Professor
Short Bio
Seoul National University, Korea, B.S. Physics, Spring 1993
Seoul National University, Korea, M.S. Physics, Spring 1995
Seoul National University, Korea, Ph.D. Physics, Summer 2000
Postdoctor, Center for Strongly Correlated Materials Research, Seoul National University, 2000-2001
Postdoctor, Princeton Materials Institute, Princeton University, 2001-2003
Full-time lecturer, Dept. of Physics, Ewha Womans University, 2003-2004
Assistant Professor, Dept. of Physics, Ewha Womans University, 2004-2008
Associate Professor, Dept. of Physics, Ewha Womans University, 2008-2009
Associate Professor, Dept. of Materials Science and Engineering, Seoul National University, 2009-2013
Professor, Dept. of Materials Science and Engineering, Seoul National University, 2013-
Visiting Professor, Korea Institute for Advanced Study, 2015.9-2016.8
Postdoctoral Researchers
Research Area
Neural Network Atomic Potential
Paper List
Accelerated identification of equilibrium structures of multicomponent inorganic crystals using machine learning potentials (Submitted)1st authorHigh-throughput computational design of Li superionic conductors for all-solid-state Li-ion batteries (Submitted)1st author
Metadynamics sampling in atomic environment space for collecting training data for machine learning potentials, npj Computational Materials (2021)
High-dimensional neural network atomic potentials for examining energy materials: some recent simulations, Journal of Physics: Energy (2021)
Training machine-learning potentials for crystal structure prediction using disordered structures, Physical Review B (2020)1st author
A band-gap database for semiconducting inorganic materials calculated with hybrid functional, Scientific Data (2020)
Efficient atomic-resolution uncertainty estimation for neural network potentials using a replica ensemble, The Journal of Physical Chemistry Letters (2020)1st author
Crystallization of amorphous GeTe simulated by neural network potential addressing medium-range order, Computational Materials Science (2020)
Atomic energy mapping of neural network potential, Physical Review Materials (2019)1st author
SIMPLE-NN: an efficient package for training and executing neural-network interatomic potentials, Computer Physics Communications (2019)
Towards reliable and transferable machine learning potentials: uniform training by overcoming sampling bias, Journal of Physical Chemistry C (2018)1st author
Structural effect on the oxygen evolution reaction in the electrochemical catalyst FePt, New Physics: Sae Mulli (2015)1st author
Ph.D candidates
Research Area
First principles calculation on amorphous non-volatile memory materials
Paper List
Suppression of metal-to-insulator transition using strong interfacial coupling at cubic and orthorhombic perovskite oxide heterointerfaces, Nanoscale (2021)Training machine-learning potentials for crystal structure prediction using disordered structures, Physical Review B (2020)
Crystallization of amorphous GeTe simulated by neural network potential addressing medium-range order, Computational Materials Science (2020)1st author
First-principles calculations on effects of Al and Ga dopants on atomic and electronic structures of amorphous Ge2Sb2Te5, Journal of Applied Physics (2019)
First-principles study on the negative-U behavior of K centers in amorphous Si3N4-x, Physical Review Applied (2018)
Research Area
Electrochemical catalysts
Quantum dots
Crystal structure prediction
Paper List
Accelerated identification of equilibrium structures of multicomponent inorganic crystals using machine learning potentials (Submitted)1st authorObservation of the back-donation π-bonding states near Fermi level with APRES (Submitted)
First-principles calculations of luminescence spectra of real-scale quantum dots, ACS Materials Au (2021)1st author
Vertically aligned MoS2 thin film catalysts with Fe-Ni sulfide nanoparticles by one-step sulfurization for efficient solar water reduction, Chemical Engineering Journal (2021)
Identification of active sites for CO2 reduction on graphene-supported single-atom catalysts, ChemSusChem (2021)
Density functional theory study of edge-induced atomic scale structural phase transitions of MoS2 nanocrystals: implications for a high-performance catalyst , ACS Applied Nano Materials (2021)
Production of C, N alternating two-dimensional materials using covalent modification and their electroluminescence performance, Small Science (2021)
Training machine-learning potentials for crystal structure prediction using disordered structures, Physical Review B (2020)1st author
