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Machine learning high-throughput screening of rare earth SACs with different coordination environments for the HER
Meiling Liu1, Qiming Fu1, Wei Zhong1
1Faculty of Materials Metallurgy and Chemistry, Jiangxi University of Science and Technology, Ganzhou 341000, People's Republic of China. liuchao198967@126.com.
None:
High-throughput screening of all rare earth SACs was conducted using ML to evaluate their HER performance. DFT calculated the ΔG*H data of 100 groups of catalysts, and the model trained by the GBR algorithm exhibited the highest accuracy, with R2 and RMSE values of 0.970 and 0.157, respectively. The study also identified three potential HER catalysts (|ΔG*H| < 0.20 eV).
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