MPhil Thesis Presentation
Miniaturization of the electronic devices and the pursuit of high efficiency thermoelectric materials have pushed the feature size of the semiconductor devices down to meso/nanoscale. At mesoscales, wave effect in the nanostructures have been predicted with simulations, and confirmed by experimental measurements.
To verify the existence of the wave-like phonon transport, it is important to have in-depth understanding of the pure particle-like phonon transport. The computation cost for the mesoscale problem could be formidable even for the solving the phonon Boltzmann transport equation. To speed up the calculation while maintaining the accuracy, a phonon Monte Carlo based on MFP-cumulative bulk thermal conductivity is developed. Benefiting from the linearized and steady state formulation, it is efficient and directly parallelizable. Since the input is obtainable from experiments or first principle calculations, the accuracy is guaranteed. Validated with the experimental results of the nanomeshes, the proposed method has the potential to predict the effective thermal conductivities of very complex nanostructures.
To address the wave interference in the superlattices, an Interfering Monte Carlo (IMC) is proposed recently. Integrating a hybrid interface model, IMC is applied to a realistic Si/Ge superlattices to explain the unexpected phenomena with aperiodic superlattices, and the computational results faithfully reproduce what molecular dynamics predicts. Through a series of the comparison of the computational results, it is confirmed that wave effect could be less important for the Si/Ge SLs under study.
Combining the Green-Kubo formula and the elastic wave calculation through finite difference time domain (FDTD) method to predict the pure wave-like phonon transport behavior seem to be promising. For the future study, this method is extended to 3D cases for better understanding of the pure wave-like phonon transport in nanostructures and may serve as benchmark to compare with the real experiments.
(Supervisor: Prof. Wenjing Ye)