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Titlebook: Bayesian Optimization for Materials Science; Daniel Packwood Book 2017 The Author(s) 2017 Bayesian optimisation.intermolecular interaction

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發(fā)表于 2025-3-21 16:05:38 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Bayesian Optimization for Materials Science
影響因子2023Daniel Packwood
視頻videohttp://file.papertrans.cn/182/181874/181874.mp4
發(fā)行地址Is a timely publication as Bayesian optimization gains interest in materials science, and is one of the few introductions to this method for materials scientists.Makes the mathematical content appeali
學(xué)科分類SpringerBriefs in the Mathematics of Materials
圖書封面Titlebook: Bayesian Optimization for Materials Science;  Daniel Packwood Book 2017 The Author(s) 2017 Bayesian optimisation.intermolecular interaction
影響因子This book provides a short and concise introduction to Bayesian optimization specifically for experimental and computational materials scientists. After explaining the basic idea behind Bayesian optimization and some applications to materials science in Chapter 1, the mathematical theory of Bayesian optimization is outlined in Chapter 2. Finally, Chapter 3 discusses an application of Bayesian optimization to a complicated structure optimization problem in computational surface science..Bayesian optimization is a promising global optimization technique that originates in the field of machine learning and is starting to gain attention in materials science. For the purpose of materials design, Bayesian optimization can be used to predict new materials with novel properties without extensive screening of candidate materials. For the purpose of computational materials science, Bayesian optimization can be incorporated into first-principles calculations to perform efficient, global structure optimizations. While research in these directions has been reported in high-profile journals, until now there has been no textbook aimed specifically at materials scientists who wish to incorporate B
Pindex Book 2017
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沙發(fā)
發(fā)表于 2025-3-21 23:19:48 | 只看該作者
板凳
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地板
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5#
發(fā)表于 2025-3-22 10:21:54 | 只看該作者
Bayesian Optimization of Molecules Adsorbed to Metal Surfaces,int in applying Bayesian optimization to such a simple system, as the full potential energy curve can be quickly calculated using simple quantum chemistry. In this chapter, we consider a more complex situation, consisting of organic molecules adsorbed to a metal surface.
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發(fā)表于 2025-3-22 13:47:28 | 只看該作者
https://doi.org/10.1007/978-3-030-73151-9int in applying Bayesian optimization to such a simple system, as the full potential energy curve can be quickly calculated using simple quantum chemistry. In this chapter, we consider a more complex situation, consisting of organic molecules adsorbed to a metal surface.
7#
發(fā)表于 2025-3-22 17:57:38 | 只看該作者
Friedrich Vogel,Arno G. Motulsky M. D.Like any other field of research, materials science involves a lot of trial and error: in the process of creating a new material or device, we will inevitably make several prototypes which fail to perform as hoped.
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發(fā)表于 2025-3-23 00:05:56 | 只看該作者
Friedrich Vogel,Arno G. Motulsky M.D.In this chapter, we introduce the theory of Bayesian optimization procedure and illustrate its application to a simple problem. A more involved application of Bayesian optimization will be presented in Chap.?..
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發(fā)表于 2025-3-23 05:12:08 | 只看該作者
Overview of Bayesian Optimization in Materials Science,Like any other field of research, materials science involves a lot of trial and error: in the process of creating a new material or device, we will inevitably make several prototypes which fail to perform as hoped.
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發(fā)表于 2025-3-23 09:17:39 | 只看該作者
Theory of Bayesian Optimization,In this chapter, we introduce the theory of Bayesian optimization procedure and illustrate its application to a simple problem. A more involved application of Bayesian optimization will be presented in Chap.?..
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