Machine Learning For Materials Discovery
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Machine Learning For Materials Discovery
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Author : N. M. Anoop Krishnan
language : en
Publisher: Springer
Release Date : 2025-05-08
Machine Learning For Materials Discovery written by N. M. Anoop Krishnan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-08 with Technology & Engineering categories.
Focusing on the fundamentals of machine learning, this book covers broad areas of data-driven modeling, ranging from simple regression to advanced machine learning and optimization methods for applications in materials modeling and discovery. The book explains complex mathematical concepts in a lucid manner to ensure that readers from different materials domains are able to use these techniques successfully. A unique feature of this book is its hands-on aspect—each method presented herein is accompanied by a code that implements the method in open-source platforms such as Python. This book is thus aimed at graduate students, researchers, and engineers to enable the use of data-driven methods for understanding and accelerating the discovery of novel materials.
Materials Discovery And Design
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Author : Turab Lookman
language : en
Publisher: Springer
Release Date : 2018-09-22
Materials Discovery And Design written by Turab Lookman and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-22 with Science categories.
This book addresses the current status, challenges and future directions of data-driven materials discovery and design. It presents the analysis and learning from data as a key theme in many science and cyber related applications. The challenging open questions as well as future directions in the application of data science to materials problems are sketched. Computational and experimental facilities today generate vast amounts of data at an unprecedented rate. The book gives guidance to discover new knowledge that enables materials innovation to address grand challenges in energy, environment and security, the clearer link needed between the data from these facilities and the theory and underlying science. The role of inference and optimization methods in distilling the data and constraining predictions using insights and results from theory is key to achieving the desired goals of real time analysis and feedback. Thus, the importance of this book lies in emphasizing that the full value of knowledge driven discovery using data can only be realized by integrating statistical and information sciences with materials science, which is increasingly dependent on high throughput and large scale computational and experimental data gathering efforts. This is especially the case as we enter a new era of big data in materials science with the planning of future experimental facilities such as the Linac Coherent Light Source at Stanford (LCLS-II), the European X-ray Free Electron Laser (EXFEL) and MaRIE (Matter Radiation in Extremes), the signature concept facility from Los Alamos National Laboratory. These facilities are expected to generate hundreds of terabytes to several petabytes of in situ spatially and temporally resolved data per sample. The questions that then arise include how we can learn from the data to accelerate the processing and analysis of reconstructed microstructure, rapidly map spatially resolved properties from high throughput data, devise diagnostics for pattern detection, and guide experiments towards desired targeted properties. The authors are an interdisciplinary group of leading experts who bring the excitement of the nascent and rapidly emerging field of materials informatics to the reader.
Machine Learning In 2d Materials Science
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Author : Parvathi Chundi
language : en
Publisher: CRC Press
Release Date : 2023-11-13
Machine Learning In 2d Materials Science written by Parvathi Chundi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-13 with Computers categories.
Data science and machine learning (ML) methods are increasingly being used to transform the way research is being conducted in materials science to enable new discoveries and design new materials. For any materials science researcher or student, it may be daunting to figure out if ML techniques are useful for them or, if so, which ones are applicable in their individual contexts, and how to study the effectiveness of these methods systematically. KEY FEATURES Provides broad coverage of data science and ML fundamentals to materials science researchers so that they can confidently leverage these techniques in their research projects Offers introductory material in topics such as ML, data integration, and 2D materials Provides in-depth coverage of current ML methods for validating 2D materials using both experimental and simulation data, researching and discovering new 2D materials, and enhancing ML methods with physical properties of materials Discusses customized ML methods for 2D materials data and applications and high-throughput data acquisition Describes several case studies illustrating how ML approaches are currently leading innovations in the discovery, development, manufacturing, and deployment of 2D materials needed for strengthening industrial products Gives future trends in ML for 2D materials, explainable AI, and dealing with extremely large and small, diverse datasets Aimed at materials science researchers, this book allows readers to quickly, yet thoroughly, learn the ML and AI concepts needed to ascertain the applicability of ML methods in their research.
Machine Learning For Advanced Functional Materials
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Author : Nirav Joshi
language : en
Publisher: Springer Nature
Release Date : 2023-05-22
Machine Learning For Advanced Functional Materials written by Nirav Joshi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-22 with Science categories.
This book presents recent advancements of machine learning methods and their applications in material science and nanotechnologies. It provides an introduction to the field and for those who wish to explore machine learning in modeling as well as conduct data analyses of material characteristics. The book discusses ways to enhance the material’s electrical and mechanical properties based on available regression methods for supervised learning and optimization of material attributes. In summary, the growing interest among academics and professionals in the field of machine learning methods in functional nanomaterials such as sensors, solar cells, and photocatalysis is the driving force for behind this book. This is a comprehensive scientific reference book on machine learning for advanced functional materials and provides an in-depth examination of recent achievements in material science by focusing on topical issues using machine learning methods.
Application Of Artificial Intelligence In New Materials Discovery
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Author : Inamuddin
language : en
Publisher: Materials Research Forum LLC
Release Date : 2023-07-05
Application Of Artificial Intelligence In New Materials Discovery written by Inamuddin and has been published by Materials Research Forum LLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-05 with Technology & Engineering categories.
