Investigation of heat transfer in a semicrystalline polymer by combining molecular simulation and machine learning

Abstract

In this work, molecular dynamics simulation is first utilized to explore the thermal conductivity of a semicrystalline polymer by varying crystallinity and applying stretching. The thermal conductivity exhibits a continuous rise with increasing crystallinity, which mainly comes from the crystalline phase rather than the amorphous phase, as revealed by distinguishing their respective contributions. High crystallinity improves the concentration and order degree of the crystalline phase and lowers the interface ratio, which thus improves thermal conductivity. Conversely, the thermal conductivity of the amorphous phase is nearly unchanged. By decomposition of heat flux into different transfer modes, the bonded interaction is the main contribution to heat transfer. By analyzing the vibrational density of states, the heights of three characteristic peaks are improved simultaneously with increasing crystallinity. In addition, increases in specific heat, intrinsic mean free path and group velocity of phonons can rationalize the high thermal conductivity of a semicrystalline polymer. Second, stretching improves the thermal conductivity parallel to the stretching direction, which is also contributed primarily by bonded interaction. Meanwhile, the enhancement factor of thermal conductivity decreases with increasing initial crystallinity, which is determined by the crystalline phase. Crystallinity increases significantly at low initial crystallinity. The enhanced orientation degree of chains improves the thermal conductivity of the crystalline phase. However, crystallinity first decreases and then rises at high initial crystallinity. Moreover, the enhanced thermal conductivity of the amorphous phase is comparable for different initial crystallinities, which is due to the similar orientation degree of chains. Finally, the eXtreme Gradient Boosting regression model yields a more accurate prediction of thermal conductivity parallel to the stretching direction than the linear or polynomial regression model. Meanwhile, both the crystallinity and the orientation degree of chains exhibit similar feature importance in determining the thermal conductivity of a semicrystalline polymer. In summary, this work provides a deep understanding of how crystallinity and stretching regulate the thermal conductivity of a semicrystalline polymer at the molecular scale.