Revisiting the universal principle for the rational design of single-atom electrocatalysts

The notion of descriptors has been widely used for assessing structure–activity relationships for many types of heterogenous catalytic reaction, as well as in searching for highly active single-atom catalysts (SACs). Here, with the aid of a machine-learning model for identifying key intrinsic properties of SACs, we revisit our previous descriptor φ [Nat. Catal. 1, 339–348 (2018)] and present φ′ to correlate the activity of graphene-based SACs for the oxygen reduction reaction, oxygen evolution reaction and hydrogen evolution reaction. The descriptor φ′ not only captures the activity trend among experimentally reported SACs, but can also help with the search for SACs to replace precious-metal-based commercial catalysts (for example Pt/C and IrO₂), including Fe-pyridine/pyrrole-4N for the oxygen reduction reaction and Co-pyridine/pyrrole-4N for the oxygen evolution reaction (discovered in previous experimental studies). More importantly, we show that the descriptor φ′ can be broadly applicable to correlate SACs embedded in small-, mid- and large-sized macrocyclic complexes, so long as the active metal centre has the same local coordination environment.