Sunghwan Choi

ORCID

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 9

Top Venues

Nature communications

Journal of chemical theory and computation

The journal of physical chemistry letters

Chemistry (Weinheim an der Bergstrasse, Germany)

Korea Advanced Institute of Science and Technology (PHD)

This page only lists publications with an associated author ORCID identifier.

Education History

Korea Advanced Institute of Science and Technology Feb 01 2012

South Korea

PHD :: Department of Chemistry

Korea Advanced Institute of Science and Technology Feb 01 2009 - Feb 01 2012

South Korea

BSC :: Department of Chemistry

Publications

Jeheon Woo, Woo Youn Kim, Sunghwan Choi
Efficient Shift-and-Invert Preconditioning for Multi-GPU Accelerated Density Functional Calculations. Journal of chemical theory and computation (2024)
Sunghwan Choi
Prediction of transition state structures of gas-phase chemical reactions via machine learning. Nature communications 14 (1) (2023)
Sunghwan Choi
Prediction of transition state structures of gas-phase chemical reactions via machine learning. Nature communications 14 (1) (2023)
Sunghwan Choi
Prediction of transition state structures of gas-phase chemical reactions via machine learning. Nature communications 14 (1) (2023)
Jeheon Woo, Woo Youn Kim, Sunghwan Choi
System-Specific Separable Basis Based on Tucker Decomposition: Application to Density Functional Calculations. Journal of chemical theory and computation 18 (5) (2022)
Sanggil Park, Herim Han, Hyungjun Kim, Sunghwan Choi
Machine Learning Applications for Chemical Reactions. Chemistry, an Asian journal 17 (14) (2022)
Herim Han, Sunghwan Choi
Transfer Learning from Simulation to Experimental Data: NMR Chemical Shift Predictions. The journal of physical chemistry letters 12 (14) (2021)
Hyungjun Kim, Ji Young Park, Sunghwan Choi
Energy refinement and analysis of structures in the QM9 database via a highly accurate quantum chemical method. Scientific data 6 (1) (2019)
Sunghwan Choi, Yeonjoon Kim, Jin Woo Kim, Zeehyo Kim, Woo Youn Kim
Feasibility of Activation Energy Prediction of Gas-Phase Reactions by Machine Learning. Chemistry (Weinheim an der Bergstrasse, Germany) 24 (47) (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Sunghwan Choi