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Changwoo Myung

Sungkyunkwan University · Materials Science

About the Lab

Professor Changwoo Myung's research lab specializes in computational materials science and catalysis, focusing on the design and optimization of advanced materials for sustainable energy applications. The lab employs high-throughput first-principles calculations and machine learning to explore electrocatalysts for water splitting, ion diffusion and redox mechanisms in high-energy battery materials, and interfacial phenomena in perovskite solar cells. Key research directions include the development of non-precious metal electrocatalysts, understanding anion redox behavior in layered oxide cathodes, and engineering electron transport layers for stable and efficient optoelectronic devices. The integration of density functional theory with advanced machine learning techniques enables predictive insights into complex materials behavior at the atomic scale.

electrocatalysisperovskite solar cellsbattery materialsmachine learningfirst-principles calculations

Research Overview

Papers
80
Total Citations
3,746
Papers (5y)
46
Primary Field
Materials Science

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
46total
2022
2023
2024
2025
2026
Citations per year (5y)
527total
20222023202420252026

Selected Papers

15
1
Article|292 citations·2021
Tuning metal single atoms embedded in NxCy moieties toward high-performance electrocatalysis
Miran Ha, Dong Yeon Kim, Muhammad Umer, Vladislav Gladkikh, Chang Woo Myung, Kwang S. Kim
SJR Q1Energy & Environmental ScienceOA

High-performance 3d–5d transition metal single atom electrocatalysts ligated by various –N<sub>x</sub>C<sub>y</sub> moieties of N-doped graphene are investigated for hydrogen evolution and oxygen evolution/reduction reactions using high-throughput computational screening and machine learning.

Renewable Energy, Sustainability and the EnvironmentEnergy
2
Article|182 citations·2019
Superb water splitting activity of the electrocatalyst Fe3Co(PO4)4 designed with computation aid
Siraj Sultan, Miran Ha, Dong Yeon Kim, Jitendra N. Tiwari, Chang Woo Myung, Abhishek Meena, Tae Joo Shin, Keun Hwa Chae, Kwang S. Kim
SJR Q1Nature CommunicationsOA

Abstract For efficient water splitting, it is essential to develop inexpensive and super-efficient electrocatalysts for the oxygen evolution reaction (OER). Herein, we report a phosphate-based electrocatalyst [Fe 3 Co(PO 4 ) 4 @reduced-graphene-oxide(rGO)] showing outstanding OER performance (much higher than state-of-the-art Ir/C catalysts), the design of which was aided by first-principles calculations. This electrocatalyst displays low overpotential (237 mV at high current density 100 mA cm −

Renewable Energy, Sustainability and the EnvironmentEnergy
3
Article|135 citations·2020
Immiscible bi-metal single-atoms driven synthesis of electrocatalysts having superb mass-activity and durability
Ahmad M. Harzandi, Sahar Shadman, Miran Ha, Chang Woo Myung, Dong Yeon Kim, Hyo Ju Park, Siraj Sultan, Woo‐Suk Noh, Wang‐Geun Lee, Pandiarajan Thangavel, Woo Jin Byun, Seong‐Hun Lee
SJR Q1Applied Catalysis B: EnvironmentalOA
Renewable Energy, Sustainability and the EnvironmentEnergy
4
Article|102 citations·2022
Al‐Doping Driven Suppression of Capacity and Voltage Fadings in 4d‐Element Containing Li‐Ion‐Battery Cathode Materials: Machine Learning and Density Functional Theory
Miran Ha, Amir Hajibabaei, Dong Yeon Kim, Aditya Narayan Singh, Jeonghun Yun, Chang Woo Myung, Kwang S. Kim
SJR Q1Advanced Energy Materials

Abstract The anion redox reaction in high‐energy‐density cathode materials such as Li‐excess layered oxides suffers from voltage/capacity fadings due to irreversible structural instability. Here, exploiting density functional theory (DFT) as well as fast simulations using the universal potential/forces generated from the newly developed sparse Gaussian process regression (SGPR) machine learning (ML) method, the very complicated/complex structures, X‐ray absorption near‐edge‐structure (XANES) spe

