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非金属掺杂β-MoC负载Pt单原子催化剂析氢反应活性的第一性原理计算与机器学习

First-Principles Calculations and Machine Learning of Hydrogen Evolution Reaction Activity of Nonmetallic Doped β-MoC Support Pt Single-Atom Catalysts.

作者信息

Song Minhui, Yang Mei, Yang Shuo, Wang Kai, Cao Chenyang, Li Hongfei, Wang Xiaoxu, Gao Panpan, Qian Ping

机构信息

Beijing Advanced Innovation Center for Materials Genome Engineering, University of Science and Technology Beijing, Beijing 100083, China.

Beijing Key Laboratory for Magneto-Photoelectrical Composite and Interface Science, Beijing 100083, China.

出版信息

ACS Appl Mater Interfaces. 2024 Oct 5. doi: 10.1021/acsami.4c10705.

Abstract

The most widely used catalyst for the hydrogen evolution reaction (HER) is Pt, but the high cost and low abundance of Pt need to be urgently addressed. Single-atom catalysts (SACs) have been an effective means of improving the utilization of Pt atoms. In this work, we used a nonmetal (NM = B, N, O, F, Si, P, S, Cl, As, Se, Br, Te, and I) doped β-MoC (100) C-termination surface as the support, with Pt atoms dispersed on the support surface to construct Pt@NM-MoC. Using density functional theory (DFT) calculations, we selected catalysts with excellent HER activity. Among 117 candidate catalysts, 49 catalysts exhibited ideal catalytic performance with Gibbs free energy of hydrogen intermediate (H*) adsorption (Δ) values less than 0.2 eV. The Δ values of 16 catalysts were even lower than that of Pt (Δ ≈ 0.09 eV), with Pt@N-MoC demonstrating the best performance (Δ = -0.01 eV). Combined with electronic structure analysis, we could understand the impact of charge transfer between Pt and the underlying NM atoms on the strength of the Pt-H bond, thereby promoting HER activity. Using machine learning (ML), we identified that the primary influencing factors of the HER catalytic activity in the Pt@NM-MoC system were the Bader charge transfer of Pt (), the d-band center of Pt (ε), and the atomic radius of NM (), with having the greatest impact on the HER catalytic activity.

摘要

用于析氢反应(HER)的最广泛使用的催化剂是铂,但铂的高成本和低丰度问题亟待解决。单原子催化剂(SACs)是提高铂原子利用率的有效手段。在这项工作中,我们使用非金属(NM = B、N、O、F、Si、P、S、Cl、As、Se、Br、Te和I)掺杂的β-MoC(100)C端表面作为载体,将铂原子分散在载体表面以构建Pt@NM-MoC。通过密度泛函理论(DFT)计算,我们筛选出了具有优异析氢反应活性的催化剂。在117种候选催化剂中,有49种催化剂表现出理想的催化性能,其氢中间体(H*)吸附的吉布斯自由能(Δ)值小于0.2 eV。16种催化剂的Δ值甚至低于铂的Δ值(Δ≈0.09 eV),其中Pt@N-MoC表现出最佳性能(Δ = -0.01 eV)。结合电子结构分析,我们可以了解铂与底层NM原子之间的电荷转移对Pt-H键强度的影响,从而促进析氢反应活性。利用机器学习(ML),我们确定了Pt@NM-MoC体系中析氢反应催化活性的主要影响因素为铂的巴德电荷转移()、铂的d带中心(ε)和NM的原子半径(),其中对析氢反应催化活性影响最大。

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