Application of Artificial Neural Networks for Catalysis: A Review

作者：Li Hao^*; Zhang Zhien^*; Liu Zhijian

来源：Catalysts, 2017, 7(10): UNSP 306.

DOI：10.3390/catal7100306

• machine learning
• artificial neural network (ANN)
• catalyst
• catalysis
• experiment
• theory

Machine learning has proven to be a powerful technique during the past decades. Artificial neural network (ANN), as one of the most popular machine learning algorithms, has been widely applied to various areas. However, their applications for catalysis were not well-studied until recent decades. In this review, we aim to summarize the applications of ANNs for catalysis research reported in the literature. We show how this powerful technique helps people address the highly complicated problems and accelerate the progress of the catalysis community. From the perspectives of both experiment and theory, this review shows how ANNs can be effectively applied for catalysis prediction, the design of new catalysts, and the understanding of catalytic structures.

• 出版日期2017-10
• 单位华北电力大学（保定）; 四川大学; 华北电力大学; 重庆理工大学