Kihoon Bang

Beijing Computational Science Research Center — China

Materials Science · Physical Sciences

9h-index413citations26works3.32yr avg
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Research Topics

Machine Learning in Materials Science(16), Electrocatalysts for Energy Conversion(9), Catalytic Processes in Materials Science(7), Fuel Cells and Related Materials(4), CO2 Reduction Techniques and Catalysts(4)

Publications26 total

Simultaneous Enhancement of the Activity and Durability of the Oxygen Reduction Reaction via Pd<sub>3</sub>Mo@Pt/C Catalysts
ACS Applied Materials & Interfaces·2025· 1 cited
MaTableGPT: GPT‐Based Table Data Extractor from Materials Science Literature (Adv. Sci. 16/2025)
Advanced Science·2025Open Access
MaTableGPT: GPT‐Based Table Data Extractor from Materials Science Literature
Advanced Science·2025· 6 citedOpen Access
Enhancing Fuel Cell Durability with Heteroenergetic TaO<sub><i>x</i></sub>-Carbon Support
ACS Energy Letters·2024· 2 cited
MaTableGPT: GPT-based Table Data Extractor from Materials Science Literature
arXiv (Cornell University)·2024· 1 citedOpen Access
Inverse design for materials discovery from the multidimensional electronic density of states
Journal of Materials Chemistry A·2024· 10 citedOpen Access
Machine learning filters out efficient electrocatalysts in the massive ternary alloy space for fuel cells
Applied Catalysis B: Environmental·2023· 22 cited
Machine learning-enabled exploration of the electrochemical stability of real-scale metallic nanoparticles
Nature Communications·2023· 50 citedOpen Access
Deep learning of electrochemical CO<sub>2</sub> conversion literature reveals research trends and directions
Journal of Materials Chemistry A·2023· 13 citedOpen Access
Machine Learning-Enabled Exploration of the Electrochemical Stability of Real-Scale Metallic Nanoparticles
2022· 1 citedOpen Access
Interpretable Deep Learning Model for Analyzing the Relationship between the Electronic Structure and Chemisorption Property
The Journal of Physical Chemistry Letters·2022· 6 cited
Machine learning assisted synthesis of lithium-ion batteries cathode materials
Nano Energy·2022· 77 citedOpen Access
Accelerated mapping of electronic density of states patterns of metallic nanoparticles via machine-learning
Scientific Reports·2021· 26 citedOpen Access
Reducing Time to Discovery: Materials and Molecular Modeling, Imaging, Informatics, and Integration
ACS Nano·2021· 62 citedOpen Access
Machine Learning Assisted Synthesis of Lithium-Ion Batteries Cathode Materials
SSRN Electronic Journal·2021· 4 citedOpen Access
Data-Driven Synthesis Optimization of Cathode Materials
ECS Meeting Abstracts·2020
Accelerated Mapping of Electronic Density of States Patterns of Metallic Nanoparticles via Machine-Learning
arXiv (Cornell University)·2020Open Access
Machine Learning Prediction of Electronic Density of States of Nanoparticles
2019
Recent Progress in First Principle Calculation and High-Throughput Screening of Electrocatalysts: A Review
Korean Journal of Metals and Materials·2019· 9 citedOpen Access
CO Oxidation On MoS2- Au Catalyst: Vacancy Formation and Tensile Strain Effects
2017
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Frequent Co-authors

Hyuck Mo Lee(16), Dong-Hun Kim(13), Sang Soo Han(12), Doosun Hong(8), EunAe Cho(6), Soonho Kwon(6), Chi Hao Liow(4), Hyeonmuk Kang(4), Moony Na(4), Arthur Baucour(4), Yoonsu Shim(4), Seongwoo Cho(4), Gun Park(4), Jiwon Yeom(4), Jong Min Yuk(4), Hye Ryung Byon(4), Seungbum Hong(4), Byung Chul Yeo(4), Kihyun Shin(4), Jiwoo Choi(4)