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View our offer Chemistry
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Handbook of Materials Modeling
€ 1066,50 -
Handbook of Materials Modeling
The Handbook of Materials Modeling, 2nd edition is a six-volume major reference serving a steadily growing community at the intersection of two mainstreams of global research: computational science and materials science and technology. This extensively expanded new edition reflects the significant developments in all aspects of computational materials research over the past decade, featuring progress in simulations at multiple scales and increasingly more realistic materials models. Thematically separated into two mutually dependent sets - "Methods: Theory and Modeling (MTM)" and "Applications: Current and Emerging Materials (ACE)" - the handbook runs the entire gamut from theory and methods to simulations and applications. Readers benefit from its in-depth coverage of a broad methodological spectrum extending from advanced atomistic simulations of rare events to data-driven artificial intelligence strategies for materials informatics in the set MTM, as well as forefront emphasis on materials of far-ranging societal importance such as photovoltaics and energy-relevant oxides, and cutting-edge applications to materials for spintronic devices, graphene, cement, and glasses in the set ACE. The thorough, interconnected coverage of methods and applications, together with a line-up of internationally acclaimed editors and authors, will ensure the Handbook of Material Modeling's standing as an enduring source of learning and inspiration for a global community of computational materials scientists.
€ 1192,50 -
Polymer Science, Nanomaterials and Beyond
Exploring the Interdisciplinarity of Materials ResearchDr Fernando Gomes de Souza Jr is a Full Professor at the Institute of Macromolecules, Federal University of Rio de Janeiro (UFRJ), Brazil, and the Nanotechnology Engineering Program at COPPE/UFRJ (O Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia). He is currently an Invited Associate Professor at Florida International University (FIU) College of Engineering and Computing (2024-2025), US. Dr Gomes completed his PhD in Polymer Science and Technology at UFRJ and has since authored 236 scientific articles, 13 books, and 25 book chapters. His research focuses on polymer nanocomposites from renewable resources, with a strong emphasis on sustainability. He has received numerous accolades, including the Young Scientist of Rio de Janeiro (2015) and Scientist of Rio de Janeiro (2021). He is the Editor-in-Chief of Current Applied Polymer Science and Brazilian Journal of Experimental Design, Data Analysis, and Inferential Statistics, contributing significantly to both academia and industry.
€ 116,50 -
Materials Informatics I
This contributed volume explores the integration of machine learning and cheminformatics within materials science, focusing on predictive modeling techniques. It begins with foundational concepts in materials informatics and cheminformatics, emphasizing quantitative structure-property relationships (QSPR). The volume then presents various methods and tools, including advanced QSPR models, quantitative read-across structure-property relationship (q-RASPR) models, optimization strategies with minimal data, and in silico studies using different descriptors. Additionally, it explores machine learning algorithms and their applications in materials science, alongside innovative modeling approaches for quantum-theoretic properties. Overall, the book serves as a comprehensive resource for understanding and applying machine learning in the study and development of advanced materials and is a useful tool for students, researchers and professionals working in these areas.
€ 267,49 -
Machine Learning Applications in Medicine and Biology
This book combines selected papers from the 2022 IEEE Signal Processing in Medicine and Biology Symposium (IEEE SPMB) held at Temple University. The symposium presents multidisciplinary research in the life sciences. Topics covered include:Signal and image analysis (EEG, ECG, MRI)Machine learningData mining and classificationBig data resources Applications of particular interest at the 2022 symposium included digital pathology, computational biology, and quantum computing. The book features tutorials and examples of successful applications that will appeal to a wide range of professionals and researchers in signal processing, medicine, and biology. Presents an interdisciplinary look at research trends;Promotes collaboration between practitioners and researchers;Includes tutorials and examples of successful applications.
€ 117,69 -
Linear and Nonlinear Optical Spectroscopy and Microscopy
The nonlinear optical spectrum signal technology is a new type of optical characterization technology owing to its non-invasiveness and good biocompatibility. This book highlights a comprehensive introduction to the Stimulated Raman scattering (SRS), Anti-Stokes Raman Spectroscopy (CARS), Two-photon Excited Fluorescence (TPEF) and Second Harmonic Generation signals (SHG) technologies. The four types of nonlinear optical signals technologies, especially two-dimensional and three-dimensional imaging, have great application potential in physics, materials science, chemistry and biomedicine. The book covers principles, theoretical calculation methods, signal measurement methods and imaging specific methods. The theoretical part starts from the basics of nonlinear optics and the relationship with strong light, and gradually transitions to theoretical calculation methods for specific optical signals. it combines the classical theory and the quantum theory to help readers develop a thorough understanding of the technologies. The book is a good reference for graduate students majored in physics and chemistry and for researchers working on optics, photonics and materials science.
