Activated chemical bonds in nanoporous and amorphous iridium oxides favor low overpotential for oxygen evolution reaction

Sangseob Lee, Yun Jae Lee, Giyeok Lee, Aloysius Soon

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11 Citations (Scopus)

Abstract

To date, the search for active, selective, and stable electrocatalysts for the oxygen evolution reaction (OER) has not ceased and a detailed atomic-level design of the OER catalyst remains an outstanding (if not, compelling) problem. Considerable studies on different surfaces and polymorphs of iridium oxides (with varying stoichiometries and dopants) have emerged over the years, showing much higher OER activity than the conventionally reported rutile-type IrO2. Here, we have considered different metastable nanoporous and amorphous iridium oxides of different chemical stoichiometries. Using first-principles electronic structure calculations, we investigate the (electro)chemical stability, intercalation properties, and electronic structure of these iridium oxides. Using an empirical regression model between the Ir-O bond characteristics and the measured OER overpotentials, we demonstrate how activated Ir-O bonds (and the presence of more electrophilic oxygens) in these less understood polymorphs of iridium oxides can explain their superior OER performance observed in experiments.

Original languageEnglish
Article number3171
JournalNature communications
Volume13
Issue number1
DOIs
Publication statusPublished - 2022 Dec

Bibliographical note

Funding Information:
S.L., Y.J.L., and G.L. gratefully acknowledge support from the Basic Science Research Program through the National Research Foundation of Korea (NRF 2020R1F1A1063070). Computational resources have been kindly provided by the Korean Institute of Science and Technology Information (KISTI) Supercomputing Center (KSC-2021-CRE-0044) and the Australian National Computational Infrastructure (NCI).

Funding Information:
S.L., Y.J.L., and G.L. gratefully acknowledge support from the Basic Science Research Program through the National Research Foundation of Korea (NRF 2020R1F1A1063070). Computational resources have been kindly provided by the Korean Institute of Science and Technology Information (KISTI) Supercomputing Center (KSC-2021-CRE-0044) and the Australian National Computational Infrastructure (NCI).

Publisher Copyright:
© 2022, The Author(s).

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • General
  • Physics and Astronomy(all)

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