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Hyunju Chang

Showing results (1-10 of 34) with videos related to

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Journal of Chemical Information and Modeling|September 15, 2023
Data-Driven Prediction of Configurational Stability of Molecule-Adsorbed Heterogeneous CatalystsJuhwan Noh, Hyunju Chang
Physical Chemistry Chemical Physics : PCCP|January 4, 2022
Nonlinearity encoding to improve extrapolation capabilities for unobserved physical statesGyoung S Na, Seunghun Jang, Hyunju Chang
Physical Chemistry Chemical Physics : PCCP|August 12, 2020
Machine-guided representation for accurate graph-based molecular machine learningGyoung S Na, Hyunju Chang, Hyun Woo Kim
Journal of Chemical Information and Modeling|January 14, 2020
Costless Performance Improvement in Machine Learning for Graph-Based Molecular AnalysisGyoung S Na, Hyun Woo Kim, Hyunju Chang
Scientific Reports|April 1, 2024
Optical property dataset of inorganic phosphorSeunghun Jang, Gyoung S Na, Yunhee Choi, et al.
The Journal of Physical Chemistry. A|December 7, 2020
Tuplewise Material Representation Based Machine Learning for Accurate Band Gap PredictionGyoung S Na, Seunghun Jang, Yea-Lee Lee, et al.
Methods in Molecular Biology (Clifton, N.J.)|April 28, 2010
Carbon nanotube biosensors with aptamers as molecular recognition elementsHye-Mi So, Dong-Won Park, Hyunju Chang, et al.
Macromolecular Rapid Communications|May 25, 2024
High Glass Transition Temperature Fluorinated Polymers Based on Transfer Learning with Small Experimental DataJin-Hoon Yang, Jiyoung Lee, Hajin Kwon, et al.
RSC Advances|May 11, 2022
New red-emitting phosphor Rb <sub></sub> K<sub>3-</sub> SiF<sub>7</sub>:Mn<sup>4+</sup> (<i>x</i> = 0, 1, 2, 3): DFT predictions and synthesisSeunghun Jang, June Kyu Park, Minseuk Kim, et al.
The Journal of Physical Chemistry. B|July 21, 2006
First-principles studies of SnS2 nanotubes: a potential semiconductor nanowireHyunju Chang, Eunjeong In, Ki-Jeong Kong, et al.
Pageof 4

Showing results (1-10 of 34) with videos related to

Sort By:
Pageof 4
Journal of Chemical Information and Modeling|September 15, 2023
Data-Driven Prediction of Configurational Stability of Molecule-Adsorbed Heterogeneous CatalystsJuhwan Noh, Hyunju Chang
Physical Chemistry Chemical Physics : PCCP|January 4, 2022
Nonlinearity encoding to improve extrapolation capabilities for unobserved physical statesGyoung S Na, Seunghun Jang, Hyunju Chang
Physical Chemistry Chemical Physics : PCCP|August 12, 2020
Machine-guided representation for accurate graph-based molecular machine learningGyoung S Na, Hyunju Chang, Hyun Woo Kim
Journal of Chemical Information and Modeling|January 14, 2020
Costless Performance Improvement in Machine Learning for Graph-Based Molecular AnalysisGyoung S Na, Hyun Woo Kim, Hyunju Chang
Scientific Reports|April 1, 2024
Optical property dataset of inorganic phosphorSeunghun Jang, Gyoung S Na, Yunhee Choi, et al.
The Journal of Physical Chemistry. A|December 7, 2020
Tuplewise Material Representation Based Machine Learning for Accurate Band Gap PredictionGyoung S Na, Seunghun Jang, Yea-Lee Lee, et al.
Methods in Molecular Biology (Clifton, N.J.)|April 28, 2010
Carbon nanotube biosensors with aptamers as molecular recognition elementsHye-Mi So, Dong-Won Park, Hyunju Chang, et al.
Macromolecular Rapid Communications|May 25, 2024
High Glass Transition Temperature Fluorinated Polymers Based on Transfer Learning with Small Experimental DataJin-Hoon Yang, Jiyoung Lee, Hajin Kwon, et al.
RSC Advances|May 11, 2022
New red-emitting phosphor Rb <sub></sub> K<sub>3-</sub> SiF<sub>7</sub>:Mn<sup>4+</sup> (<i>x</i> = 0, 1, 2, 3): DFT predictions and synthesisSeunghun Jang, June Kyu Park, Minseuk Kim, et al.
The Journal of Physical Chemistry. B|July 21, 2006
First-principles studies of SnS2 nanotubes: a potential semiconductor nanowireHyunju Chang, Eunjeong In, Ki-Jeong Kong, et al.
Pageof 4