The electrocatalytic oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) are key processes in renewable energy technologies, which are important for improving the energy conversion efficiency and promoting sustainable development. Despite significant progress in this area, the development of efficient, stable, and economical bifunctional catalysts still faces many challenges. In this paper, axial halogen ligands (X = F, Cl, Br, I) are chosen as an effective means to strategically modulate the OER/ORR activity of 3d TM phthalocyanine molecule (TMPc). We employ an integrated approach combining density–functional theory calculations with machine learning (ML), aiming to efficiently screen 45 different 3d–TMPc–X systems. Through high–throughput screening, we successfully identified a variety of electrocatalysts with low bifunctional overpotential (ηBi), such as CoPc (ηBi = 0.40 V), FePc–F (ηBi = 0.93 V) and MnPc–Br (ηBi = 0.82 V). The superior performance of these candidates is mainly attributed to their optimized and moderate interactions with oxygen–containing intermediates, which is consistent with the established principles of catalytic fouling relationships and volcano diagrams. Notably, the results show that adsorption of axial halogen ligands is an effective strategy to modulate the strength of the interaction between the oxygenated intermediate and the 3d–TM active center. This modulation significantly affected the bifunctional activity of the catalysts, suggesting that the catalytic performance is not only influenced by the choice of the central TM, but also decisively by the nature of the axial halogen ligands. In addition, machine learning analysis identified four key descriptors (dTM, rTM, εd, and Qe) that can effectively characterize the OER/ORR activity trends of the 3d–TMPc–X series. This study indicates that axial halide coordination is a promising strategy for developing advanced OER/ORR electrocatalysts.
Wang et al. (Tue,) studied this question.