Sungkyunkwan University Materials AI Modeling Laboratory
Materials AI Modeling Laboratory
AI-Guided DiscoveryMultiscale ModelingNucleation Theory
AI-guided discovery, multiscale simulation, and nucleation-aware process modeling for advanced materials and devices.
AI-Assisted Synthesis Recipe DesignUses literature, simulations, and experiments to prioritize testable synthesis conditions.
What we do
Computational materials science from atomic-scale mechanisms to process and device-level design.
Materials AI Modeling Laboratory combines first-principles calculations, molecular dynamics, multiscale simulation, and data-driven analysis to understand materials behavior and guide design across semiconductors, energy systems, functional devices, and manufacturing processes.
Research
Research Areas
People
Research Groups
AI
Data-driven materials discovery and synthesis recipe generation.
Multi-scale
Linked first-principles, process, and device-scale simulations.
Nucleation
Phase formation, reaction pathways, and synthesis condition design.
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