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The exploration of catalysts for energy conversion lies at the center of sustainable development. The combination of experimental and computational approaches can provide insights into the inner laws between the catalytic performance and the structural and electronic properties of catalysts. Owing to the inherent advantages of 2D materials over their 3D counterparts, including high specific surface area and abundant surface defects that could provide sufficient active sites, 2D materials are promising candidates and have attracted wide interest in catalysis. Importantly, 2D materials are the most widely computationally investigated models with which to relate computational prediction with experimental confirmation conveniently. Recently, more 2D catalysts have been prepared in experiments while more accurate computational methods have been used to disclose catalytic performance, and explore the mechanism at an atomic level. In this review, recent advances are summarized related to the development and design of 2D electro/photocatalysts. The main emphasis is put on the unique properties of 2D catalysts investigated by the combination of experiments and computations. Computational methods closer to experimental environments are introduced with particular attention to bridge the gap between experiments and computations. In addition, the challenges of computations and experiments are also discussed for 2D catalysts.
Advanced Energy Materials – Wiley
Published: Jan 1, 2022
Keywords: 2D materials; computations; electrocatalysts; machine learning; photocatalysts
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