Data for 'A systematic study on the metallophilicity of ordered five-atomic-layer MXenes using high-throughput automated workflow and machine learning'
Published: 22 August 2023| Version 2 | DOI: 10.17632/9wx8v7djw3.2
Contributor:
Xiang FengDescription
These files accompany the manuscript 'A systematic study on the metallophilicity of ordered five-atomic-layer MXenes using high-throughput automated workflow and machine learning'. In this manuscript, the metallophilicity of ordered five-atomic-layer MXenes to a total of eight kinds of metal (Li, Na, K, Mg, Ca, Fe, Zn, and Al) anodes is investigated using density functional theory (DFT) and machine learning (ML) schemes.
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Categories
Energy Materials, Machine Learning, Density Functional Theory