Machine learning-assisted dual-atom sites design with interpretable descriptors unifying electrocatalytic reactions

Abstract Low-cost, efficient catalyst high-throughput screening is crucial for future renewable energy technology. Interpretable machine learning is a powerful method for accelerating catalyst design by extracting physical meaning but faces huge challenges. This paper describes an interpretable desc...

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Bibliographic Details

Published in:	Nature Communications
Main Authors:	Xiaoyun Lin, Xiaowei Du, Shican Wu, Shiyu Zhen, Wei Liu, Chunlei Pei, Peng Zhang, Zhi-Jian Zhao, Jinlong Gong
Format:	Article
Language:	English
Published:	Nature Portfolio 2024-09-01
Online Access:	https://doi.org/10.1038/s41467-024-52519-8