Mok Dong Hyeon, Back Seoin, Siahrostami Samira
Department of Chemical and Biomolecular Engineering, Institute of Emergent Materials, Sogang University, Seoul, 04107, Republic of Korea.
Department of Chemistry, Simon Fraser University, 8888 University Drive, Burnaby, B.C. V5 A 1S6, Canada.
Angew Chem Int Ed Engl. 2024 Jun 3;63(23):e202404677. doi: 10.1002/anie.202404677. Epub 2024 Apr 12.
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 identification of selectivity patterns has been made more accessible through the introduction of a newly developed selectivity descriptor derived from thermodynamics, denoted as ΔΔG introduced in Chem Catal. 2023, 3(3), 100568. To validate the suitability of this parameter as a descriptor for 2e-ORR selectivity, we utilize an extensive library of 155 binary alloys. We validate that ΔΔG reliably depicts the selectivity trends in binary alloys reported for their high activity in the 2e-ORR. This analysis also enables the identification of nine selective 2e-ORR catalysts underscoring the efficacy of ΔΔG as 2e-ORR selectivity descriptor. This work highlights 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.
理解选择性趋势是开发通过两电子氧还原反应(2e-ORR)生成过氧化氢的创新催化剂的关键障碍。通过引入一种新开发的源自热力学的选择性描述符(表示为ΔΔG,发表于《化学催化》2023年第3卷第3期,100568页),使得选择性模式的识别变得更加容易。为了验证该参数作为2e-ORR选择性描述符的适用性,我们使用了一个包含155种二元合金的广泛数据库。我们验证了ΔΔG能够可靠地描述二元合金中报道的2e-ORR高活性的选择性趋势。该分析还能够识别出九种选择性2e-ORR催化剂,突出了ΔΔG作为2e-ORR选择性描述符的有效性。这项工作强调了同时考虑选择性和活性趋势的重要性。这种整体方法对于全面理解在各种应用中识别高性能催化剂材料以实现最佳效率至关重要。