Computational modeling study reveals a holographic thermodynamic descriptor accurately predicts oxygen reduction activity at reduced cost, suggesting faster screening of carbon electrocatalysts.
The rational design of metal‐free carbon catalysts for the oxygen reduction reaction (ORR) is limited by heterogeneous active sites and complex thermodynamics. Conventional single‐descriptor methods collapse this complexity, obscuring potential‐determining step transitions. Here we introduce a holographic thermodynamic descriptor (HTD) that reconstructs the dual‐descriptor ORR landscape from a single adsorption free energy. Using a universal scaling relation from over 2200 carbon sites and a consistent switching criterion, HTD achieves high accuracy ( R 2 = 0.949, RMSE = 0.094 V), comparable to dual‐descriptor models, with ~50% lower cost. It is validated on extreme structures ( R 2 = 0.981, RMSE = 0.114 V) and offers a preliminary correlation‐based prescreening approach for bifunctional ORR/HER candidates.
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Hu et al. (2026) studied this question.
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