Magnetic moment enhanced CO catalytic oxidation on transition metal (Fe, Co, Ni) doped MoS ₂: A DFT study

Abstract

This study employs density functional theory (DFT) calculations to systematically investigate the structural, electronic, and catalytic performance of transition metal (TM = Fe, Co, Ni) embedded monolayer MoS₂ for CO oxidation. The TM atoms are stably doped into S vacancy sites, inducing significant charge redistribution and electronic structure modulation. Among them, Fe and Co doping generate high magnetic moments and strong hybridization with adsorbates (CO and O₂) at the Fermi level, which substantially enhance the adsorption abilities compared to Ni-doped MoS₂. The CO oxidation reaction proceeds via the Langmuir-Hinshelwood mechanism, with the lowest activation energy (0.37 eV) obtained for Fe-MoS₂, indicating its potential CO catalytic activity at room temperature. The Co-MoS₂ also shows a comparably low barrier (0.41 eV), while Ni-MoS₂ exhibits a significantly higher energy barrier (1.04 eV) due to weaker orbital interactions and negligible magnetic moment. These findings highlight the crucial role of magnetic moment and orbital hybridization in promoting catalytic performance and offer insights into the design of efficient MoS₂-based single-atom catalysts for CO oxidation.

Keywords

DFT / MoS ₂ / Transition metals / CO catalytic oxidation / Magnetic moment

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

CRediT authorship contribution statement

Amna Inayat: Writing – original draft, Methodology, Formal analysis. Usama Arif: Formal analysis. Muhammad Fasih: Visualization, Formal analysis. Jiajia Wang: Supervision, Resources, Conceptualization.

Acknowledgements

This work is supported by National Natural Science Foundation of China (Grant No. 22572043) and Open Subject of National Laboratory of Solid State Microstructures (Grant No. M37060). We are grateful to the High Performance Computing Platform, Hohai University for doing the calculations.

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