Machine learning-based design of electrocatalytic materials towards high-energy lithium||sulfur batteries development

作者：Zhiyuan Han, An Chen, Zejian Li, Mengtian Zhang, Zhilong Wang, Lixue Yang, Runhua Gao, Yeyang Jia, Guanjun Ji, Zhoujie Lao, Xiao Xiao, Kehao Tao, Jing Gao, Wei Lv, Tianshuai Wang, Jinjin Li, Guangmin Zhou · 发表于：Nature Communications · 年份：2024 · DOI：10.1038/s41467-024-52550-9 · 被引用次数：87 · 研究领域：Machine Learning in Materials Science、Fuel Cells and Related Materials、X-ray Diffraction in Crystallography

The atomic-level interactions among electrocatalytic sites in Li | |S batteries remain unclear. Here, authors propose a multiview machine-learned framework to evaluate electrocatalyst features using limited datasets and intrinsic factors, thus enhancing the understanding of electrocatalytic sites.