Electrical and Electronic EngineeringEngineering
5
Article|84 citations·2020
Efficient electron extraction of SnO2 electron transport layer for lead halide perovskite solar cell
Junu Kim, Kwang S. Kim, Chang Woo Myung
SJR Q1npj Computational MaterialsOA

Abstract SnO 2 electron transport layer (ETL) has been spotlighted with its excellent electron extraction and stability over TiO 2 ETL for perovskite solar cells (PSCs), rapidly approaching the highest power conversion efficiency. Thus, how to boost the performance of ETL is of utmost importance and of urgent need in developing more efficient PSCs. Here we elucidate the atomistic origin of efficient electron extraction and long stability of SnO 2 -based PSCs through the analysis of band alignmen

Electrical and Electronic EngineeringEngineering
6
Article|52 citations·2018
La-doped BaSnO3 electron transport layer for perovskite solar cells
Chang Woo Myung, Geunsik Lee, Kwang S. Kim
SJR Q1Journal of Materials Chemistry A

Recently, La-doped BaSnO<sub>3</sub> (LBSO) electron transport layer for perovskite solar cells has been introduced to replace TiO<sub>2</sub> which is susceptible to UV light. This paper unveils the key mechanism for the ideal band alignment between LBSO and MAPbI<sub>3</sub>. The amount of La dopant in LBSO is crucial for the fine tuning of the conduction band level of LBSO.

Materials ChemistryMaterials Science
7
Article|51 citations·2022
Challenges, Opportunities, and Prospects in Metal Halide Perovskites from Theoretical and Machine Learning Perspectives
Chang Woo Myung, Amir Hajibabaei, Ji‐Hyun Cha, Miran Ha, Junu Kim, Kwang S. Kim
SJR Q1Advanced Energy Materials

Abstract Metal halide perovskite (MHP) is a promising next generation energy material for various applications, such as solar cells, light emitting diodes, lasers, sensors, and transistors. MHPs show excellent mechanical, dielectric, photovoltaic, photoluminescence, and electronic properties, and such intriguing physical and chemical properties have drawn attention recently. However, there exists a chasm between the successful applications of MHPs and theoretical understandings. The difficulty a

Materials ChemistryMaterials Science
8
Article|34 citations·2022
Prediction of a Supersolid Phase in High-Pressure Deuterium
Chang Woo Myung, Barak Hirshberg, Michele Parrinello
SJR Q1Physical Review LettersOA

Supersolid is a mysterious and puzzling state of matter whose possible existence has stirred a vigorous debate among physicists for over 60 years. Its elusive nature stems from the coexistence of two seemingly contradicting properties, long-range order and superfluidity. We report computational evidence of a supersolid phase of deuterium under high pressure (p>800 GPa) and low temperature (T<1.0 K). In our simulations, that are based on bosonic path integral molecular dynamics, we observe a high

Atomic and Molecular Physics, and OpticsPhysics and Astronomy
9
Article|11 citations·2024
Active sparse Bayesian committee machine potential for isothermal–isobaric molecular dynamics simulations
Soohaeng Yoo Willow, Dong Geon Kim, R. Sundheep, Amir Hajibabaei, Kwang S. Kim, Chang Woo Myung
SJR Q2Physical Chemistry Chemical Physics

Introducing active sparse Bayesian committee machine potentials with virial kernels for enhanced pressure accuracy. This enables efficient on-the-fly training for accurate isobaric machine learning molecular dynamics simulations with reduced costs.

Materials ChemistryMaterials Science
10
Article|8 citations·2024
Going for Gold(-Standard): Attaining Coupled Cluster Accuracy in Oxide-Supported Nanoclusters
Benjamin X. Shi, David J. Wales, Angelos Michaelides, Chang Woo Myung
SJR Q1Journal of Chemical Theory and Computation

The structure of oxide-supported metal nanoclusters plays an essential role in their sharply enhanced catalytic activity over that of bulk metals. Simulations provide the atomic-scale resolution needed to understand these systems. However, the sensitive mix of metal–metal and metal–support interactions, which govern their structure, puts stringent requirements on the method used, requiring calculations beyond standard density functional theory (DFT). The method of choice is coupled cluster theor

