Proceedings of MATSUS Fall 2024 Conference (MATSUSFall24)
DOI: https://doi.org/10.29363/nanoge.matsusfall.2024.226
Publication date: 28th August 2024
Understanding selectivity trends is a crucial hurdle in the developing innovative catalysts for generating hydrogen peroxide through the two-electron oxygen reduction reaction (2e-ORR). The adsorption free energy of O* and OOH* intermediate and the degree of O2's adsorption to the surface and have been suggested as selectivity descriptors for 2e-ORR.[1] These approaches have been the main guide for understanding and predicting selectivity for 2e-ORR catalysts over the past decade. Yet, none of them has yielded an appropriate selectivity descriptor capable of quantifying selectivity, thereby serving as a metric for describing trends in selectivity. To resolve this issue, we identify a thermodynamically derived selectivity parameter (ΔΔG) based on computational hydrogen electrode (CHE) model [2] which allows to quantify selectivity using predicted adsorption free energies of ORR intermediates (OOH* and O*) and free energy of H2O2 (Figure 1). [3] We validate the efficacy of this parameter, across a wide spectrum of reported binary alloys [4] and demonstrate that only a small number of binary alloys with a single active site that have been reported to have high activity are selective for 2e-ORR. [5] These findings highlight the potential of ΔΔG as a selectivity parameter for identifying high-performance 2e-ORR catalysts. It also demonstrates the significance of concurrently considering both selectivity and activity trends. This holistic approach is crucial for obtaining a comprehensive understanding in the identification of high-performance catalyst materials for optimal efficiency in various applications.
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