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

• Published in: Science (American Association for the Advancement of Science) Vol. 376; no. 6589; p. eabn3103
• Main Authors: Yao, Yonggang, Dong, Qi, Brozena, Alexandra, Luo, Jian, Miao, Jianwei, Chi, Miaofang, Wang, Chao, Kevrekidis, Ioannis G., Ren, Zhiyong Jason, Greeley, Jeffrey, Wang, Guofeng, Anapolsky, Abraham, Hu, Liangbing
• Format: Journal Article
• Language: English
• Published: United States The American Association for the Advancement of Science 08.04.2022
• Subjects: Amorphous materials; Atomic structure; Cascade chemical reactions; Catalysis; Catalysts; Catalytic activity; Composition; Computer applications; Crystal defects; Data mining; Design optimization; Electron states; Energy; Energy technology; Entropy; Evolution; Experimental methods; Experimentation; Exploration; High-throughput screening; Literary Devices; Machine learning; Nanomaterials; Nanoparticles; Opportunities; Optimization; Phosphates; Physicochemical properties; Scientific Concepts; Selectivity; Solid solutions; Structural analysis; Structural stability; Synthesis

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 att...