机器学习辅助理解化石墨烯层厚度依赖的导热率
Jun-Nan Liang1, Hua Tong1, Yu-Jia Zeng1
1School of Materials Science and Engineering, Hunan University of Science and Technology, Xiangtan 411201, People's Republic of China.
概括
化石墨烯是一种化石墨烯.
科学领域:
- 材料科学 材料科学 材料科学
- 凝聚物质物理学 凝聚物质物理学
- 纳米技术 纳米技术
背景情况:
- 导热率 (κ) 操纵对于热电,绝缘和热管理应用至关重要.
- 化石墨烯 (FG) 是这些应用的一个有前途的材料.
研究的目的:
- 系统地研究化石墨烯 (FG) 层厚度依赖的导热率 (κ).
- 了解影响FG中k的底层声子散射机制.
主要方法:
- 利用基于机器学习的原子间潜力进行精确的材料模拟.
- 使用声子博尔兹曼传输方程来计算导热率.
- 分析了晶体对称性对声子传输的影响.
主要成果:
- FG的晶格导热率 (κ) 在伯纳尔双层堆叠时显著下降.
- 两层之外的进一步增加的层不会影响 κ,但散装配置显示 κ增加.
- 从P-3m1 (单层) 到P3m1 (多层) 的晶体对称性变化是观察到 κ 变化的原因.
- 声学模式对 κ 的贡献随着层次的增加而减少,而光学模式的贡献则增加.
结论:
- 该研究揭示了FG层厚度和导热性之间的非单调关系.
- 晶体对称性和声子散射机制是FG中热传输的关键因素.
- 结果为设计具有量身定制的热性能的基于FG的材料提供了洞察力.
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