where ∆GX*, ∆Gdes1 and ∆Gdes2 correspond to binding free energies of adsorbate X*, descriptor 1 (des 1) and 2 (des 2), respectively. 𝛼, 𝛽 and 𝛾 are weights for des 1 and des 2, and an intercept, respectively. ∆GN* was chosen as the first descriptor, which is strongly correlated with binding free energies of other adsorbates, except NHNH* (Figure , Figure ). To choose the second descriptor, we calculated mean absolute errors (MAEs) between the predicted binding free energies from the linear functions and the calculated ones. NHNH* is chosen as the second descriptor, which demonstrated the smallest average MAE for predicting binding free energies of the remaining adsorbates (Figure , Figure ). This could be due to the weakest correlation between ∆GN* and ∆GNHNH* (Figure ). Based on the scaling relations and the BEP relations, we constructed a two-dimensional volcano plot, which predicts the total TOF using two simple descriptors (∆GN* and ∆GNHNH*) (Figure ). In line with the results of the thermodynamic analysis (Figure ), BCC and HCP metals are suggested to be inactive due to too strong N* binding, while most of FCC metals, especially Pt, are predicted to be more active as they are located close to the top of the volcano. Notably, Ag, Au and Cu are positioned at weakly N* binding region and expected to be inert, in agreement with the experimental results . These agreements provide a reasonable rationale for using the microkinetic model and the volcano plot to understand the limitations of transition metal catalysts and to design new ones by overcoming those challenges. and ∆GNHNH*). The applied potential was set to 0.60 VRHE, which yielded the maximum current density for Pt catalyst. Only FCC metals are highlighted for clarity, but the complete version can be found in Figure . We additionally tested the effect of higher Ga,i, which did not affect the overall conclusion (Figure ).