催化作用
无定形固体
合金
材料科学
非晶态金属
化学工程
耐久性
纳米技术
冶金
复合材料
化学
结晶学
有机化学
工程类
作者
Siyan Gao,Huijie Zhen,Bo Wen,Jiang Ma,Xi Zhang
出处
期刊:Nanoscale
[The Royal Society of Chemistry]
日期:2022-01-01
卷期号:14 (7): 2660-2667
被引量:12
摘要
The amorphous alloy Pd40Ni10Cu30P20 is a rising star as an HER catalyst since it possesses an excellent electrocatalytic activity and a high durability in practical experiments. However, the physical origin of the electrocatalytic performance of the amorphous alloy catalyst is still unclear due to the difficulty of amorphous modelling and the huge cost of DFT calculations. Here, we built a Smooth Overlap of Atomic Positions-Machine Learning (SOAP-ML) model to accelerate the DFT study on the effect of the local atomic environment of the Pd40Ni10Cu30P20 catalyst. Compared to pure DFT-calculated results and experiment, our model makes a good prediction (MSE = 0.018) of the local atomic environment with the best catalysis. We calculated 40 000 active sites on the amorphous alloy surface and obtained the optimal atomic ratio of the alloy catalyst (Pd : Cu : P : Ni = 0.51 : 0.33 : 0.09 : 0.07), indicating that the Pd d electrons mainly enhance the catalytic performance. We employed the SOAP-ML model to reveal the physical origin of the long durability as the dealloying of Ni, which is highly consistent with the experimental results. The above results all prove the high accuracy and reliability of the established SOAP-ML model and provide an appealing idea for the future application of the amorphous alloy.
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