机器学习辅助下无铂RuNiCo纳米笼在酸性介质中电催化氢氧化反应的开发

IF 5.5 3区材料科学 Q2 CHEMISTRY, PHYSICAL

ACS Applied Energy Materials Pub Date : 2025-09-29 DOI:10.1021/acsaem.5c02113

Colin A. Tadgell, , , Masaru Kato*, , , Sae Dieb, , , Keitaro Sodeyama, , , Takahito Hoshi, , , Koshiro Suzuki, , , Bohao Du, , , Takeshi Watanabe, , and , Ichizo Yagi*,

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引用次数: 0

摘要

通过数据驱动合成，我们从16,384种可能的组合（<1%）中进行了24次实验，开发了两种最佳的酸性介质中氢氧化反应（HOR）的电催化剂：PtIrRuNiCo纳米线和不含pt的RuNiCo纳米笼。在贝叶斯优化（BO）过程中得到的目标函数与实验电流密度高度相关。由于抑制了表面氧化物的形成，RuNiCo纳米笼表现出比Ru更高的HOR活性。我们的bo辅助方法加速了高活性电催化剂的开发，而不需要高通量合成。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Machine Learning-Assisted Development of Platinum-Free RuNiCo Nanocages for Electrocatalytic Hydrogen Oxidation Reaction in Acidic Media

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Machine Learning-Assisted Development of Platinum-Free RuNiCo Nanocages for Electrocatalytic Hydrogen Oxidation Reaction in Acidic Media

Through data-driven synthesis involving 24 experiments from 16,384 possible combinations (<1%), we developed two optimal electrocatalysts for the hydrogen oxidation reaction (HOR) in acidic media: PtIrRuNiCo nanowires and Pt-free RuNiCo nanocages. The objective function obtained in the Bayesian optimization (BO) process is highly correlated with the experimental current density for the HOR. The RuNiCo nanocages exhibited higher HOR activity than Ru because of the suppression of the surface oxide formation. Our BO-assisted approach accelerates the development of highly active electrocatalysts without requiring high-throughput synthesis.

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来源期刊

ACS Applied Energy Materials Materials Science-Materials Chemistry

CiteScore

10.30

自引率

6.20%

发文量

1368

期刊介绍： ACS Applied Energy Materials is an interdisciplinary journal publishing original research covering all aspects of materials, engineering, chemistry, physics and biology relevant to energy conversion and storage. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important energy applications.