Discovery of Quantitative Electronic Structure-OER Activity Relationship in Metal-Organic Framework Electrocatalysts Using an Integrated Theoretical-Experimental Approach

Developing cost-effective and high-performance catalysts for oxygen evolution reaction (OER) is essential to improve the efficiency of electrochemical conversion devices. Unfortunately, current studies greatly depend on empirical exploration and ignore the inherent relationship between electronic structure and catalytic activity, which impedes the rational design of high-efficiency OER catalysts. Herein, a series of bimetallic Ni-based metal-organic frameworks (Ni-M-MOFs, M = Fe, Co, Cu, Mn, and Zn) with well-defined morphology and active sites are selected as the ideal platform to explore the electronic-structure/catalytic-activity relationship. By integrating density-functional theory calculations and experimental measurements, a volcano-shaped relationship between electronic properties (d-band center and e(g) filling) and OER activity is demonstrated, in which the NiFe-MOF with the optimized energy level and electronic structure situated closer to the volcano summit. It delivers ultra-low overpotentials of 215 and 297 mV for 10 and 500 mA cm(-2), respectively. The identified electronic-structure/catalytic activity relationship is found to be universal for other Ni-based MOF catalysts (e.g., Ni-M-BDC-NH2, Ni-M-BTC, Ni-M-NDC, Ni-M-DOBDC, and Ni-M-PYDC). This work widens the applicability of d band center and e(g) filling descriptors to activity prediction of MOF-based electrocatalysts, providing an insightful perspective to design highly efficient OER catalysts.

Automated summary

The research demonstrates a volcano-shaped relationship between electronic properties and OER activity, showing that NiFe-MOF with optimized energy level and electronic structure delivers ultra-low overpotentials. This electronic-structure/catalytic activity relationship is found to be universal for other Ni-based MOF catalysts, providing insights for designing highly efficient OER catalysts.