Materials ChemistryMaterials Science
11
Article|8 citations·2024
Exploring Direct Electrochemical Fischer–Tropsch Chemistry of C1–C7 Hydrocarbons via Perimeter Engineering of Au–SrTiO3 Catalyst
Ju Yang, Gi Beom Sim, So Jeong Park, Choong Kyun Rhee, Chang Woo Myung, Youngku Sohn
SJR Q1Advanced Energy MaterialsOA

Abstract Traditionally, Fischer–Tropsch (FT) synthesis is performed using thermal catalysts and syngas (CO and H 2 ) under high‐pressure and high‐temperature conditions. However, this study introduces an approach that relies on FT chemistry assisted by electrochemistry, referred to here as direct electrochemical (EC) FT chemistry, under ambient conditions. A series of CH 4 , C n H 2n , and C n H 2n+2 hydrocarbons (n = 1–7) is successfully produced over gold (Au) nanoparticle‐loaded perovskite st

Renewable Energy, Sustainability and the EnvironmentEnergy
12
Article|7 citations·2025
Machine Learning Nonadiabatic Dynamics: Eliminating Phase Freedom of Nonadiabatic Couplings with the State-Interaction State-Averaged Spin-Restricted Ensemble-Referenced Kohn–Sham Approach
Sung Wook Moon, Soohaeng Yoo Willow, Tae Park, Seung Kyu Min, Chang Woo Myung
SJR Q1Journal of Chemical Theory and Computation

Excited-state molecular dynamics (ESMD) simulations near conical intersections (CIs) pose significant challenges when using machine learning potentials (MLPs). Although MLPs have gained recognition for their integration into mixed quantum-classical (MQC) methods, such as trajectory surface hopping (TSH), and their capacity to model correlated electron–nuclear dynamics efficiently, difficulties persist in managing nonadiabatic dynamics. Specifically, singularities at CIs and double-valued couplin

Materials ChemistryMaterials Science
13
Article|2 citations·2020
Anharmonicity‐Driven Rashba Cohelical Excitons Break Quantum Efficiency Limitation
Chang Woo Myung, Kwang S. Kim
SJR Q1Advanced MaterialsOA

Abstract Closed‐shell light‐emitting diodes (LEDs) suffer from the internal quantum efficiency (IQE) limitation imposed by optically inactive triplet excitons. Here, an unrevealed emission mechanism of lead halide perovskites (LHPs) APbX 3 (A = Cs/CN 2 H 5 ; X = Cl/Br/I) that circumvents the efficiency limit of closed‐shell LEDs is explored. Though efficient emission is prohibited by optically inactive J = 0 in inversion symmetric LHPs, the anharmonicity arising from stereochemistry of Pb and re

Electrical and Electronic EngineeringEngineering
14
Article|2 citations·2025
Synergistic Fe–Si Dual‐Site Pathway Engineering in Biomass‐Derived Carbon Matrix for High‐Performance Oxygen Reduction Reaction
Min Su Cho, Yanmei Zang, S. Park, Byeong‐Seon An, Ho Jin Lee, Ashishi Gaur, Ghulam Muhammad Ali, Mingony Kim, K. D. Chung, SungBin Park, Yung‐Eun Sung, Daehae Kim
SJR Q1Carbon EnergyOA

ABSTRACT Anion exchange membrane fuel cells (AEMFCs) offer a sustainable energy solution with non‐precious metal catalysts, reduced degradation, and fuel flexibility. However, the sluggish oxygen reduction reaction (ORR) at the cathode and durability concerns impede commercialization. To address these challenges, this study presents a dual‐atomic SiFe–N–C catalyst derived from pinecones, a naturally abundant biomass resource. The catalyst features a nitrogen‐rich porous carbon matrix that stabil

Renewable Energy, Sustainability and the EnvironmentEnergy
15
Article|1 citations·2025
Temperature-independent emission in a [(CH3)3NPh]2MnBr4 single crystal analogous to thermally activated delayed fluorescence
Mutibah Alanazi, Atanu Jana, Won Woong Choi, D. ChangMo Yang, Robert A. Taylor, Chang Woo Myung, Young S. Park
SJR Q1Applied Materials Today
Electrical and Electronic EngineeringEngineering

Research Areas

Materials ChemistryRenewable Energy, Sustainability and the EnvironmentElectrical and Electronic EngineeringAtomic and Molecular Physics, and OpticsControl and Systems EngineeringStructural Biology

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