Understanding the fundamental link between structure and functionalization is crucial for designing and optimizing functional materials, since different structural configurations could trigger materials to demonstrate diverse physical and chemical properties. However, the correlation between crystal structure and thermal conductivity (κ) remains unclear. In this study, taking two-dimensional (2D) carbon allotropes Janus-graphene and graphene as study cases, we utilize phonon Boltzmann transport equation combined with machine learning potential to thoroughly investigate the complex folding structure of pure sp2 hybridized Janus-graphene from the perspective of crystal structure, phonon modal resolved thermal transport, and atomic interactions, with the goal of identifying the underlying relationship between 2D geometry and κ. The results reveal that the folded structure in Janus-graphene causes strong symmetry breaking, significantly reduces phonon group velocities, increases phonon–phonon scattering, and ultimately leads to low κ. These findings enhance our understanding of how atomic structure folding affects thermal transport and the relationship between structure and functionalization.

中文翻译：

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通过机器学习力常势揭示 Janus-石墨烯中不对称结构与低热导率之间的相关性


了解结构和功能化之间的基本联系对于设计和优化功能材料至关重要，因为不同的结构配置可以触发材料表现出不同的物理和化学特性。然而，晶体结构和热导率 （κ） 之间的相关性仍不清楚。在本研究中，以二维 （2D） 碳同素异形体 Janus-graphene 和石墨烯为研究案例，我们利用声子玻尔兹曼输运方程结合机器学习潜力，从晶体结构、声子模态分辨热输运和原子相互作用的角度深入研究纯 sp2 杂化 Janus-石墨烯的复杂折叠结构，目的是确定二维几何和 κ 之间的潜在关系。结果表明，Janus-石墨烯中的折叠结构导致强对称性破坏，显著降低声子群速度，增加声子-声子散射，最终导致低 κ。这些发现增强了我们对原子结构折叠如何影响热传输以及结构与功能化之间关系的理解。