The Study on Thermal Conductivity of Perfect and Defective Silicon Carbide Nanofilms and the Influence of Phonon Transport Behavior Using Non-Equilibrium Molecular Dynamics

Abstract

This study mainly uses non-equilibrium molecular dynamics simulation methods to investigate the temperature and scale effects of silicon carbide in different nano-scale films and compare the differences in thermal conductivity after adding defect scattering mechanisms Using the phonon transmission behavior of silicon carbide nanofilms under different initial conditions the reason for its heat transfer effect is discussed We establish a model of the perfect molecular crystal structure of the silicon carbide thin film under the simulation of the ideal silicon carbide thin film and directly change its thickness and temperature to observe the change of its thermal conductivity with the thickness and temperature and use the phonon coherence to observe the phonon whether the vibration modes of the two regions are similar which reflects the situation of phonon transmission The higher the phonon coherence the less the phonon scattering between the two regions and the more complete the energy transferred by the phonon Among them the greater the coherence of low-frequency phonons the greater the thermal conductivity In establishing the defect film model the defect rate of the overall model is first changed In the case of fixed film thickness molecules with different defect ratios are removed by randomly selecting molecules to simulate the silicon carbide film under real experimental conditions Under the condition of imperfect structure we change its thickness and temperature under the model of defected silicon carbide thin film observe the comparison of its thermal conductivity with perfect silicon carbide thin film and discuss the phonon coherence changes under the influence of defect scattering mechanism This result discusses the possible causes that affect the thermal conductivity in various situations

Date of Award	2020
Original language	English
Supervisor	Alex Chang-Da Wen (Supervisor)