Data-Based Methods for Materials Design and Discovery - Basic Ideas and General Methods (Paperback)

Machine learning methods are changing the way we design and discover new materials. This book provides an overview of approaches successfully used in addressing materials problems (alloys, ferroelectrics, dielectrics) with a focus on probabilistic methods, such as Gaussian processes, to accurately estimate density functions. The authors, who have extensive experience in this interdisciplinary field, discuss generalizations where more than one competing material property is involved or data with differing degrees of precision/costs or fidelity/expense needs to be considered.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Synthesis Lectures on Materials and Optics
Release date:	March 2020
First published:	2020
Authors:	Ghanshyam Pilania • Prasanna V Balachandran • James E. Gubernatis • Turab Lookman
Dimensions:	235 x 191mm (L x W)
Format:	Paperback
Pages:	172
ISBN-13:	978-3-03-101255-6
Languages:	English
Subtitles:	English
Categories:	Books > Science & Mathematics > Physics > Optics (light) Books > Professional & Technical > Mechanical engineering & materials > Materials science > General
LSN:	3-03-101255-0
Barcode:	9783031012556

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