四川师范大学学报（自然科学版）2025，Vol.48Issue(3)：285-311,27.DOI:10.3969/j.issn.1001-8395.2025.03.001
高熵陶瓷的功能性应用和数据驱动设计
Functional Applications and Data-driven Design of High-entropy Ceramics
摘要
Abstract
High-entropy ceramics(HECs),as a member of the large family of high-entropy materials(HEMs),are defined as solid solutions containing five or more cationic or anionic sublattices with high configurational entropy.HECs and high-entropy alloys(HEAs)share the similar"four major effects",including the high-entropy effect,the lattice distortion effect,the hysteresis-diffusion effect,and the synergistic effect.The compositional and structural complexity of HECs allows them to exhibit a diverse range of per-formance characteristics,which have the potential to be applied in numerous technological fields.These include,but are not limited to,wear and corrosion-resistant coatings,thermal barrier coatings,wave-absorbing coatings,solar energy-absorbing and irradiation-re-sistant coatings,and so on.Nevertheless,the expansive compositional space necessitates the time-consuming and costly experimental trial-and-error method as a significant factor in the development of new HECs.In the field of materials science,the discovery and iden-tification of new compositions can be accelerated by data-driven and high-throughput methods that employ machine learning(ML)methods for phase prediction and property prediction of new materials.This paper presents a review of the functional applications of high-entropy ceramics,with a particular focus on data-driven methods and high-throughput strategies.The objective is to provide in-sights that can facilitate the advancement and innovation of high-entropy ceramics in functional applications.关键词
高熵陶瓷/功能性应用/数据驱动/高通量策略/机器学习Key words
high-entropy ceramics/functional application/data drive/high-throughput strategies/machine learning分类
金属材料引用本文复制引用
张勇,朱祥涵..高熵陶瓷的功能性应用和数据驱动设计[J].四川师范大学学报（自然科学版）,2025,48(3):285-311,27.基金项目
中国创新群体基金(51921001) （51921001）
