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An Introduction To Materials Informatics


An Introduction To Materials Informatics
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An Introduction To Materials Informatics


An Introduction To Materials Informatics
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Author : Tongyi Zhang
language : en
Publisher: Springer Nature
Release Date : 2025-02-26

An Introduction To Materials Informatics written by Tongyi Zhang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-26 with Technology & Engineering categories.


This textbook educates current and future materials workers, engineers, and researchers on Materials Informatics. Volume I serves as an introduction, merging AI, ML, materials science, and engineering. It covers essential topics and algorithms in 11 chapters, including Linear Regression, Neural Networks, and more. Suitable for diverse fields like materials science, physics, and chemistry, it enables quick and easy learning of Materials Informatics for readers without prior AI and ML knowledge.



An Introduction To Materials Informatics


An Introduction To Materials Informatics
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Author : 张统一
language : en
Publisher:
Release Date : 2022

An Introduction To Materials Informatics written by 张统一 and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Machine learning categories.




Materials Informatics I


Materials Informatics I
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Author : Kunal Roy
language : en
Publisher: Springer Nature
Release Date : 2025-05-10

Materials Informatics I written by Kunal Roy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-10 with Science categories.


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.



Materials Informatics


Materials Informatics
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Author : Olexandr Isayev
language : en
Publisher: John Wiley & Sons
Release Date : 2019-08-08

Materials Informatics written by Olexandr Isayev and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-08 with Technology & Engineering categories.


Provides everything readers need to know for applying the power of informatics to materials science There is a tremendous interest in materials informatics and application of data mining to materials science. This book is a one-stop guide to the latest advances in these emerging fields. Bridging the gap between materials science and informatics, it introduces readers to up-to-date data mining and machine learning methods. It also provides an overview of state-of-the-art software and tools. Case studies illustrate the power of materials informatics in guiding the experimental discovery of new materials. Materials Informatics: Methods, Tools and Applications is presented in two parts?Methodological Aspects of Materials Informatics and Practical Aspects and Applications. The first part focuses on developments in software, databases, and high-throughput computational activities. Chapter topics include open quantum materials databases; the ICSD database; open crystallography databases; and more. The second addresses the latest developments in data mining and machine learning for materials science. Its chapters cover genetic algorithms and crystal structure prediction; MQSPR modeling in materials informatics; prediction of materials properties; amongst others. -Bridges the gap between materials science and informatics -Covers all the known methodologies and applications of materials informatics -Presents case studies that illustrate the power of materials informatics in guiding the experimental quest for new materials -Examines the state-of-the-art software and tools being used today Materials Informatics: Methods, Tools and Applications is a must-have resource for materials scientists, chemists, and engineers interested in the methods of materials informatics.



Materials Informatics And Catalysts Informatics


Materials Informatics And Catalysts Informatics
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Author : Keisuke Takahashi
language : en
Publisher: Springer Nature
Release Date : 2024-03-30

Materials Informatics And Catalysts Informatics written by Keisuke Takahashi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-30 with Technology & Engineering categories.


This textbook is designed for students and researchers who are interested in materials and catalysts informatics with little to no prior experience in data science or programming languages. Starting with a comprehensive overview of the concept and historical context of materials and catalysts informatics, it serves as a guide for establishing a robust materials informatics environment. This essential resource is designed to teach vital skills and techniques required for conducting informatics-driven research, including the intersection of hardware, software, programming, machine learning within the field of data science and informatics. Readers will explore fundamental programming techniques, with a specific focus on Python, a versatile and widely-used language in the field. The textbook explores various machine learning techniques, equipping learners with the knowledge to harness the power of data science effectively. The textbook provides Python code examples, demonstrating materials informatics applications, and offers a deeper understanding through real-world case studies using materials and catalysts data. This practical exposure ensures readers are fully prepared to embark on their informatics-driven research endeavors upon completing the textbook. Instructors will also find immense value in this resource, as it consolidates the skills and information required for materials informatics into one comprehensive repository. This streamlines the course development process, significantly reducing the time spent on creating course material. Instructors can leverage this solid foundation to craft engaging and informative lecture content, making the teaching process more efficient and effective.



Materials Informatics Iii


Materials Informatics Iii
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Author : Kunal Roy
language : en
Publisher: Springer Nature
Release Date : 2025-03-01

Materials Informatics Iii written by Kunal Roy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-01 with Science categories.


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.



Materials Informatics


Materials Informatics
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Author : Krishna Rajan
language : en
Publisher: Wiley-Interscience
Release Date : 2018-01-03

Materials Informatics written by Krishna Rajan and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-03 with Technology & Engineering categories.


Materials Informatics: Data-Driven Discovery in Materials Science outlines the value of adding an "informatics" dimension to the analysis of materials science phenomena, by processes which can permit one to gather and survey complex, multiscale information. Such informatics and combinatorial approaches have emerged as powerful tools in materials design and discovery, in much the same way that genomics and bioinformatics impacted the biological arena. Including topics like data mining and combinatorial experimentation, this book covers the current state of the field, and provides examples (via case studies) of the analysis of multivariate data on a wide array of materials systems.



Nanoinformatics


Nanoinformatics
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Author : Isao Tanaka
language : en
Publisher: Springer
Release Date : 2018-01-15

Nanoinformatics written by Isao Tanaka and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-15 with Technology & Engineering categories.


This open access book brings out the state of the art on how informatics-based tools are used and expected to be used in nanomaterials research. There has been great progress in the area in which “big-data” generated by experiments or computations are fully utilized to accelerate discovery of new materials, key factors, and design rules. Data-intensive approaches play indispensable roles in advanced materials characterization. "Materials informatics" is the central paradigm in the new trend. "Nanoinformatics" is its essential subset, which focuses on nanostructures of materials such as surfaces, interfaces, dopants, and point defects, playing a critical role in determining materials properties. There have been significant advances in experimental and computational techniques to characterize individual atoms in nanostructures and to gain quantitative information. The collaboration of researchers in materials science and information science is growing actively and is creating a new trend in materials science and engineering.



Materials Informatics Ii


Materials Informatics Ii
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Author : Kunal Roy
language : en
Publisher: Springer Nature
Release Date : 2025-03-14

Materials Informatics Ii written by Kunal Roy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-14 with Science categories.


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.



Materials Science And Engineering


Materials Science And Engineering
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Author : Krishna Rajan
language : en
Publisher: Elsevier Inc. Chapters
Release Date : 2013-07-10

Materials Science And Engineering written by Krishna Rajan and has been published by Elsevier Inc. Chapters this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-10 with Technology & Engineering categories.


Studying structure–property relationships is an accepted paradigm in materials science, yet these relationships are often not linear and the challenge is to seek patterns among multiple length and time scales. There is rarely a single multiscale theory or experiment that can meaningfully and accurately capture such information. In this chapter we introduce the rationale as to why we need informatics by briefly summarizing the challenges of information complexity one has to deal with in material science, in order to systematically establish structure–property–processing relationships. Some of the concepts and topics to be covered in this book are introduced, including information networks, data mining, databases, and combinatorial experiments to mention a few. The value of “materials informatics” lies in its ability to permit one to survey complex, multiscale information in a high-throughput, statistically robust and yet physically meaningful manner.