Kwang Soo Kim

Professor, Director

Korea Advanced Institute of Science and Technology

South Korea

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About

Professor Kwang Soo Kim is the Director at Ulsan National Institute of Science and Technology in South Korea. His research areas include materials discovery, machine learning applications in catalysis, and the development of advanced electrochemical systems. Recent publications highlight his work on single-atom catalysts, materials simulations, and innovative approaches to CO2 reduction and nitrogen fixation.

Articles (18)

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SOUTH KOREA

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Hyung-Joon Shin

Professor

Korea Advanced Institute of Science and Technology

SOUTH KOREA

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Kwang Soo Kim

Research Interests

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Articles (18)

Unlocking the catalytic potential of iMXenes: selective electrochemical CO2 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

Active sparse Bayesian committee machine potential for isothermal–isobaric molecular dynamics simulations

Progress in Single/Multi Atoms and 2D‐Nanomaterials for Electro/Photocatalytic Nitrogen Reduction: Experimental, Computational and Machine Leaning Developments

Single-atom catalysts supported on a hybrid structure of boron nitride/graphene for efficient nitrogen fixation via synergistic interfacial interactions

Sparse Gaussian process based machine learning first principles potentials for materials simulations: Application to batteries, solar cells, catalysts, and macromolecular systems

Dual Interface Passivation in Mixed-Halide Perovskite Solar Cells by Bilateral Amine

High‐Performing Atomic Electrocatalyst for Chlorine Evolution Reaction

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

Al‐Doping Driven Suppression of Capacity and Voltage Fadings in 4d‐Element Containing Li‐Ion‐Battery Cathode Materials: Machine Learning and Density Functional Theory

Challenges, Opportunities, and Prospects in Metal Halide Perovskites from Theoretical and Machine Learning Perspectives

Ir and NHC Dual Chiral Synergetic Catalysis: Mechanism and Stereoselectivity in γ-Butyrolactone Formation

Fast atomic structure optimization with on-the-fly sparse Gaussian process potentials *

Unveiling the Role of Charge Transfer in Enhanced Electrochemical Nitrogen Fixation at Single-Atom Catalysts on BX Sheets (X = As, P, Sb)

Sparse Gaussian Process Regression-Based Machine Learned First-Principles Force-Fields for Saturated, Olefinic, and Aromatic Hydrocarbons

C60 Adsorbed on TiO2 Drives Dark Generation of Hydroxyl Radicals

Collaborators (8)

Dong Yeon Kim

Chang Woo Myung

ADITYA NARAYAN SINGH

Jung Woon Yang

Soohaeng Willow

Rohit Anand

Saeed Pourasad

Hyung-Joon Shin

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