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High-Entropy Alloys As a Discovery Platform for Electrocatalysis

Joule(2019)

Univ Copenhagen

Cited 571|Views108
Abstract
High-entropy alloys (HEAs) provide a near-continuous distribution of adsorption energies. With a minority of sites having optimal properties that dominate the catalysis, the overall catalytic activity can increase. In this article, we focus on the oxygen reduction reaction (ORR). We present density functional theory (DFT) calculated *OH and *O adsorption energies on a random subset of available binding sites on the surface of the HEA IrPdPtRhRu. Employing a simple machine learning algorithm, we predict remaining adsorption energies, finding good agreement between calculated and predicted values. With a full catalog of available adsorption energies, an appropriate expression for predicting catalytic activity was used to optimize the HEA composition. The HEA then becomes a design platform for the unbiased discovery of new alloys by promoting sites with exceptional catalytic activity. Setting different optimization constraints led to a new HEA composition and binary alloy IrPt, showing significant enhancements over pure Pt(111).
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Key words
electrocatalysis,ORR,high-entropy alloy,multicomponent alloy,machine learning,rational-design
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要点】:该论文利用高熵合金(HEAs)作为发现平台,通过优化其组成,提高氧还原反应(ORR)的催化活性,并使用机器学习算法预测吸附能,从而实现了对具有优异催化活性的位点的促进,创新点在于将高熵合金应用于电催化领域,并通过机器学习优化合金组成。

方法】:该研究主要采用密度泛函理论(DFT)计算了HEA IrPdPtRhRu表面随机子集上的OH和O吸附能,并利用简单的机器学习算法预测了剩余的吸附能。

实验】:通过对不同优化约束的设置,发现了一种新的HEA组成和二元合金IrPt,其在ORR催化活性上显著优于纯Pt(111)。实验结果显示,这种新合金在电催化领域具有巨大的应用潜力。