Biomimetic Intelligent Thermal Management Materials: From Nature‐Inspired Design to Machine‐Learning‐Driven Discovery
Heng Zhang, Qingxia He, Fei Zhang, Yanshuai Duan, Mengmeng Qin, Wei Feng
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.