Yousung Jung

Seoul National University — South Korea

Materials Science · Physical Sciences

82h-index30.9kcitations330works8.32yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Machine Learning in Materials Science(71), Electrocatalysts for Energy Conversion(59), Advancements in Battery Materials(37), CO2 Reduction Techniques and Catalysts(36), Advanced Chemical Physics Studies(33)

Publications328 total

SynTwins: a retrosynthesis-guided framework for synthesizable molecular analog generation
Chemical Science·2025Open Access
Author response for "SynTwins: A Retrosynthesis-Guided Framework for Synthesizable Molecular Analog Generation"
2025
Author response for "SynTwins: A Retrosynthesis-Guided Framework for Synthesizable Molecular Analog Generation"
2025
Synthesis-Aware Materials Redesign via Large Language Models
Journal of the American Chemical Society·2025· 1 cited
Oxygen Poisoning of Copper Surfaces in the Presence of Cesium Ions during Electrochemical Nitrate Reduction to Ammonia
ACS Catalysis·2025· 3 cited
Direct Imaging of Co‐CUK‐1 Framework with H<sub>2</sub>O Guests
Small·2025· 1 cited
Degradation of NiMo Catalyst Under Intermittent Operation of Anion Exchange Membrane Water Electrolyzer and its Mitigation by Carbon Encapsulation
Advanced Energy Materials·2025· 7 citedOpen Access
Reliable Li-ion conductivity with efficient data generation and uncertainty estimation toward large-scale screening
Chemical Engineering Journal·2025· 4 cited
Feasibility of Active and Durable Lattice Oxygen‐Mediated Oxygen Evolution Electrocatalysts in Proton Exchange Membrane Water Electrolyzers Through d<sup>0</sup> Metal Ion Incorporation
Small·2025· 15 citedOpen Access
A Perspective on Foundation Models in Chemistry
JACS Au·2025· 21 citedOpen Access
Single-solvent electrolyte system for rechargeable magnesium batteries
2025Open Access
Predicting Chemical Reaction Outcomes Based on Electron Movements Using Machine Learning
arXiv (Cornell University)·2025Open Access
Explainable Synthesizability Prediction of Inorganic Crystal Polymorphs Using Large Language Models
Angewandte Chemie·2025Open Access
Explainable Synthesizability Prediction of Inorganic Crystal Polymorphs Using Large Language Models
Angewandte Chemie International Edition·2025· 18 citedOpen Access
Explainable Synthesizability Prediction of Inorganic Crystal Polymorphs using Large Language Models
2025Open Access
Electrochemical CO2 reduction to liquid fuels: Mechanistic pathways and surface/interface engineering of catalysts and electrolytes
The Innovation·2025· 16 citedOpen Access
Unveiling high-performance hosts for blue OLEDs via deep learning and high-throughput virtual screening
Chemical Engineering Journal·2025· 4 cited
Synergistic catalysis between In single atoms and In nanoparticles for highly selective electrocatalytic CO<sub>2</sub> reduction to formate with high current densities
Chemical Science·2025· 1 citedOpen Access
Explainable Synthesizability Prediction of Inorganic Crystal Polymorphs using Large Language Models
2024· 1 citedOpen Access
Noise Analysis and Data Refinement for Chemical Reactions from US Patents via Large Language Models
2024· 2 citedOpen Access
page 1 of 17Next →

Frequent Co-authors

Changhyeok Choi(10), Heejin Kim(9), Zhenyu Sun(8), Song Hong(7), Seoin Back(7), Jang Wook Choi(6), Juhwan Noh(6), Eunjeong Yang(5), Y. L. Soo(5), Geun Ho Gu(5), Dong Shin Choi(4), Tai‐Sing Wu(4), Martin Head‐Gordon(3), Zishan Han(3), Qun Fan(3), Min Sun Yeom(3), Justus Masa(3), Soo Yeon Lim(3), Jieshan Qiu(3), Rohini C. Lochan(2)