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催化领域中的高熵合金:进展、挑战与展望

High-Entropy Alloys in Catalysis: Progress, Challenges, and Prospects.

作者信息

Sun Liang, Wen Kaihua, Li Guanjie, Zhang Xindan, Zeng Xiaohui, Johannessen Bernt, Zhang Shilin

机构信息

School of Chemical Engineering, The University of Adelaide, Adelaide 5000, Australia.

Institute of Surface Science, Helmholtz-Zentrum Hereon, Max-Planck-Str. 1, 21502 Geesthacht, Germany.

出版信息

ACS Mater Au. 2024 Sep 29;4(6):547-556. doi: 10.1021/acsmaterialsau.4c00080. eCollection 2024 Nov 13.

DOI:10.1021/acsmaterialsau.4c00080
PMID:39554860
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11565283/
Abstract

High-entropy alloys (HEAs) have become pivotal materials in the field of catalysis, offering unique advantages due to their diverse elemental compositions and complex atomic structures. Recent advances in computational techniques, particularly density functional theory (DFT) and machine learning (ML), have significantly enhanced our understanding and design of HEAs for use in catalysis. These innovative atomistic simulations shed light on the properties of HEAs, enabling the discovery and optimization of catalysis materials for solid-solution structures. This Perspective discusses recent studies that illustrate the progress of HEAs in catalysis. It offers an overview of the properties, constraints, and prospects of HEAs, emphasizing their roles in catalysis to enhance catalytic activity and selectivity. The discussion underscores the capabilities of HEAs as multifunctional catalysts with stable structures. The presented insights aim to inspire future computational and experimental efforts to address the challenges in fine-tuning HEAs properties for improved catalytic performance.

摘要

高熵合金(HEAs)已成为催化领域的关键材料,由于其多样的元素组成和复杂的原子结构而具有独特优势。计算技术的最新进展,特别是密度泛函理论(DFT)和机器学习(ML),显著增强了我们对用于催化的高熵合金的理解和设计。这些创新的原子模拟揭示了高熵合金的性质,有助于发现和优化用于固溶体结构的催化材料。本观点文章讨论了近期说明高熵合金在催化方面进展的研究。它概述了高熵合金的性质、限制和前景,强调了它们在催化中增强催化活性和选择性的作用。讨论强调了高熵合金作为具有稳定结构的多功能催化剂的能力。所呈现的见解旨在激发未来的计算和实验努力,以应对在微调高熵合金性能以提高催化性能方面的挑战。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/444e/11565283/7a3f3f1db37f/mg4c00080_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/444e/11565283/d8beaaa74be6/mg4c00080_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/444e/11565283/12afac9a83a1/mg4c00080_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/444e/11565283/8244f41a1c67/mg4c00080_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/444e/11565283/19784c8d319d/mg4c00080_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/444e/11565283/d9ea0bc3e15d/mg4c00080_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/444e/11565283/cf0147ae1fdc/mg4c00080_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/444e/11565283/7a3f3f1db37f/mg4c00080_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/444e/11565283/d8beaaa74be6/mg4c00080_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/444e/11565283/12afac9a83a1/mg4c00080_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/444e/11565283/8244f41a1c67/mg4c00080_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/444e/11565283/19784c8d319d/mg4c00080_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/444e/11565283/d9ea0bc3e15d/mg4c00080_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/444e/11565283/cf0147ae1fdc/mg4c00080_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/444e/11565283/7a3f3f1db37f/mg4c00080_0007.jpg

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