Computational Structural Materials Group
2023.09.01 Update
We are responsible for improving the accuracy of prediction of material properties in the field of computational materials science and accelerating development of materials. By combining the fundamental laws of physics, simulation methods over a wide range of time and spatial scales, experiments, and data science, we aim to dramatically improve the ability of prediction properties in materials using DX, and clarify a mechanisms and accelerating materials development.
Specialized Research Field
To investigate various stages of phase transformation and micorstructure formation in materials from atomic to macroscopic point of view, we perform a variety of simulation techniques such as ab initio, molecular dynamics (MD), Monte Carlo (MC) method, cluster variation method, CALPHAD method, and phase-field method, having strong collaboration with experiment.