High-entropy nanoparticles: Synthesis-structureproperty relationships and data-driven discovery

Yonggang Yao, Qi Dong, Alexandra Brozena, Jian Luo, Jianwei Miao, Miaofang Chi, Chao Wang, Ioannis G. Kevrekidis, Zhiyong Jason Ren, Jeffrey Greeley, Guofeng Wang, Abraham Anapolsky, Liangbing Hu

Research output: Contribution to journalReview articlepeer-review

8 Scopus citations

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.

Original languageEnglish (US)
Article numberabn3103
JournalScience
Volume376
Issue number6589
DOIs
StatePublished - Apr 8 2022

All Science Journal Classification (ASJC) codes

  • General

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