QUANTUM-TO-DEVICE MODELLING LAB
Introduction
Our research group is also focused on computational models for materials, then combining those materials with experimental characterization to help design new materials and devices. Specifically, our expertise lies in predictive modeling of materials at multiple length and time scales ranging from quantum to meso-scale. We use wide range of state-of-the-art methods such as ab initio electronic structure calculations, density functional theory (DFT), time-dependent DFT (TDDFT), complete active space self-consistent field (CASSCF), and quantum Monte Carlo (QMC) techniques for capturing complex electronic correlations. We also employ classical and ab initio molecular dynamics (MD and AIMD), coarse-grained simulation methods, advanced sampling techniques, and development of materials models using machine learning methods.