Computational identification of transition-metal dichalcogenides for electrochemical CO2 reduction to highly reduced species beyond CO and HCOOH, The Journal of Physical Chemistry C (2020)1st author
Adatom doping of transition metals in ReSe2 nanosheets for enhanced electrocatalytic hydrogen evolution reaction, ACS Nano (2020)
Fundamental limit of the emission linewidths of quantum dots: an ab initio study of CdSe nanocrystals, ACS Applied Materials & Interfaces (2020)1st author
Anion extraction-induced polymorph control of transition metal dichalcogenides, Nano Letters (2019)1st author
Boosting the photocatalytic hydrogen evolution performance via an atomically thin 2D heterojunction visualized by scanning photoelectrochemical microscopy, Nano Energy (2019)
Influence of Bi doping on physical properties of lead halide perovskites: a comparative first-principles study between CsPbI3 and CsPbBr3, Materials Today Advances (2019)
Two-dimensional NbS2 gas sensors for selective and reversible NO2 detection at room temperature, ACS Sensors (2019)1st author
Unveiling electrochemical reaction pathways of CO2 reduction to CN species at S-vacancies of MoS2, ChemSusChem (2019)1st author
Role of hyper-reduced states in hydrogen evolution reaction at sulfur vacancy in MoS2, ACS Catalysis (2018)
Hydrogen evolution reaction at anion vacancy of two-dimensional transition metal dichalcogenides: ab initio computational screening, The Journal of Physical Chemistry Letters (2018)1st author
Directly assembled 3D molybdenum disulfide on silicon wafer for efficient photoelectrochemical water reduction, Advanced Sustainable Systems (2018)
Paper List
Training machine-learning potentials for crystal structure prediction using disordered structures, Physical Review B (2020)Computational identification of transition-metal dichalcogenides for electrochemical CO2 reduction to highly reduced species beyond CO and HCOOH, The Journal of Physical Chemistry C (2020)
Adatom doping of transition metals in ReSe2 nanosheets for enhanced electrocatalytic hydrogen evolution reaction, ACS Nano (2020)1st author
Paper List
Metadynamics sampling in atomic environment space for collecting training data for machine learning potentials, npj Computational Materials (2021)1st authorTraining machine-learning potentials for crystal structure prediction using disordered structures, Physical Review B (2020)
AMP2: a fully automated program for ab initio calculations of crystalline materials, Computer Physics Communications (2020)
Efficient atomic-resolution uncertainty estimation for neural network potentials using a replica ensemble, The Journal of Physical Chemistry Letters (2020)
Paper List
Accelerated identification of equilibrium structures of multicomponent inorganic crystals using machine learning potentials (Submitted)Training machine-learning potentials for crystal structure prediction using disordered structures, Physical Review B (2020)1st author
A band-gap database for semiconducting inorganic materials calculated with hybrid functional, Scientific Data (2020)
AMP2: a fully automated program for ab initio calculations of crystalline materials, Computer Physics Communications (2020)
Former Ph.D. students
Eunae Cho (조은애)
Affiliation Samsung Electronics
Graduated in 2012/2
Sang Ho Jeon (전상호)
Affiliation Samsung Display
Graduated in 2012/8
Bora Lee (이보라)
Affiliation LG Chem
Graduated in 2012/8
Youngho Kang (강영호)
Affiliation Incheon National Univerisity
Graduated in 2015/8
Kye Yeop Kim (김계엽)
Affiliation Samsung Electronics
Graduated in 2017/2
Kanghoon Yim (임강훈)
Affiliation Korea Institute of Energy Research
Graduated in 2017/2
Joohee Lee (이주희)
Affiliation Samsung Display
Graduated in 2017/8
Yong Youn (윤용)
Affiliation Korea Institute of Energy Research
Graduated in 2018/8
Hochul Song (송호철)
Affiliation Samsung Display
Graduated in 2019/2
Gijae Kang (강기재)
Affiliation Samsung Electronics
Graduated in 2019/2
Kyuhyun Lee (이규현)
Affiliation Samsung Electronics
Graduated in 2019/8
Dongsun Yoo (유동선)
Affiliation Samsung Display
Graduated in 2020/2
Dongheon Lee (이동헌)
Affiliation IBS
Graduated in 2020/8
Miso Lee (이미소)
Affiliation Samsung Electronics
Graduated in 2020/8
Former M.S. student
Tae-Eun Kim (김태은)
Affiliation 천재교육
Sohee Park (박소희)
Graduated in 2012.2
Doyeon Kim (김도연)
Graduated in 2020.1
Former Post Doctors
Choongki Lee (이충기)
Affiliation Condensed Matter Physics, KIAS
Hyo-Shin Ahn (안효신)
Affiliation Samsung Electronics
Won-joon Son (손원준)
Affiliation Samsung Advanced Institue of Technology