Data-driven identification of low-dimensional descriptors for the rational design of stable and active single-atom catalysts for nitrogen oxidation

Despite recent advances, simple intrinsic descriptors that can simultaneously assess the stability and activity of electrocatalysts for nitrogen oxidation remain elusive. In this work, first-principles calculations combined with data-driven analysis were employed to systematically investigate the stability and catalytic performance of single-atom catalysts supported on the anatase TiO2(101) surface. 58 transition-metal single-atom sites were constructed and screened. The analysis results reveal that three intrinsic elemental parameters, namely atomic weight (MW), d-electron number (Nd), and the presence of oxygen vacancies (VO), serve as unified intrinsic descriptors for both stability and activity. This three-parameter descriptor establishes a clear structure–stability–activity relationship space, enabling the identification of a region that simultaneously favors both structural stability and catalytic activity. Furthermore, the effectiveness of this descriptor-guided design window is validated through Pareto-front analysis. As a result, W-TiO2 is identified as the optimal catalyst, achieving a balanced optimization between structural stability and catalytic activity.

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