Poly(Ionic Liquid) matrices embedded with liquid metal particles: A versatile solution for high-power density thermal management

材料科学 离子液体 热的 复合材料 液态金属 金属 电子设备和系统的热管理 功率密度 功率(物理) 化学工程 热力学 机械工程 冶金 催化作用 有机化学 化学 工程类 物理
作者
Jianhui Zeng,Taoying Rao,Ting Liang,Yimin Yao,Chaoyang Wang,Jianbin Xu,Liejun Li,Rong Sun
出处
期刊:Composites Part A-applied Science and Manufacturing [Elsevier BV]
卷期号:199: 109221-109221 被引量:1
标识
DOI:10.1016/j.compositesa.2025.109221
摘要

• A flexible poly(ionic liquid) is used as the TIM matrix. • Liquid metals can be blended within poly(ionic liquid)s at high filler ratios. • PIL/LM composites have excellent properties needed for TIM. • PIL/LM TIM exhibits ultra-low thermal resistance and high thermal conductivity. Amid the global surge in generative AI and the resulting compute revolution, thermal management has emerged to be a pivotal determinant of its success. Innovation in thermal interface materials (TIMs) now represents a strategic frontier in shaping the trajectory of the Fourth Industrial Revolution. Conventional silicone-based TIMs face a performance dilemma comprising thermal cycling-induced interfacial delamination, aging-related increases in interfacial thermal resistance. Building on previous work that introduced poly(ionic liquid)s (PILs) as a novel alternative to silicones, this study further optimizes the molecular structure of PILs. Incorporation of ethoxy groups significantly enhances the mechanical compliance of PIL while maintaining high adhesion strength. Robust hydrogen bonding between ethoxy groups in PIL and liquid metal enables a high loading of 82 vol% without leakage, achieving a thermal conductivity of nearly 5 W m −1 K −1 . Meanwhile, strong interfacial adhesion yields a interface contact thermal resistance of 0.74 ± 0.12 × 10 -6 m 2 ·K/W between the PIL/LM composite and Si, lower than that of silicone-based TIMs. The noncovalent self-healing of the PIL matrix effectively prevents crack formation in TIMs during aging. This work advances the application of PILs in TIMs and provides strategies for performance optimization, paving the way for their practical deployment as viable matrix alternatives.
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