Perovskite oxides as bifunctional oxygen electrocatalysts for oxygen evolution/reduction reactions – A mini review
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Abstract
Abstract Energy crisis due to the depletion of fossil fuel as well as the increased population has stimulated researchers to search for new energy resources and energy storage and conversion systems, including fuel cells, electrolyzers and metal–air batteries. Oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) are two reactions that dominate the overall performance of these devices. However, the sluggish kinetics of these two reactions still impedes the practical application of these devices. Therefore, electrocatalysts, especially non-noble metal oxides are needed to expedite the reactions. Perovskite oxides, as a member of the mixed metal oxide family, show promising electrocatalytic performance toward both ORR and OER. However, there are only a few articles regarding the recent progress of perovskites as bifunctional electrocatalysts till now. In this mini-review, we summarize the recent research status and progress of perovskite oxides as electrocatalysts for ORR/OER, including the basic mechanism behind the catalytic reactions, different approaches to synthesize perovskites as well as the various strategies that researchers have developed to promote their electrocatalytic activities. Besides, the related theoretical calculation method, density functional theory (DFT), which is used to understand the mechanism behind these reactions, has also been discussed. It is believed that this mini-review can not only offer researchers guidance to synthesize perovskite oxides as demanded, but also provide researchers more insights into how to rationally design new perovskite-based catalysts with improved bifunctional electrocatalytic properties.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Electrocatalysts for Energy Conversion · Advanced battery technologies research · Fuel Cells and Related Materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (100+)
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