€ 96,29 -
Materials Informatics II
This contributed volume explores the application of machine learning in predictive modeling within the fields of materials science, nanotechnology, and cheminformatics. It covers a range of topics, including electronic properties of metal nanoclusters, carbon quantum dots, toxicity assessments of nanomaterials, and predictive modeling for fullerenes and perovskite materials. Additionally, the book discusses multiscale modeling and advanced decision support systems for nanomaterial risk management, while also highlighting various machine learning tools, databases, and web platforms designed to predict the properties of materials and molecules. It is a comprehensive guide and a great tool for researchers working at the intersection of machine learning and material sciences.
€ 213,99 -
Artificial Intelligence in Catalysis
Enables researchers and professionals to leverage machine learning tools to optimize catalyst design and chemical processes Artificial Intelligence in Catalysis delivers a state-of-the-art overview of artificial intelligence methodologies applied in catalysis. Divided into three parts, it covers the latest advancements and trends for catalyst discovery and characterization, reaction predictions, and process optimization using machine learning, quantum chemistry, and cheminformatics. Written by an international team of experts in the field with each chapter combining experimental and computational knowledge, Artificial Intelligence in Catalysis includes information on: Artificial intelligence techniques for chemical reaction monitoring and structural analysis Application of artificial neural networks in the analysis of electron microscopy data Construction of training datasets for chemical reactivity prediction through computational means Catalyst optimization and discovery using machine learning models Predicting selectivity in asymmetric catalysis with machine learning Artificial Intelligence in Catalysis is a practical guide for researchers in academia and industry interested in developing new catalysts, improving organic synthesis, and minimizing waste and energy use.
€ 139,00 -
Materials Informatics III
This contributed volume focuses on the application of machine learning and cheminformatics in predictive modeling for organic materials, polymers, solvents, and energetic materials. It provides an in-depth look at how machine learning is utilized to predict key properties of polymers, deep eutectic solvents, and ionic liquids, as well as to improve safety and performance in the study of energetic and reactive materials. With chapters covering polymer informatics, quantitative structure-property relationship (QSPR) modeling, and computational approaches, the book serves as a comprehensive resource for researchers applying predictive modeling techniques to advance materials science and improve material safety and performance.
€ 213,99 -
Computer-Aided and Machine Learning-Driven Drug Design
The computer-aided drug design research field comprises several different knowledge areas, and often, researchers are only familiar or experienced with a small fraction of them. Indeed, pharmaceutical industries and large academic groups rely on a broad range of professionals, including chemists, biologists, pharmacists, and computer scientists. In this sense, it is difficult to be an expert in every single CADD approach. Furthermore, there are well-established methods that are constantly revisited, and novel approaches are introduced, such as machine-learning based scoring functions for molecular docking. This book provides an organized update of the most commonly employed CADD techniques, as well as successful examples of actual applications to develop bioactive compounds/drug candidates. Also includes is a section of case studies that cover certain pharmacological/target classes, focusing on the applications of the previously described methods. This part will especially appeal to professionals who are not as interested in the theoretical aspects of CADD. This is an ideal book for students, researchers, and industry professionals in the fields of pharmacy, chemistry, biology, bioinformatics, computer sciences, and medicine who are seeking a go-to reference on drug design and medicinal chemistry.
€ 213,99 -
Computational Methods for the Multiscale Modelling of Soft Matter
Due to the hierarchical organization of morphology in soft materials and their slow dynamics, a single modelling technique does not suffice to simulate them. The wide range of modelling approaches available span many time and length scales, making it challenging for newcomers to the field to know how to critically assess the tools and to determine which is most appropriate for any given problem. This book provides a concise and clear description of a variety of simulation methods to model these ubiquitous materials. The list of techniques includes numerical and molecular modelling ones and covers several time and length scales.Along with the fundamental concepts of the theory behind the methods, a comprehensive set of examples taken from the broad pool of soft materials is included. These exemplify how, thanks to the increased computational resources nowadays available to almost any research group, computational methods have become a powerful tool to sit alongside other experimental characterizations and show their increasing relevance for the manufacturing sector. Chapters illustrate how modelling techniques can be used to aid interpretation of experimental data, and how experiments can be used to parameterise models. In addition to enabling informed decisions to be made about the modelling tools to adopt for a given problem, the book will enable those who might already be experts in one technique to transition to other tools more easily. This will become increasingly important as multiscale tools become increasingly sophisticated and sufficiently well developed to be used by more casual users of simulation tools.Bringing together all these modelling approaches and applications into one coherent volume, Computational Methods for the Multiscale Modelling of Soft Matter provides a one-stop resource that is written primarily for postgraduate students and researchers in materials science, computational physics and chemists and chemical engineering interested in learning about simulation methods for soft materials as polymers, surfactants, and colloids.
€ 198,50 -
Theoretical and Physical Chemistry of Triel Bonding
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.
€ 215,50