Understanding the Role of the Local Structure Optimization in Cu–S-Based Single-Atom Catalysts for Oxygen Electroreduction

Abstract

The oxygen reduction reaction (ORR) is a central process in energy conversion and storage systems, such as fuel cells and metal–air batteries. To meet the urgent demand for efficient ORR catalysts, promising single-atom catalysts (SACs) with heteroatoms incorporated into a carbon matrix are a current research focus. However, the complex structure–function relationships between their metal coordination environments and the resulting ORR activity remain to be fully understood. Herein, three Cu-based SACs featuring S heteroatoms at different distances from the Cu center were synthesized by a ligand modification strategy. The short-range order of Cu-SACs was resolved by X-ray absorption spectroscopy (XAS), and the Gibbs adsorption energies (ΔG) of ORR intermediates were calculated by density functional theory (DFT). Using the correlation between ΔGOOH* and ΔGO* as a descriptor for the ORR activity linked to the O–O bond cleavage and Cu–S interatomic distances, we show that balanced *OOH adsorption occurs when S atoms are located in the second coordination shell around the Cu centers forming Cu–N4/S–C moieties. Combined operando Raman spectroscopy and operando XAS further unravel the dynamic role of sulfur incorporation in the optimization of the local coordination environment of Cu centers toward the facilitated generation of key ORR intermediates. When assembled into a rechargeable Zn–air battery (ZAB), the Cu–N4/S–C cathode displayed a peak power density of 138.9 mW cm–2 and sustained operation for 80 h. In a flexible ZAB, the Cu–N4/S–C air cathode revealed an open-circuit potential of 1.56 V and good bending tolerance. This work provides mechanistic insights on how dopant sites of heteroatomic species influence the catalytic activity of metal centers in SACs through their specific local coordination environments, thereby offering valuable atomic-level structure descriptors for performance optimization.