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Updated: Jan 31, 2026

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通过主动机器学习发现高性能Ni0.62Fe0.23Ce0.15O电催化剂,用于通过主动机器学习进行氧气进化反应

Miaomiao Xue1,2, Wenxuan Fan1, Zaibin Xue1

  • 1School of Chemistry and Chemical Engineering, Anhui Province Key Laboratory of Coal Clean Conversion and Low Carbon Utilization, Anhui University of Technology, Ma'anshan 243032, China.

ACS nano
|January 30, 2026
PubMed
概括

机器学习和遗传算法加速了对氧演化反应 (OER) 有效的异原子化过渡金属氧化物 (H-TMO) 电催化剂的发现. 优化的NiFeCeO表现出卓越的性能,通过DFT验证,减少了OER能源障碍.

关键词:
遗传算法 遗传算法 遗传算法不同原子的兴奋剂.机器学习 机器学习氧的演化反应反应的反应.过渡金属氧化物 过渡金属氧化物

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