Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Dong Hyeon Mok"'
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-12 (2023)
Abstract The electrochemical carbon dioxide reduction reaction (CO2RR) is an attractive approach for mitigating CO2 emissions and generating value-added products. Consequently, discovery of promising CO2RR catalysts has become a crucial task, and mac
Externí odkaz:
https://doaj.org/article/9623cf484da94621a0a6fb555a722f58
Autor:
Guiru Zhang, Bing Tan, Dong Hyeon Mok, Huiya Liu, Baoxin Ni, Gui Zhao, Ke Ye, Shengjuan Huo, Xiaohe Miao, Zheng Liang, Xi Liu, Liwei Chen, Zemin Zhang, Wen-Bin Cai, Seoin Back, Kun Jiang
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America; 7/16/2024, Vol. 121 Issue 29, p1-549, 57p
Publikováno v:
Journal of Materials Chemistry A. 11:10184-10194
We developed Electronic Structure Network (ESNet) to predict formation energies using density of states extracted from initial structures. ESNet outperformed previously reported models that used other input features and architectures.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa3513afa10f269eddf3ac5dc0953e67
https://doi.org/10.1039/d3ta01767b
https://doi.org/10.1039/d3ta01767b
Publikováno v:
Chemistry of Materials. 35:63-70
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c11646d7c24be825f86be5091290c856
https://doi.org/10.1021/acs.chemmater.2c02498
https://doi.org/10.1021/acs.chemmater.2c02498
Autor:
Dong Hyeon Mok, WooSeok Lee, JongSeung Kim, Hyun Dong Jung, Ho Yeon Jang, SungJin Moon, ChaeHyeon Lee, Seoin Back
Publikováno v:
Ceramist. 25:126-144
Towards a sustainable energy future, it is essential to develop new catalysts with improved properties for key catalytic systems such as Haber-Bosch process, water electrolysis and fuel cell. Unfortunately, the current state-of-the-art catalysts stil
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1f5d9def0aa6dc8da21abc858900ed3
https://doi.org/10.31613/ceramist.2022.25.2.08
https://doi.org/10.31613/ceramist.2022.25.2.08
Autor:
Jinwoung Jo, Ji Mun Yoo, Dong Hyeon Mok, Ho Yeon Jang, Jiheon Kim, Wonjae Ko, Kyungbeen Yeom, Megalamane S. Bootharaju, Seoin Back, Yung-Eun Sung, Taeghwan Hyeon
Publikováno v:
Nano Letters. 22:3636-3644
Exposing facet and surface strain are critical factors affecting catalytic performance but unraveling the composition-dependent activity on specific facets under strain-controlled environment is still challenging due to the synthetic difficulties. He
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0abbedc8613ae1838e5fec476dc30f6d
https://doi.org/10.1021/acs.nanolett.2c00238
https://doi.org/10.1021/acs.nanolett.2c00238
In recent years, a development of appropriate crystal representations for accurate prediction of inorganic crystal properties has been considered as one of the essential tasks to accelerate materials discovery through high-throughput virtual screenin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::03f9327ffdc598b42df9b636981cb1de
https://doi.org/10.26434/chemrxiv-2023-ks8vp
https://doi.org/10.26434/chemrxiv-2023-ks8vp
Autor:
Qinglin Yuan, Jiajun Zhao, Dong Hyeon Mok, Zemin Zheng, Yixing Ye, Changhao Liang, Lin Zhou, Seoin Back, Kun Jiang
Publikováno v:
Nano letters. 22(3)
Se-based nanoalloys as an emerging class of metal chalcogenide with tunable crystalline structure, component distribution, and electronic structure have attracted considerable interest in renewable energy conversion and utilization. In this Letter, w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2a1e41b95876bd41c715ae658fd4c3b3
https://pubmed.ncbi.nlm.nih.gov/34965148
https://pubmed.ncbi.nlm.nih.gov/34965148
Autor:
Dong Hyeon Mok, Seoin Back
To discover new catalysts using density functional theory (DFT) calculations, binding energies of reaction intermediates are considered as descriptors to predict catalytic activities. Recently, machine learning methods have been developed to reduce t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a98899248eb1d49140ce0dc730da5dbc
https://doi.org/10.26434/chemrxiv.14560581.v1
https://doi.org/10.26434/chemrxiv.14560581.v1
Autor:
Jiheon Kim, Seong‐Jun Kim, Euiyeon Jung, Dong Hyeon Mok, Vinod K. Paidi, Jaewoo Lee, Hyeon Seok Lee, Yunseo Jeoun, Wonjae Ko, Heejong Shin, Byoung‐Hoon Lee, Shin‐Yeong Kim, Hyunjoong Kim, Ji Hwan Kim, Sung‐Pyo Cho, Kug‐Seung Lee, Seoin Back, Seung‐Ho Yu, Yung‐Eun Sung, Taeghwan Hyeon
Publikováno v:
Advanced Functional Materials. 32:2270108
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::053c1f60d7919cdc071644b52c7be01e
https://doi.org/10.1002/adfm.202270108
https://doi.org/10.1002/adfm.202270108