Molecular metal-nitrogen-carbon (M-N-C) catalysts with well-defined structures and metal-coordination environments exhibit distinct structural properties and excellent electrocatalytic performance, notably in the oxygen reduction reaction (ORR) for fuel cells. Metal-doped azaphthalocyanine (AzPc) catalysts, a variant of molecular M-N-Cs, can be structured with unique long stretching functional groups, which make them have a geometry far from a two-dimensional geometry when loaded onto a carbon substrate, similar to a "dancer" on a stage, and this significantly affects their ORR efficiency at different pH levels. However, linking structural properties to performance is challenging, requiring comprehensive microkinetic modeling, substantial computational resources, and a combination of theoretical and experimental validation. Herein, we conducted pH-dependent microkinetic modeling based upon ab initio calculations and electric field-pH coupled simulations to analyze the pH-dependent ORR performance of carbon-supported Fe-AzPcs with varying surrounding functional groups. In particular, this study incorporates large molecular structures with complex long-chain "dancing patterns", each featuring >650 atoms, to analyze their performance in the ORR. Comparison with experimental ORR data shows that pH-field coupled microkinetic modeling closely matches the observed ORR efficiency at various pH levels in Fe-AzPc catalysts. Our results also indicate that assessing charge transfer at the Fe-site, where the Fe atom typically loses around 1.3 electrons, could be a practical approach for screening appropriate surrounding functional groups for the ORR. This study provides a direct benchmarking analysis for the microkinetic model to identify effective M-N-C catalysts for the ORR under various pH conditions.
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