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高熵纳米颗粒:合成-结构-性能关系与数据驱动的发现。

High-entropy nanoparticles: Synthesis-structure-property relationships and data-driven discovery.

机构信息

Department of Materials Science and Engineering, University of Maryland, College Park, MD 20742, USA.

Department of NanoEngineering, Program of Materials Science and Engineering, University of California San Diego, La Jolla, CA 92093, USA.

出版信息

Science. 2022 Apr 8;376(6589):eabn3103. doi: 10.1126/science.abn3103.

Abstract

High-entropy nanoparticles have become a rapidly growing area of research in recent years. Because of their multielemental compositions and unique high-entropy mixing states (i.e., solid-solution) that can lead to tunable activity and enhanced stability, these nanoparticles have received notable attention for catalyst design and exploration. However, this strong potential is also accompanied by grand challenges originating from their vast compositional space and complex atomic structure, which hinder comprehensive exploration and fundamental understanding. Through a multidisciplinary view of synthesis, characterization, catalytic applications, high-throughput screening, and data-driven materials discovery, this review is dedicated to discussing the important progress of high-entropy nanoparticles and unveiling the critical needs for their future development for catalysis, energy, and sustainability applications.

摘要

高熵纳米颗粒近年来成为研究的热点。由于其多元素组成和独特的高熵混合状态(即固溶体),可以实现可调的活性和增强的稳定性,这些纳米颗粒在催化剂设计和探索方面引起了广泛关注。然而,这种巨大的潜力也伴随着巨大的挑战,这些挑战源于其广阔的组成空间和复杂的原子结构,阻碍了全面的探索和基础理解。通过合成、表征、催化应用、高通量筛选和数据驱动的材料发现等多学科的视角,本文致力于讨论高熵纳米颗粒的重要进展,并揭示其在催化、能源和可持续性应用方面未来发展的关键需求。

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