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基于三维垂直排列氮化硼网络的聚合物复合材料的壁密度控制热导率和力学性能

Wall Density-Controlled Thermal Conductive and Mechanical Properties of Three-Dimensional Vertically Aligned Boron Nitride Network-Based Polymeric Composites.

作者信息

Jiang Fang, Song Na, Ouyang Runhai, Ding Peng

机构信息

School of Materials Science and Engineering, Shanghai University, 99 Shangda Road, Shanghai 200444, PR China.

Research Center of Nanoscience and Nanotechnology, Shanghai University, 99 Shangda Road, Shanghai 200444, PR China.

出版信息

ACS Appl Mater Interfaces. 2021 Feb 17;13(6):7556-7566. doi: 10.1021/acsami.0c22702. Epub 2021 Feb 2.

DOI:10.1021/acsami.0c22702
PMID:33528995
Abstract

Polymeric composites with good thermal conductive and improved mechanical properties are in high demand in the thermal management materials. Construction of a three-dimensional (3D) structure has been proved to be an effective method to obtain polymeric composites with improved through-plane thermal conductivity (TC) for efficient thermal management of electronics. However, the TC enhancement of the obtained polymeric composites is limited, mainly due to poor control of the 3D thermal conductive network. Additionally, achieving high thermal conductive properties and enhanced mechanical properties simultaneously is of great challenge for polymeric composites. In this work, a 3D boron nitride framework (BNF) with a well-defined vertically aligned open structure and designed wall density fabricated by a unidirectional freezing technique was applied. The as-prepared BNF/polyethylene glycol (PBNF) composites exhibit enhanced through-plane TC, excellent thermal transfer capability (Δ = 34 °C), and improved mechanical properties (Young's modulus enhancement up to 356%) simultaneously, making it attractive to thermal management applications. Strong correlation between the TC and mechanical properties of the PBNF composites and the wall density of the BNF scaffolds was found, providing opportunities to tune the TC and mechanical properties through the controlling of wall density. Furthermore, the models between TC and Young's modulus of PBNF composites were established by using the data-driven method "sure independence screening and sparsifying operator", which enables us to predict TC and Young's modulus of the polymeric composites for designing promising composite materials. The design principles and fabrication strategies proposed in this work could be important for developing advanced composite materials.

摘要

具有良好导热性和改善机械性能的聚合物复合材料在热管理材料中需求旺盛。构建三维(3D)结构已被证明是获得具有改善的面内热导率(TC)的聚合物复合材料以实现电子器件高效热管理的有效方法。然而,所获得的聚合物复合材料的热导率增强有限,主要是由于对3D导热网络的控制不佳。此外,同时实现高导热性能和增强的机械性能对聚合物复合材料来说是巨大的挑战。在这项工作中,应用了通过单向冷冻技术制造的具有明确垂直排列开放结构和设计壁密度的3D氮化硼骨架(BNF)。所制备的BNF/聚乙二醇(PBNF)复合材料同时表现出增强的面内热导率、优异的热传递能力(Δ = 34°C)和改善的机械性能(杨氏模量增强高达356%),使其对热管理应用具有吸引力。发现PBNF复合材料的热导率与机械性能以及BNF支架的壁密度之间存在强相关性,这为通过控制壁密度来调节热导率和机械性能提供了机会。此外,通过使用数据驱动方法“确定独立筛选和稀疏化算子”建立了PBNF复合材料的热导率与杨氏模量之间的模型,这使我们能够预测聚合物复合材料的热导率和杨氏模量以设计有前景的复合材料。这项工作中提出的设计原则和制造策略对于开发先进复合材料可能很重要。

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