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以数据驱动的框架,准确预测颗粒填充复合材料的界面热阻
Xiaoxin Lu1, Jiabin Huang1, Nan Cheng2,3
1Shenzhen Institute of Advanced Electronic Materials, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518103, P. R. China.
ACS applied materials & interfaces
|September 5, 2023
概括
准确地描述聚合物复合材料的界面热阻 (ITR) 是改善热导率 (TC) 的关键. 本研究提出了一个结合模拟,机器学习和实验的框架,以精确确定ITR以获得更好的材料设计.
科学领域:
- 材料科学 材料科学 材料科学
- 聚合物复合材料 聚合物复合材料
- 热性质 热性质
背景情况:
- 界面热阻 (ITR) 阻碍了颗粒填充的聚合物复合材料的热导率 (TC).
- 准确地描述ITR对于材料设计和TC预测至关重要.
- 现有的方法缺乏对局部复合条件的全面考虑.
研究的目的:
- 开发一个强大的框架,用于在颗粒填充的聚合物复合材料中精确地确定ITR.
- 通过考虑局部热特性,使TC的准确预测成为可能.
- 为了促进热导电复合材料的高效虚拟选.
主要方法:
- 集成高通量数值模拟,机器学习和优化算法.
- 从简单的实验中提取结构和传热信息.
- 开发一个全面的ITR表征框架.
主要成果:
- 该框架准确地确定了聚合物填充器和填充器与填充器接触的ITR.
- 获得了TC预测的有效参数,超越了实验限制.
- 在预测复合材料的TC方面实现了高效率.
结论:
- 拟议的框架为复合材料中准确的ITR表征提供了一个强大的工具.
- 它通过提供必要的有效参数,使TC的精确数值预测成为可能.
- 该方法促进了用于导热复合材料设计的虚拟高通量选.
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