Artificial Intelligence for Materials Science

Artificial Intelligence for Materials Science
Author: Yuan Cheng
Publisher: Springer Nature
Total Pages: 231
Release: 2021-03-26
Genre: Technology & Engineering
ISBN: 3030683109


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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.


Artificial Intelligence for Materials Science
Language: en
Pages: 231
Authors: Yuan Cheng
Categories: Technology & Engineering
Type: BOOK - Published: 2021-03-26 - Publisher: Springer Nature

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Machine learning methods have lowered the cost of exploring new structures of unknown compounds, and can be used to predict reasonable expectations and subseque
Artificial Intelligence for Materials Science
Language: en
Pages: 228
Authors: Yuan Cheng
Categories: Technology & Engineering
Type: BOOK - Published: 2022-03-29 - Publisher: Springer

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Machine learning methods have lowered the cost of exploring new structures of unknown compounds, and can be used to predict reasonable expectations and subseque
Artificial Intelligence-Aided Materials Design
Language: en
Pages: 363
Authors: Rajesh Jha
Categories: Technology & Engineering
Type: BOOK - Published: 2022-03-15 - Publisher: CRC Press

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This book describes the application of artificial intelligence (AI)/machine learning (ML) concepts to develop predictive models that can be used to design alloy
Reviews in Computational Chemistry, Volume 29
Language: en
Pages: 486
Authors: Abby L. Parrill
Categories: Science
Type: BOOK - Published: 2016-04-11 - Publisher: John Wiley & Sons

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The Reviews in Computational Chemistry series brings together leading authorities in the field to teach the newcomer and update the expert on topics centered on
Materials Discovery and Design
Language: en
Pages: 266
Authors: Turab Lookman
Categories: Science
Type: BOOK - Published: 2018-09-22 - Publisher: Springer

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This book addresses the current status, challenges and future directions of data-driven materials discovery and design. It presents the analysis and learning fr