贝叶斯优化
催化作用
贝叶斯概率
空格(标点符号)
从头算
计算机科学
纳米技术
材料科学
作者
Jiayu Peng,James K. Damewood,Jessica Karaguesian,Rafael Gómez-Bombarelli,Yang Shao-Horn
出处
期刊:Joule
[Elsevier]
日期:2021-12-01
卷期号:5 (12): 3069-3071
标识
DOI:10.1016/j.joule.2021.11.011
摘要
Summary
Multinary metal alloy catalysts can provide unprecedented tunability in catalyst design, but their optimization is challenging due to the vastness of the combinatorial design space. In a recent issue of Angewandte Chemie International Edition, Rossmeisl and coworkers used a computational framework combining ab initio calculations, kinetic modeling, and Bayesian optimization to efficiently optimize fuel cell catalysts by first quantifying the number of trials needed and then executing an efficient search.
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