基于对称性适配视角的准一维系统热输运的分子动力学模态分析

中文摘要 AI 辅助

对从分子动力学（MD）轨迹获得的热导率结果的详细分析通常依赖于系统的简谐振动模式知识，Green-Kubo模态分析（GKMA）和均匀非平衡模态分析（HNEMA）等方法就是如此。这种方法存在若干缺点，在处理纳米结构时尤为突出，其中最主要的是可扩展性，其次是由共同平移波数k定义的大振动子空间的简并性带来的模糊性。我们为准一维（quasi-1D）系统提出了一种替代方案：我们从线群投影算子构建用于热导率分解的模态基，使得每个投影分量都带有明确定义的对称标签（包括旋转信息和宇称），并且该分解在不可约表示（irreps）层面是唯一的。将该思路应用于由神经进化势（NEP）描述的（10,0）-（20,0）WS2-MoS2双壁纳米管（DWNT），我们发现在300 K下，HNEMA和GKMA均产生统计上一致的总电导率，并且能够识别出若干显著的对称性适配传导通道。GKMA对矩阵显示，块内和同通道跨k项占总电导率的75.6%，而跨通道相关性贡献24.4%。

英文摘要

Detailed analysis of thermal conductivity results obtained from molecular dynamics (MD) trajectories conventionally relies on knowledge of the harmonic vibrational modes of the system. This is the case in methods like Green-Kubo modal analysis (GKMA) and homogeneous nonequilibrium modal analysis (HNEMA). However, arbitrary mixing within degenerate phonon subspaces makes individual modal contributions basis dependent and can obscure their symmetry character. We propose an alternative for quasi-one-dimensional (quasi-1D) systems: we construct the modal basis for the decomposition of the thermal conductivity from line-group projection operators, so that every projected component carries well-defined symmetry labels (including rotational information and parities) and the decomposition is unique at the level of irreducible representations (irreps). Applying the idea to a (10, 0)-(20, 0) WS2-MoS2 double-walled nanotube (DWNT) described by a neuroevolution potential (NEP), we find that at 300 K both HNEMA and GKMA yield statistically consistent total conductivities and allow the identification of several prominent symmetry-adapted conduction channels. The GKMA pair matrix shows that within-block and same-channel cross-k terms account for 75.6% of the total conductivity, while cross-channel correlations contribute 24.4%.

发表机构

• TU Wien（维也纳工业大学）
• Institute of Materials Chemistry, TU Wien（维也纳工业大学材料化学研究所）
• Instituto de Nanociencia y Materiales de Aragón, CSIC-Universidad de Zaragoza（阿拉贡纳米科学与材料研究所，西班牙科学研究中心-萨拉戈萨大学）

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