Projects : Structural
AI based supercritical materials research
As global issues emerge, exploration and development of resources and energy in extreme environments such as space, deep sea, and polar regions are actively progressing. Supercritical materials that greatly exceed the physical properties of existing materials are indispensable for stable work. However, its slow development speed and high probability of failure are blocked the progressing. Therefore, in this project, 7 promising supercritical materials that are used in the future extreme environment were selected, and an AI platform that integrates material design/manufacturing, synthesis/analysis, and evaluation is built to develop those materials in a relatively short time.END.
Completed projects
Development of machine learning model for predicting corrosion of high corrosion-resistant alloy plated steel
Alloy plating is used to prevent corrosion of steel construction materials, but it has limited lifespan under harsh environments. Through a machine learning model developed from alloy plated steel corrosion images and experimental environment data, we predict lifespan of construction materials in real marine and soil environments.
HEA-TRIP steel study with first-principle calculation
HEAs are one of promising materials with almost infinite potential in numerous combinations. However, the numerous combinations is also bottleneck of advanced research. In this project, we will screen concentrations of systems with more than 5 elements using first-principle calculation with coherent potential approximation which can deal with positional and magnetical randomness.