Overview

Multiscale/Multiphysics-based modeling and simulation

Our lab is conducting researches based on computational sciences and numerical methods related with multi-scale and multi-physics, including coarse-grained calculations at scales of tens of nanometers or more, discrete modeling at scales of several nanometers (i.e., Monte Carlo (MC) and molecular dynamics (MD) simulation), and quantum level calculations (i.e., ab initio and density functional theory (DFT)) at 1 nanometer scale. In addition to the continuum theory-based transport phenomena modelling, as computational photonics methodologies, we can design and optimize optical/electrical devices and materials using a variety tools such as 3D finite difference time domain (3D FDTD), discrete/coupled dipole approximation (DDA/CDA), rigorous-coupled wave approximation (RCWA), Monte Carlo ray tracing (MCRT), boundary element modeling (BEM), scattering/transfer matrix method (SMM/TMM). 

Statistical physics-based material design and analysis

Every materials and phenomena have their intrinsic information. These information can be represented as material properties (i.e., electronic, magnetic, or optical properties) or pattern formation (e.g., pattern formation during phase transition and reactions). For example, unique patterns (i.e., uniform, stripe, and triangular phase) are observed during the grain formation in phase crystal model, which is a function of density and temperature. Unfortunately, these data are often treated and examined in a qualitative manner because they have a variety of forms (i.e., 1D signals, 2D images, and 3D structures), making them hard to be interpreted. To address this, we reveal and examine the underlying nature of the material properties and phenomena quantitatively based on statistical physics (i.e., order parameter and fractal analysis) and information theory-based methodologies (i.e., information entropy).