Elucidating the impact of oxygen functional groups on the catalytic activity of M-N-C catalysts for the oxygen reduction reaction: a density functional theory and machine learning approach.

Efforts to enhance the efficiency of electrocatalysts for the oxygen reduction reaction (ORR) in energy conversion and storage devices present formidable challenges. In this endeavor, M-N-C single-atom catalysts (MN) have emerged as promising candidates due to their precise atomic structure and adaptable electronic properties. However, MN catalysts inherently introduce oxygen functional groups (OGs), intricately influencing the catalytic process and complicating the identification of active sites. This study employs advanced density functional theory (DFT) calculations to investigate the profound influence of OGs on ORR catalysis within MN catalysts (referred to as OGs@MN, where M represents Fe or Co). We established the following activity order for the 2eORR: for OGs@CoN: OH@CoN > CoN > CHO@CoN > C-O-C@CoN > COC@CoN > COOH@CoN > CO@CoN; for OGs@FeN: COC@FeN > CO@FeN > OH@FeN > FeN > COOH@FeN > CHO@FeN > C-O-C@FeN. Multiple oxygen combinations were constructed and found to be the true origin of MN activity (for instance, the overpotential of 2OH@CoN as low as 0.07 V). Furthermore, we explored the performance of the OGs@MN system through charge and d-band center analysis, revealing the limitations of previous electron-withdrawing/donating strategies. Machine learning analysis, including GBR, GPR, and LINER models, effectively guides the prediction of catalyst performance (with an value of 0.93 for predicting Δ in the GBR model). The descriptor was identified as the primary factor characterizing Δ (accounting for 62.8%; OGs@CoN: = 0.9077, OGs@FeN: = 0.7781). This study unveils the significant impact of OGs on MN catalysts and pioneers design and synthesis criteria rooted in . These innovative findings provide valuable insights into understanding the origins of catalytic activity and guiding the design of carbon-based single-atom catalysts, appealing to a broad audience interested in energy conversion technologies and materials science.