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首页> 外文期刊>Physical chemistry chemical physics: PCCP >First-principles database driven computational neural network approach to the discovery of active ternary nanocatalysts for oxygen reduction reaction
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First-principles database driven computational neural network approach to the discovery of active ternary nanocatalysts for oxygen reduction reaction

机译：第一原理数据库驱动的计算神经网络方法，以发现活性三元纳米催化剂的氧还原反应

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摘要

An elegant machine-learning-based algorithm was applied to study the thermo-electrochemical properties of ternary nanocatalysts for oxygen reduction reaction (ORR). High-dimensional neural network potentials (NNPs) for the interactions among the components were parameterized from big dataset established by first-principles density functional theory calculations. The NNPs were then incorporated with Monte Carlo (MC) and molecular dynamics (MD) simulations to identify not only active, but also electrochemically stable nanocatalysts for ORR in acidic solution. The effects of surface strain caused by selective segregation of certain components on the catalytic performance were accurately characterized. The computationally efficient and precise approach proposes a promising ORR candidate: 2.6 nm icosahedron comprising 60% of Pt and 40% Ni/Cu. Our methodology can be applied for high-throughput screening and designing of key functional nanomaterials to drastically enhance the performance of various electrochemical systems.
机译：优雅的基于机器学习算法应用于研究用于氧还原反应（ORR）三元纳米催化剂的热电化学性能。高维神经网络的潜力（NNP相当）的组件之间的交互是通过第一原理密度泛函理论计算建立大数据集参数。的专业NNP然后用蒙特卡罗（MC）和分子动力学（MD）模拟掺入不仅识别活性，而且电化学稳定的纳米催化剂用于ORR在酸性溶液中。引起的对催化性能的某些组件的选择性偏析表面应变的效果进行准确表征。的计算高效且精确的方法提出了一种有前途的候选ORR：2.6纳米的二十面体包括Pt的60％和40％的Ni / Cu等。我们的方法能够高通量筛选和关键功能纳米材料的设计，大幅提升各种电化学系统的性能申请。

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    Joonhee Kang; Seung Hyo Noh; Jeemin Hwang; Hoje Chun; Hansung Kim; Byungchan Han;

  • 作者单位

    Department of Chemical and Biomolecular Engineering Yonsei University;

    Department of Chemical and Biomolecular Engineering Yonsei University;

    Department of Chemical and Biomolecular Engineering Yonsei University;

    Department of Chemical and Biomolecular Engineering Yonsei University;

    Department of Chemical and Biomolecular Engineering Yonsei University;

    Department of Chemical and Biomolecular Engineering Yonsei University;

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  • 正文语种 eng
  • 中图分类 物理学;化学;
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