Suppr超能文献

识别MoSi@MoO异质结中用于增强析氢的活性位点。

Identifying the Active Sites in MoSi@MoO Heterojunctions for Enhanced Hydrogen Evolution.

作者信息

Gao Bo, Cheng Qiuping, Du Xiaoye, Ding Shujiang, Xiao Chunhui, Wang Jin, Song Zhongxiao, Jang Ho Won

机构信息

School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao, Shandong, 266525, China.

Key Lab of Industrial Fluid Energy Conservation and Pollution Control (Qingdao University of Technology), Ministry of Education, Qingdao, Shandong, 266525, China.

出版信息

Small Methods. 2024 Sep;8(9):e2301542. doi: 10.1002/smtd.202301542. Epub 2024 Apr 11.

Abstract

Developing Two-dimensional (2D) Mo-based heterogeneous nanomaterials is of great significance for energy conversion, especially in alkaline hydrogen evolution reaction (HER), however, it remains a challenge to identify the active sites at the interface due to the structure complexity. Herein, the real active sites are systematically explored during the HER process in varied Mo-based 2D materials by theoretical computational and magnetron sputtering approaches first to filtrate the candidates, then successfully combined the MoSi and MoO together through Oxygen doping to construct heterojunctions. Benefiting from the synergistic effects between the MoSi and MoO, the obtained MoSi@MoO exhibits an unprecedented overpotential of 72 mV at a current density of 10 mA cm. Density functional theory calculations uncover the different Gibbs free energy of hydrogen adsorption (ΔG) values achieved at the interfaces with different sites as adsorption sites. The results can facilitate the optimization of heterojunction electrocatalyst design principles for the Mo-based 2D materials.

摘要

开发二维(2D)钼基异质纳米材料对于能量转换具有重要意义,特别是在碱性析氢反应(HER)中,然而,由于结构复杂性,识别界面处的活性位点仍然是一个挑战。在此,通过理论计算和磁控溅射方法,首先在各种钼基二维材料的HER过程中系统地探索实际活性位点以筛选候选者,然后通过氧掺杂成功地将MoSi和MoO结合在一起以构建异质结。受益于MoSi和MoO之间的协同效应,所获得的MoSi@MoO在电流密度为10 mA cm时表现出前所未有的72 mV过电位。密度泛函理论计算揭示了在具有不同位点作为吸附位点的界面处实现的不同氢吸附吉布斯自由能(ΔG)值。这些结果有助于优化钼基二维材料的异质结电催化剂设计原则。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验