开发用于催化剂优化的计算机引导工作流程. 描述器验证,子集选择和训练集分析

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Jeremy J Henle1, Andrew F Zahrt1, Brennan T Rose1

  • 1Roger Adams Laboratory, Department of Chemistry, University of Illinois, Urbana, Illinois 61801, United States.

Journal of the American Chemical Society
|June 23, 2020
PubMed
概括

这项研究引入了一种统计方法,以简化反选择性催化剂的开发,超越传统的经验主义. 这种信息工作流可以提高催化剂优化和预测建模的准确性.

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