Area of research
Atomic and Molecular Physics, and Optics · Materials Chemistry
Research interest
1996. 3 ~ 1999. 2 Teaching and Research Assistant, Dept EE, KAIST, Daejeon, Korea 1999. 3 ~ 2000. 3 Postdoc researcher, Dept ECE, UC San Diego, La Jolla, U.S.A. 2000. 4 ~ 2004. 2 Senior member of research staff, Mobile Communication Lab., Electronics and Telecommunications Research Institute, Daejeon, Korea 2004. 3 ~ 2009. 2 Assistant Professor, School of Electrical and Electronics Engineering, Yonsei University, Seoul, Korea 2009. 3 ~ 2015. 8 Associate Professor, School of Electrical and Electronics Engineering, Yonsei University, Seoul, Korea 2015.
Accelerating Materials Discovery Through Sparse Gaussian Process Machine Learning Potentials.
Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications
Machine Learning for Accelerating Energy Materials Discovery: Bridging Quantum Accuracy with Computational Efficiency
Unlocking the catalytic potential of iMXenes: selective electrochemical CO<sub>2</sub> reduction for methane production
A sparse Bayesian Committee Machine potential for oxygen-containing organic compounds
A Quantum Compass for Materials Discovery: Navigating the Combinatorial Explosion.
Structural Order as the Key Phase Indicator in Supercooled Liquid Water
Progress in Single/Multi Atoms and 2D‐Nanomaterials for Electro/Photocatalytic Nitrogen Reduction: Experimental, Computational and Machine Leaning Developments
Sparse Gaussian process based machine learning first principles potentials for materials simulations: Application to batteries, solar cells, catalysts, and macromolecular systems
Active sparse Bayesian committee machine potential for isothermal-isobaric molecular dynamics simulations.
Single-atom catalysts supported on a hybrid structure of boron nitride/graphene for efficient nitrogen fixation <i>via</i> synergistic interfacial interactions.
Unveiling enigmatic phase transitions of water in the supercooled region and no man’s land
Unveiling enigmatic phase transitions of water in the supercooled region and no man’s land
Unveiling enigmatic phase transitions of water in the supercooled region and no man’s land
supercooled region and no man’s land in the phase diagram of water
Engineering Pt Coordination Environment with Atomically Dispersed Transition Metal Sites Toward Superior Hydrogen Evolution
Computation-aided design of oxygen-ligand-steered single-atom catalysts: Sewing unzipped carbon nanotubes
High-Performing Atomic Electrocatalyst for Chlorine Evolution Reaction.
Dual Interface Passivation in Mixed-Halide Perovskite Solar Cells by Bilateral Amine
Machine learning assisted high-throughput screening of transition metal single atom based superb hydrogen evolution electrocatalysts
Al‐Doping Driven Suppression of Capacity and Voltage Fadings in 4d‐Element Containing Li‐Ion‐Battery Cathode Materials: Machine Learning and Density Functional Theory
Doped MXene combinations as highly efficient bifunctional and multifunctional catalysts for water splitting and metal–air batteries
Challenges, Opportunities, and Prospects in Metal Halide Perovskites from Theoretical and Machine Learning Perspectives
Transition metal single atom embedded GaN monolayer surface for efficient and selective CO<sub>2</sub> electroreduction
Upconversion and multiexciton generation in organic Mn(<scp>ii</scp>) complex boost the quantum yield to > 100%
Unveiling the Role of Charge Transfer in Enhanced Electrochemical Nitrogen Fixation at Single-Atom Catalysts on BX Sheets (X = As, P, Sb).
Ir and NHC Dual Chiral Synergetic Catalysis: Mechanism and Stereoselectivity in γ-Butyrolactone Formation.
C<sub>60</sub> Adsorbed on TiO<sub>2</sub> Drives Dark Generation of Hydroxyl Radicals
Sparse Gaussian Process Regression-Based Machine Learned First-Principles Force-Fields for Saturated, Olefinic, and Aromatic Hydrocarbons.
Fast atomic structure optimization with on-the-fly sparse Gaussian process potentials.