Revisiting four-phonon scattering in WS2 monolayer with machine learning potential

Recently, the importance of the higher-order anharmonic effect on the thermal transport has been demonstrated in a few two-dimensional (2D) materials. As a member of 2D materials, the WS2 monolayer possesses excellent properties, but its higher-order phonon anharmonic effect is still unclear. As an emerging tool for atomistic simulations, the machine learning Gaussian approximation potential (GAP) has good computational speed and accuracy. In this work, the effect of the four-phonon scattering on the thermal transport properties of the WS2 monolayer is systematically investigated by combining a well-trained GAP with the Boltzmann transport equation. We find that the in-plane thermal conductivity of the WS2 monolayer decreases by 34.68% at 300 K compared to the results without considering the four-phonon scattering, which mainly originates from the strong low-frequency redistribution scattering process. The temperature-induced phonon renormalization in WS2 monolayer is investigated using the temperature-dependent effective potential method. The results show that phonon modes slightly soften with increasing temperature, and the temperature effect weakens the four-phonon scattering while hardly affect the three-phonon scattering. Our work reveals that previous studies considering only the three-phonon scattering and the temperature effect are insufficient, and the four-phonon interaction must be introduced to accurately describe the thermal transport properties of the WS2 monolayer.