Issue 14, 2023

Rational design of MoS2-supported Cu single-atom catalysts by machine learning potential for enhanced peroxidase-like activity

Abstract

Two-dimensional molybdenum disulfide (2D-MoS2)-supported single atom nanomaterials with enhanced enzyme-like activities are potential substitutes for natural enzymes due to their huge specific surface areas, ease of decoration, high catalytic activity and high catalytic stability. However, their catalytic mechanism remains unclear, making the rational design of nanozymes difficult to achieve. Herein, the mechanisms have been explored to enhance the peroxidase-like activity of MoS2 for H2O2 decomposition. Global neutral network (G-NN) potentials were constructed to accurately and quickly illustrate the mechanisms of MoS2 catalysts and their surface modifications. The high peroxidase-like activity of the MoS2-supported Cu single atom catalyst with sulfur vacancy (Cu@MoS2-Vs) in acidic conditions was systematically evaluated using the trained G-NN potential and density functional theory (DFT), as well as experimental validation. Further analysis of the geometric and electronic properties of pivotal stationary structures revealed the enhanced electron transfer process for high catalytic performance with the modulation of the Cu single atom loading, sulfur vacancy engineering and the surrounding acidic and alkaline environment regulation on the MoS2 basal plane. The results also showed that Cu@MoS2-Vs in an acidic environment exhibited the highest peroxidase-like activity. This work is expected to provide broad implications for the rational design of substrate-supported single-atom catalysts with superior performance and lower cost by surface modification and acidic and alkaline environment regulation.

Graphical abstract: Rational design of MoS2-supported Cu single-atom catalysts by machine learning potential for enhanced peroxidase-like activity

Supplementary files

Article information

Article type
Paper
Submitted
28 12月 2022
Accepted
07 3月 2023
First published
07 3月 2023
This article is Open Access
Creative Commons BY-NC license

Nanoscale, 2023,15, 6686-6695

Rational design of MoS2-supported Cu single-atom catalysts by machine learning potential for enhanced peroxidase-like activity

D. Xu, W. Yin, J. Zhou, L. Wu, H. Yao, M. Sun, P. Chen, X. Deng and L. Zhao, Nanoscale, 2023, 15, 6686 DOI: 10.1039/D2NR07270J

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence. You can use material from this article in other publications, without requesting further permission from the RSC, provided that the correct acknowledgement is given and it is not used for commercial purposes.

To request permission to reproduce material from this article in a commercial publication, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party commercial publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements