In this work, the hydrogenation performances of nonmetal sites in the transition metal dichalcogenides with the stoichiometry of $M{\mathit{X}}_2$ are systematically investigated using the first principles calculations. The trained machine learning model demonstrates that the $p_{\mathrm{z}}$ band center, bandgap, and the intrinsic nature of $X$ atoms are the key factors influencing the HER activity of $\mathit{M}{\mathit{X}}_2$. Furthermore, it also reveals that the observed relations between the $p_{\mathrm{z}}$ band center and HER activity in the semiconductorlike materials do not follow the scaling law, which originates from the bandgap-induced downshift of bonding and antibonding states. In addition to the bandgap, the intrinsic $p$ orbital energy level of the nonmetal atoms also contributes to the translation of $p_{\mathrm{z}}$ band center. Extended calculations indicate that the descriptor is equally applicable to the other catalysts, suggesting its universality in predicting the HER activity of nonmetal sites.

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• Adsorption
• Electronic structure of atoms & molecules
• First-principles calculations
• Hydrogen energy
• Surface & interfacial phenomena