Research Interest
2D van der Waals Transistor, Machine learning, Optoelectronic devices
Paper & Patent
“Enhanced gating efficiency in vertical mixed molecular transistors with deep orbital level”, Science Advances (2025)
“Design of Self-Assembled Monolayer in Tungsten Diselenide Bilayer for Exciton Dissociation”, ACS Nano (2025)
“A New Direction for First-Principles Device Simulations”, IEEE Nanotechnology Magazine (2024)
1st“Convolutional network learning of self-consistent electron density via grid-projected atomic fingerprints”, npj Computational Materials (2024)
“Characterizing Defects Inside Hexagonal Boron Nitride Using Random Telegraph Signals in van der Waals 2D Transistor”, ACS Nano (2024)
“High-κ Dielectric (HfO2)/2D Semiconductor (HfSe2) Gate Stack for Low-Power Steep-Switching Computing Devices”, Advanced Materials (2024)
“Ab initio theory of the nonequilibrium adsorption energy”, npj Computational Materials (2024)
"Gate-versus defect-induced voltage drop and negative differential resistance in vertical graphene heterostructures", Npj Computational Materials (2022)
1st"Optogenetics-inspired flexible van-der-Waals optoelectronic synapse and its application to a convolutional neural network", Advanced Materials (2021)
"Device Analysis System and Method for Deriving Partial Electron Density" Patent No. P2024-1167-KR01 (KR)
"Electronic Structure Modeling System Using Artificial Neural Network " Patent No. P2024-0840-KR01 (KR)
Awards
한국물리학회 봄학술대회 우수 구두발표상 (2022)
한국물리학회 가을학술대회 우수 구두발표상 (2021)
- ronggyulee@kaist.ac.kr
- 042-350-7523
- KAIST School of Electrical Engineering Bld. (E3-2) 6210
