journal article·2023-08-02

Regulation mechanisms of electron-delocalized single transition metal-doped Mo2CO2 MXene hydrogen evolution reaction catalysts

Changxin Wang, Mei Yang, Shuo Cao, Xiaoxu Wang, Hao Fu, Yang Bai, Turab Lookman, Ping Qian, Yanjing Su

Physical Review Materials· Volume 7· Issue 8
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Abstract

Two-dimensional (2D) Mo-based MXenes $({\mathrm{Mo}}n+1{C}n{T}x)$ are recognized to have significant potential as hydrogen evolution reaction (HER) activity electrocatalysts. However, appropriate descriptors are absent to predict the H-adsorption Gibbs energy $(\mathrm{\ensuremath{\Delta}}{G}_{\mathrm{H}})$ due to the unique delocalized electronic properties of the Mo atom. In this paper, we used first-principles calculations and machine learning to study the HER activity of ${\mathrm{Mo}}2\mathrm{C}{\mathrm{O}}2$ with single transition metal-doped (${\mathrm{Mo}}2\mathrm{C}{\mathrm{O}}2$-STM), and elucidate the mechanisms by which single transition metals (STMs) regulate the hydrogen evolution reaction. Our results revealed that $\mathrm{\ensuremath{\Delta}}{G}_{\mathrm{H}}$ has a ``W'' shape as a function of the doped atom changing in one period. The electronic structure analysis indicates that the electronic delocalized Mo has a longer range affecting not only the nearest atoms, but the second-nearest neighbor (STM-Mo) bonding effect controls the periodic distribution of $\mathrm{\ensuremath{\Delta}}{G}_{\mathrm{H}}$. Using machine-learning method, we quantized the STM regulation mechanism using five key structural and electronic descriptors, and predicted the $\mathrm{\ensuremath{\Delta}}{G}_{\mathrm{H}}$ of ${\mathrm{Mo}}2\mathrm{C}{\mathrm{O}}2$-STM, which were also extended to ${\mathrm{W}}2\mathrm{C}{\mathrm{O}}2$-STM successfully. Our findings highlight the importance of considering second-nearest-neighbor bonding effects in similar delocalized materials systems research.
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Research context

OpenAlex topics: MXene and MAX Phase Materials · Electrocatalysts for Energy Conversion · 2D Materials and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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