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模拟-制造-调节高合金与高级电催化剂的激活水解离中心

Ho Ngoc Nam¹, Ravi Nandan², Lei Fu¹

¹Department of Materials Process Engineering, Graduate School of Engineering, Nagoya University, Furu-cho, Chikusa-ku, Nagoya 464-8603, Japan.

Journal of the American Chemical Society

|September 3, 2025

概括

机器学习加速了用于甲醇电氧化的高合金 (HEAs) 的设计. 新型PtPdRhRuMo催化剂显示出增强的活性和耐久性,为高效的燃料电池应用铺平了道路.

科学领域:

材料科学
电化学
计算化学

背景情况:

高合金提供可调节的电子结构和独特的结合点,使其成为有前途的电催化剂.
对于合理的催化剂设计来说, HEA 的庞大构成空间带来了挑战,通常依赖于低效的试错方法.

研究的目的:

通过机器学习和第一原理计算,加速高性能五元高电压反应的合理设计.
调查 (Mo) 加入在激活HEA表面以增强甲醇氧化中的作用.

主要方法:

采用了自下而上的研究策略,将机器学习与第一原则计算相结合.
设计和合成纳米粒子和薄膜形式的中孔PtPdRhRuMo催化剂.
评估甲醇氧化的电催化性能,包括电流密度和质量活性.

主要成果:

成功设计了一种 quinary HEA,PtPdRhRuMo,其特性有利于甲醇氧化反应.
加入Mo显著增强了甲醇吸附和水解离,促进了二氧化碳的产生.
合成的催化剂具有高电流密度 (18.20 mA cm−2) 和质量活性 (9.89 A mgPt−1).

结论:

开发的 PtPdRhRuMo HEA 显示出优异的电催化活性和耐久性.
机器学习辅助的第一原理计算为设计先进的HEA电催化剂提供了有效的途径.
这项工作突显了HEAs在电化学应用中的潜力,特别是燃料电池.

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