From atoms to fabs, simulated.
VDLab develops multiscale, multiphysics simulation and AI to resolve plasma–material interactions across the full semiconductor manufacturing stack.
A computational lab bridging quantum to continuum.
We resolve plasma–surface interactions at the atomic level and bridge them to process-, reactor-, and equipment-scale models — pairing machine-learning force fields and multiphysics simulation with AI-driven digital twins to accelerate etching, deposition, and materials design for semiconductor manufacturing.
Three areas, one platform
Physical AI & Digital Twin
Physics-informed virtual process platforms for real-time evaluation and predictive control.
Multiscale / Multiphysics Simulation
Quantum-to-continuum modeling of plasma-surface interaction with MLFF and molecular dynamics.
Data-Driven Materials Modeling
ALD/CVD and next-gen materials, accelerated with deep learning.
★Featured output
Polyaniline as an integrated amine-redox platform for energy-efficient PFAS remediation
Sunghoon Doh, Sangmin Eom, Byungjo Kim*, et al.
In-Situ Post-Doping Plasma Process during ALD of Al-Doped TiO₂
Gyuha Lee, Youngmin Sunwoo, Byungjo Kim*, et al.
Deep neural network-based reduced-order modeling of ion–surface interactions
Byungjo Kim*, Jinkyu Bae, et al.
Selected news
2026.05.07 ★ 신진학술상 — 대한기계학회 CAE·응용역학부문 2025.12.22 New paper — Environmental Science & Technology 2025.09.17 New paper — Int. J. of Extreme Manufacturing 2025.09.09 ★ 한-일 공동연구 — World models in AI 선정 (NRF) 2025.08.27 ★ 개인기초연구 국가아젠다 — Physical AI 선정 (NRF) 2024.12.14 ★ NVIDIA Academic Grant Program 수상Recruiting researchers in materials, mechanics & AI.
Contact Byungjo Kim for postdoc and graduate positions at the quantum–continuum interface.