Zichao Shen, Ke Wang, Yutong Yuan, Fan Gao, Xinqiang Wang, Wengang Cui, Fulai Qi, Xiangrong Ren, Jian Chen, Chunhui Xiao, Hongge Pan
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引用次数: 0
Abstract
The sluggish kinetics of the oxygen evolution reaction (OER) in alkaline water electrolysis lead to high overpotentials, limiting cost-effective green hydrogen production. Ni-based catalysts, recognized as promising OER electrocatalysts, require electronic structure modulation to enhance performance. However, under oxidizing conditions, Ni-based materials undergo surface reconstruction with significant electronic alterations, rendering bulk-phase studies less practical. Recent efforts focus on regulating reconstructed surface electronic structures for improved efficiency, underscoring the need for a systematic review on this critical topic. This review highlights the fundamental progress regarding the electronic structure regulation of reconstructed surface of Ni-based OER electrocatalysts for better understanding the surface reconstruction process and the structure-activity relationship, including the basic understanding of OER mechanism and surface reconstruction of Ni-based materials, the principles and practical applications of key electronic structure descriptors with their respective advantages and limitations, and recent advancements and developing bottle-necks in surface reconstruction chemistry across diverse Ni-based OER catalyst systems. Finally, the challenges facing surface reconstruction of Ni-based OER catalysts are summarized, and several future prospects are proposed to guide the in-depth analysis of the reconstruction mechanism and the rational design of Ni-based OER catalysts.
Small MethodsMaterials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍:
Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques.
With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community.
The online ISSN for Small Methods is 2366-9608.