Lattice Thermal Conductivity of Janus WXY (X, Y = S, Se, Te) Monolayers: A Machine-Learning Based Study

Shengxiang Liu, Jingfeng Wang, Zihe Li, Wenyan Jiao, Fuyun Lv, Huijun Liu

Due to their unique structures, intriguing electronic properties, and potential applications across various fields, Janus materials have attracted extensive attention from the science community. However, the thermal transport properties of Janus systems are less known so far, especially regarding lattice thermal conductivity (LTC). In this work, we establish an accurate machine learning potential by which the phonon Boltzmann transport equation can be iteratively solved to readily predict the LTC of Janus WXY (X, Y = S, Se, Te) monolayers. It is found that the LTC for all three systems decreases monotonically with increasing temperature. Among them, the WTeSe monolayer exhibits the lowest LTC, which can be traced back to the competition between the contributions of phonon group velocity and relaxation time. Interestingly, we demonstrate that the effect of four phonon scattering plays an important role in accurately determining the LTC of these Janus monolayers. Our work also provides an alternative way of effectively predicting the LTC of systems with low symmetry and/or large size.