The book is concerned with the use of Artificial Intelligence in the discovery, production and application of new engineering materials. Topics covered include nano-robots. data mining, solar energy systems, materials genomics, polymer manufacturing, and energy conversion issues. Keywords: Artificial Intelligence, Mathematical Models, Machine Learning, Artificial Neural Networks, Bayesian Analysis, Vector Machines, Heuristics, Crystal Structure, Component Prediction, Process Optimization, Density Functional Theory, Monitoring, Classification, Nano-Robots, Data Mining, Solar Photovoltaics, Renewable Energy Systems, Alternative Energy Sources, Material Genomics, Polymer Manufacturing, Energy Conversion.
Accelerating Materials Discovery With Machine Learning
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Author : Rhys Goodall
language : en
Publisher:
Release Date : 2021
Accelerating Materials Discovery With Machine Learning written by Rhys Goodall and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
Machine Learning In Materials Science
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Author : Keith T. Butler
language : en
Publisher: American Chemical Society
Release Date : 2022-06-16
Machine Learning In Materials Science written by Keith T. Butler and has been published by American Chemical Society this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-16 with Technology & Engineering categories.
Machine Learning for Materials Science provides the fundamentals and useful insight into where Machine Learning (ML) will have the greatest impact for the materials science researcher. This digital primer provides example methods for ML applied to experiments and simulations, including the early stages of building an ML solution for a materials science problem, concentrating on where and how to get data and some of the considerations when choosing an approach. The authors demonstrate how to build more robust models, how to make sure that your colleagues trust the results, and how to use ML to accelerate or augment simulations, by introducing methods in which ML can be applied to analyze and process experimental data. They also cover how to build integrated closed-loop experiments where ML is used to plan the course of a materials optimization experiment and how ML can be utilized in the discovery of materials on computers.
Artificial Intelligence For Materials Science
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Author : Yuan Cheng
language : en
Publisher: Springer Nature
Release Date : 2021-03-26
Artificial Intelligence For Materials Science written by Yuan Cheng and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-26 with Technology & Engineering categories.
Machine learning methods have lowered the cost of exploring new structures of unknown compounds, and can be used to predict reasonable expectations and subsequently validated by experimental results. As new insights and several elaborative tools have been developed for materials science and engineering in recent years, it is an appropriate time to present a book covering recent progress in this field. Searchable and interactive databases can promote research on emerging materials. Recently, databases containing a large number of high-quality materials properties for new advanced materials discovery have been developed. These approaches are set to make a significant impact on human life and, with numerous commercial developments emerging, will become a major academic topic in the coming years. This authoritative and comprehensive book will be of interest to both existing researchers in this field as well as others in the materials science community who wish to take advantage of these powerful techniques. The book offers a global spread of authors, from USA, Canada, UK, Japan, France, Russia, China and Singapore, who are all world recognized experts in their separate areas. With content relevant to both academic and commercial points of view, and offering an accessible overview of recent progress and potential future directions, the book will interest graduate students, postgraduate researchers, and consultants and industrial engineers.
Methods And Applications Of Autonomous Experimentation
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Author : Marcus Noack
language : en
Publisher: CRC Press
Release Date : 2023-12-14
Methods And Applications Of Autonomous Experimentation written by Marcus Noack and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-14 with Business & Economics categories.
Autonomous Experimentation is poised to revolutionize scientific experiments at advanced experimental facilities. Whereas previously, human experimenters were burdened with the laborious task of overseeing each measurement, recent advances in mathematics, machine learning and algorithms have alleviated this burden by enabling automated and intelligent decision-making, minimizing the need for human interference. Illustrating theoretical foundations and incorporating practitioners’ first-hand experiences, this book is a practical guide to successful Autonomous Experimentation. Despite the field’s growing potential, there exists numerous myths and misconceptions surrounding Autonomous Experimentation. Combining insights from theorists, machine-learning engineers and applied scientists, this book aims to lay the foundation for future research and widespread adoption within the scientific community. This book is particularly useful for members of the scientific community looking to improve their research methods but also contains additional insights for students and industry professionals interested in the future of the field.
Introduction To Functional Nanomaterials
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Author : M. Anusuya
language : en
Publisher: CRC Press
Release Date : 2024-11-27
Introduction To Functional Nanomaterials written by M. Anusuya and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-27 with Science categories.
This book provides a comprehensive review of nanomaterials, including essential foundational examples of nanosensors, smart nanomaterials, nanopolymers, and nanotubes. Chapters cover their synthesis and characteristics, production methods, and applications, with specific sections exploring nanoelectronics and electro-optic nanotechnology, nanostructures, and nanodevices. This book is a valuable resource for interdisciplinary researchers who want to learn more about the synthesis of nanomaterials and how they are used in different types of energy storage devices, including supercapacitors, batteries, fuel cells solar cells in addition to electrical, chemical, and biomedical engineering. Key Features: Comprehensive overview of how nanomaterials can be utilised in a variety of interdisciplinary applications Explores the fundamental theories, alongside their electrochemical mechanisms and computation Discusses recent developments in electrode designing based on nanomaterials, separators, and the fabrication of advanced devices and their performances