electrostatic potential has become firmly established as an effective guide to molecular interactions. With the recent advances in computational technology, it is currently being applied to a variety of important chemical and biological systems. Its range of applicability has expanded from primarily a focus on sites for electrophilic and nucleophilic attack to now include solvent effects, studies of zeolite, molecular cluster and crystal behavior, and the correlation and prediction of a wide range of macroscopic properties. Moreover, the increasing prominence of density functional theory has raised the molecular electrostatic potential to a new stature on a more fundamental conceptual level. It is rigorously defined in terms of the electron density, and has very interesting topological characteristics since it explicitly reflects opposing contributions from the nuclei and the electrons.

This volume opens with a survey chapter by one of the original pioneers of the use of the electrostatic potential in studies of chemical reactivity, Jacopo Tomasi. Though the flow of the succeeding chapters is not stringently defined, the overall trend is that the emphasis changes gradually from methodology to applications. Chapters discussing more theoretical topics are placed near the end. Readers will find the wide variety of topics provided by an international group of authors both convincing and useful.

The present status of Density Functional Theory (DFT), which has evolved as the main technique for the study of matter at the atomistic level, is described in this volume. Knowing the behavior of atoms and molecules provides a sure avenue for the design of new materials with specific features and properties in many areas of science and technology. A technique based on purely first principles allowing large savings in time and money greatly benefits the specialist or designer of new materials.

The range of areas where DFT is applied has expanded and continues to do so. Any area where a molecular system is the center of attention can be studied using DFT.The scope of the 22 chapters in this book amply testifies to this.

This volume is devoted to the various aspects of theoretical organic chemistry. In the nineteenth century, organic chemistry was primarily an experimental, empirical science. Throughout the twentieth century, the emphasis has been continually shifting to a more theoretical approach. Today, theoretical organic chemistry is a distinct area of research, with strong links to theoretical physical chemistry, quantum chemistry, computational chemistry, and physical organic chemistry.

The objective in this volume has been to provide a cross-section of a number of interesting topics in theoretical organic chemistry, starting with a detailed account of the historical development of this discipline and including topics devoted to quantum chemistry, physical properties of organic compounds, their reactivity, their biological activity, and their excited-state properties.