Revealing the correlation between asymmetric structure and low thermal conductivity in Janus-graphene via machine learning force constant potential

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.