High-throughput screening of dual atom catalysts for oxygen reduction and evolution reactions and rechargeable zinc-air battery

Abstract

We provide the rational design of dual atom catalysts (DACs) supported on nitrogen-doped graphene for the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) through high-throughput computational screening of M1M2N6-DAC systems, where M1 and M2 represent Fe, Co, Ni, Ru, Rh, Pd, Os, Ir, or Pt metals. We predict that FeRuN6-DAC at the summit of the volcano plot exhibits a low theoretical ORR overpotential (ηORR) of 0.24 V and a low theoretical OER overpotential (ηOER) of 0.19 V. The low ηORR and ηOER result from the catalytic performance of the Fe site being tuned to electronic properties that facilitate adsorption and desorption of the OH* intermediate. Inspired by these hybrid density functional theory (DFT) computational and machine learning (ML) results, we synthesized FeRuN6-DAC, FeN4-SAC, and RuN4-SAC and characterized them using X-ray photoelectron spectroscopy (XPS), X-ray absorption spectroscopy (XAS), scanning transmission electron microscopy (STEM), and in-situ electron spin resonance (ESR). Our in-situ ESR spectroscopy signifies that the spin of the Fe active site increases with increasing applied potential due to the increase in the concentration of OH* intermediate on Fe. We verified experimentally the predicted catalytic performances, finding that FeRuN6-DAC leads to an experimental ORR overpotential of 0.29 V with a Tafel slope of 104 mVdec−1 and an OER overpotential of 0.27 V with a Tafel slope of 124 mVdec−1. The rechargeable Zinc-air battery setup was fabricated with FeRuN6-DAC in place of the cathode, showing a maximum power density of 0.45 W/cm2 at the current density of 0.44 A/cm2 and good stability after 120 cycles. According to our findings, we demonstrate that DFT-guided strategies are useful for designing advanced DACs applicable to ORR, OER, and Zinc-air battery applications.