Layered double perovskite (LnBaM₂O_5+δ, Ln = lanthanides, M = Mn or Co) has recently caused intensive attentions in water electrolysis area. Here a series of Mn-based layered perovskite oxides are investigated as enhanced bifunctional catalysts for water electrolysis. First, we found that compared with the pristine Pr_0.5Ba_0.5MnO_3−δ, the layered PrBaMn₂O_5+δ (H-PBM) is characterized by boosted oxygen reduction/evolution reaction activities. The improvement can be ascribed to the introduction of additional oxygen vacancies, an optimized e_g filling of Mn ions, and the facile incorporation of oxygen into layered H-PBM.^[1] In addition, the effect of oxygen vacancies present in layered perovskites on water electrolysis activity is further investigated with neodymium barium manganese oxides. We found that by facilely controlling annealing conditions, the caused small oxygen composition changes could markedly alter the crystallographic structure, electronic configuration and atomic arrangements (structural distortion) of the layered perovskite oxides, and thus the oxygen and hydrogen evolution reaction (OER and HER) activities. The large family of layered perovskite is for the first time applied in overall water splitting area.^[2] Layered NdBaMn₂O_5.5 demonstrates significant improvement in catalyzing OER and HER, in contrast to its counterparts including disordered Nd_0.5Ba_0.5MnO_3-δ as well as NdBaMn₂O_5.5-δ and NdBaMn₂O_5.5+δ (δ < 0.5). The substantially enhanced performance is attributed to the approximately half-filled eg orbit occupancy, optimized O p-band center location, as well as distorted structure. Interestingly, we found that for the investigated perovskite oxides, their OER and HER activity seem correlated, i.e., the material achieving a higher OER activity is also more active in catalyzing HER. As a result, the previously developed OER activity descriptors such e_g filling and Op band center location, which determines the charge transfer between the surface cation and adsorbed reaction intermediates, may potentially apply to HER activity prediction as well.

References:

[1] D. Chen, J. Wang, Z. Zhang, Z. Shao, F. Ciucci, Chem. Commun. 2016, 52, 10739.

[2] J. Wang, Y. Gao, D. Chen, J. Liu, Z. Zhang, Z. Shao, F. Ciucci, ACS Catal. 2018, 8, 364.