1. Efficient ternary mn-based spinel oxide with multiple active sites for oxygen evolution reaction discovered via high-throughput screening methods
- Author
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Mahmoud Gamal Ahmed, Ying Fan Tay, Xiao Chi, Mengyuan Zhang, Joel Ming Rui Tan, Sing Yang Chiam, Andrivo Rusydi, Lydia Helena Wong, School of Materials Science and Engineering, Institute of Materials Research and Engineering, A*STAR, Singapore-HUJ Alliance for Research and Enterprise (SHARE), and Energy Research Institute @ NTU (ERI@N)
- Subjects
Biomaterials ,Materials [Engineering] ,High-Throughput Methods ,General Materials Science ,FeCoMnO ,General Chemistry ,Biotechnology - Abstract
The discovery of more efficient and stable catalysts for oxygen evolution reaction (OER) is vital in improving the efficiency of renewable energy generation devices. Given the large numbers of possible binary and ternary metal oxide OER catalysts, high-throughput methods are necessary to accelerate the rate of discovery. Herein, Mn-based spinel oxide, Fe10 Co40 Mn50 O, is identified for the first time using high-throughput methods demonstrating remarkable catalytic activity (overpotential of 310 mV on fluorine-doped tin oxide (FTO) substrate and 237 mV on Ni foam at 10 mA cm-2 ). Using a combination of soft X-ray absorption spectroscopy and electrochemical measurements, the high catalytic activity is attributed to 1) the formation of multiple active sites in different geometric sites, tetrahedral and octahedral sites; and 2) the formation of active oxyhydroxide phase due to the strong interaction of Co2+ and Fe3+ . Structural and surface characterizations after OER show preservation of Fe10 Co40 Mn50 O surface structure highlighting its durability against irreversible redox damage on the catalytic surface. This work demonstrates the use of a high-throughput approach for the rapid identification of a new catalyst, provides a deeper understanding of catalyst design, and addresses the urgent need for a better and stable catalyst to target greener fuel. Ministry of Education (MOE) National Research Foundation (NRF) This research was partially supported by grants from the National Research Foundation, Prime Minister’s Office, Singapore, under its Campus of Research Excellence and Technological Enterprise (CREATE) program. This work was partially supported by the Singapore Ministry of Education (MOE2019-T2-1-163), Tier 1 grant (2020-T1-001-147(RG64/20)), Tier 2 grant (MOE T2EP50120-00081), Singapore National Research Foundation-National University of Singapore Postdoc Fellowship, and NUS core SupportC-380-003-003-001.
- Published
- 2023