The Machine Intelligence for Chemical Chemistry (MICC) group focuses on developing machine learning algorithms and advanced simulation methods to accelerate novel chemical discovery. Current applications include energy conversion, storage, and generation, catalysis, carbon capture, organic and inorganic synthesis planning, and self-driving laboratories.

서울대학교 MICC 연구실은 새로운 화학 물질 발견을 가속화하기 위한 머신러닝 알고리즘 및 고급 시뮬레이션 방법 개발에 중점을 둔다. 에너지 변환, 저장 및 생성, 촉매, 탄소 포집, 유기 및 무기 합성 계획, 그리고 자율 주행 실험실 등이 주요 연구 분야이다.

Explainable synthesizability prediction of inorganic crystal polymorphs using large language models

Synergistic catalysis between In single atoms and In nanoparticles for highly selective electrocatalytic CO 2 reduction to formate with high current densities

Predicting synthesis recipes of inorganic crystal materials using elementwise template formulation

SynTwins: a retrosynthesis-guided framework for synthesizable molecular analog generation

Materealize: a multi-agent deliberation system for end-to-end material design and synthesis

Identifying the active sites and intermediates on copper surfaces for electrochemical nitrate reduction to ammonia

Single-solvent electrolyte system for rechargeable magnesium batteries

Predicting Chemical Reaction Outcomes Based on Electron Movements Using Machine Learning

Assessing the extrapolation capability of template-free retrosynthesis models

A photoelectrocatalytic system as a reaction platform for selective radical–radical coupling

Learning single-step retrosynthesis with simulated reactions

Data-Enabled Synthesis Predictions for Molecules and Materials

Advances in molecular quantum chemistry contained in the Q-Chem 4 program package

Advances in methods and algorithms in a modern quantum chemistry program package

Software for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package

Nitrogen fixation by Ru single-atom electrocatalytic reduction

Strengthening effect of single-atomic-layer graphene in metal–graphene nanolayered composites

On the theory of organic catalysis “on water”

On the mechanism of enhanced oxygen reduction reaction in nitrogen-doped graphene nanoribbons

Suppression of Hydrogen Evolution Reaction in Electrochemical N 2 Reduction Using Single-Atom Catalysts: A Computational Guideline

Scaled opposite-spin second order Møller–Plesset correlation energy: An economical electronic structure method

Active Sites of Au and Ag Nanoparticle Catalysts for CO 2 Electroreduction to CO

Unprecedented high-temperature CO 2 selectivity in N 2 -phobic nanoporous covalent organic polymers

Single-atom catalysts for CO 2 electroreduction with significant activity and selectivity improvements

The high performance of crystal water containing manganese birnessite cathodes for magnesium batteries

Inverse design of solid-state materials via a continuous representation

Electrochemical ammonia synthesis: mechanistic understanding and catalyst design

Na 2 FeP 2 O 7 as a Promising Iron‐Based Pyrophosphate Cathode for Sodium Rechargeable Batteries: A Combined Experimental and Theoretical Study

Electrochemical and thermal properties of NASICON structured Na3V2 (PO4) 3 as a sodium rechargeable battery cathode: a combined experimental and theoretical study

Entropy and the driving force for the filling of carbon nanotubes with water

Balancing activity, stability and conductivity of nanoporous core-shell iridium/iridium oxide oxygen evolution catalysts

Activation of Ni Particles into Single Ni–N Atoms for Efficient Electrochemical Reduction of CO 2

Yousung Jung

Professor of Chemical and Biological Engineering, Adjunct faculty, Graduate School of AI

MICC

교수님 소개

정유성

연구실 소개

연구실 키워드

알럼나이가 간 회사

연구실 지원 방법

대우 조건

연도별 논문 인용수

저널 & 학회 논문 출판 수

연구실 논문 목록

SynTwins: a retrosynthesis-guided framework for synthesizable molecular analog generation

Materealize: a multi-agent deliberation system for end-to-end material design and synthesis

Explainable synthesizability prediction of inorganic crystal polymorphs using large language models

연구실 보유 특허

대학별 입시끈

우리 연구실 모집

교수님 소개

정유성

연구실 키워드

알럼나이가 간 회사

연구실 지원 방법

대우 조건

연도별 논문 인용수

저널 & 학회 논문 출판 수

연구실 논문 목록

SynTwins: a retrosynthesis-guided framework for synthesizable molecular analog generation

Materealize: a multi-agent deliberation system for end-to-end material design and synthesis

Explainable synthesizability prediction of inorganic crystal polymorphs using large language models

연구실 보유 특허

최근 3년간 연구실적 높은 연구실

대학별 입시끈

우리 연구실 모집