{"title":"Biomimetic Intelligent Thermal Management Materials: From Nature-Inspired Design to Machine-Learning-Driven Discovery.","authors":"Heng Zhang,Qingxia He,Fei Zhang,Yanshuai Duan,Mengmeng Qin,Wei Feng","doi":"10.1002/adma.202503140","DOIUrl":null,"url":null,"abstract":"The development of biomimetic intelligent thermal management materials (BITMs) is essential for tackling thermal management challenges in electronics and aerospace applications. These materials possess not only exceptional thermal conductivity but also environmental compatibility. However, developing such materials necessitates overcoming intricate challenges, such as precise control over the material structure and optimization of the material's properties and stability. This review comprehensively overviews the research progress of BITMs, emphasizing the synergy between biomimetic design principles and artificial-intelligence-driven methodologies to enhance their performance. The unique nature-inspired structures are explored and valuable insights are provided into adaptive thermal management strategies, which can be further enhanced through data analytics and machine learning (ML). This review offers insights into overcoming design challenges and outlines future prospects for advanced BITMs by integrating ML and biomimetic design principles.","PeriodicalId":114,"journal":{"name":"Advanced Materials","volume":"141 1","pages":"e2503140"},"PeriodicalIF":27.4000,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Materials","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1002/adma.202503140","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
The development of biomimetic intelligent thermal management materials (BITMs) is essential for tackling thermal management challenges in electronics and aerospace applications. These materials possess not only exceptional thermal conductivity but also environmental compatibility. However, developing such materials necessitates overcoming intricate challenges, such as precise control over the material structure and optimization of the material's properties and stability. This review comprehensively overviews the research progress of BITMs, emphasizing the synergy between biomimetic design principles and artificial-intelligence-driven methodologies to enhance their performance. The unique nature-inspired structures are explored and valuable insights are provided into adaptive thermal management strategies, which can be further enhanced through data analytics and machine learning (ML). This review offers insights into overcoming design challenges and outlines future prospects for advanced BITMs by integrating ML and biomimetic design principles.
期刊介绍:
Advanced Materials, one of the world's most prestigious journals and the foundation of the Advanced portfolio, is the home of choice for best-in-class materials science for more than 30 years. Following this fast-growing and interdisciplinary field, we are considering and publishing the most important discoveries on any and all materials from materials scientists, chemists, physicists, engineers as well as health and life scientists and bringing you the latest results and trends in modern materials-related research every week.