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Geun Ho Gu

Showing results (1-10 of 24) with videos related to

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Chemical Science|June 14, 2021
Machine-enabled inverse design of inorganic solid materials: promises and challengesJuhwan Noh, Geun Ho Gu, Sungwon Kim, et al.
Journal of Chemical Information and Modeling|March 27, 2020
Uncertainty-Quantified Hybrid Machine Learning/Density Functional Theory High Throughput Screening Method for CrystalsJuhwan Noh, Geun Ho Gu, Sungwon Kim, et al.
Nature Communications|April 27, 2022
Automated exploitation of the big configuration space of large adsorbates on transition metals reveals chemistry feasibilityGeun Ho Gu, Miriam Lee, Yousung Jung, et al.
Journal of the American Chemical Society|October 26, 2020
Structure-Based Synthesizability Prediction of Crystals Using Partially Supervised LearningJidon Jang, Geun Ho Gu, Juhwan Noh, et al.
Chemical Science|January 19, 2024
Predicting synthesis recipes of inorganic crystal materials using elementwise template formulationSeongmin Kim, Juhwan Noh, Geun Ho Gu, et al.
Nature Communications|July 17, 2021
Understanding potential-dependent competition between electrocatalytic dinitrogen and proton reduction reactionsChanghyeok Choi, Geun Ho Gu, Juhwan Noh, et al.
ACS Central Science|March 31, 2022
Correction to "Generative Adversarial Networks for Crystal Structure Prediction"Sungwon Kim, Juhwan Noh, Geun Ho Gu, et al.
ACS Central Science|September 3, 2020
Generative Adversarial Networks for Crystal Structure PredictionSungwon Kim, Juhwan Noh, Geun Ho Gu, et al.
Accounts of Chemical Research|June 26, 2024
Reaction Templates: Bridging Synthesis Knowledge and Artificial IntelligenceShuan Chen, Juhwan Noh, Jidon Jang, et al.
The Journal of Physical Chemistry Letters|March 20, 2020
Practical Deep-Learning Representation for Fast Heterogeneous Catalyst ScreeningGeun Ho Gu, Juhwan Noh, Sungwon Kim, et al.
Pageof 3

Showing results (1-10 of 24) with videos related to

Sort By:
Pageof 3
Chemical Science|June 14, 2021
Machine-enabled inverse design of inorganic solid materials: promises and challengesJuhwan Noh, Geun Ho Gu, Sungwon Kim, et al.
Journal of Chemical Information and Modeling|March 27, 2020
Uncertainty-Quantified Hybrid Machine Learning/Density Functional Theory High Throughput Screening Method for CrystalsJuhwan Noh, Geun Ho Gu, Sungwon Kim, et al.
Nature Communications|April 27, 2022
Automated exploitation of the big configuration space of large adsorbates on transition metals reveals chemistry feasibilityGeun Ho Gu, Miriam Lee, Yousung Jung, et al.
Journal of the American Chemical Society|October 26, 2020
Structure-Based Synthesizability Prediction of Crystals Using Partially Supervised LearningJidon Jang, Geun Ho Gu, Juhwan Noh, et al.
Chemical Science|January 19, 2024
Predicting synthesis recipes of inorganic crystal materials using elementwise template formulationSeongmin Kim, Juhwan Noh, Geun Ho Gu, et al.
Nature Communications|July 17, 2021
Understanding potential-dependent competition between electrocatalytic dinitrogen and proton reduction reactionsChanghyeok Choi, Geun Ho Gu, Juhwan Noh, et al.
ACS Central Science|March 31, 2022
Correction to "Generative Adversarial Networks for Crystal Structure Prediction"Sungwon Kim, Juhwan Noh, Geun Ho Gu, et al.
ACS Central Science|September 3, 2020
Generative Adversarial Networks for Crystal Structure PredictionSungwon Kim, Juhwan Noh, Geun Ho Gu, et al.
Accounts of Chemical Research|June 26, 2024
Reaction Templates: Bridging Synthesis Knowledge and Artificial IntelligenceShuan Chen, Juhwan Noh, Jidon Jang, et al.
The Journal of Physical Chemistry Letters|March 20, 2020
Practical Deep-Learning Representation for Fast Heterogeneous Catalyst ScreeningGeun Ho Gu, Juhwan Noh, Sungwon Kim, et al.
Pageof 3