Zobrazeno 1 - 10 of 24 pro vyhledávání: '"Joonchul Kim"'
1
Akademický článek
Interpretable machine learning boosting the discovery of targeted organometallic compounds with optimal bandgap
Autor: Taehyun Park, JunHo Song, Jinyoung Jeong, Seungpyo Kang, Joonchul Kim, Joonghee Won, Jungim Han, Kyoungmin Min
Publikováno v: Materials Today Advances, Vol 23, Iss , Pp 100520- (2024)
Organometallic compounds (OMCs) have attracted tremendous attention in various fields, such as photovoltaic cell and high-k dielectric application, due to their beneficial properties. Despite their potential, the progression of OMCs into industrial a
Externí odkaz: https://doaj.org/article/4e5365fe992e44c0a4706e551b588147
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2
Akademický článek
Toward fast and accurate machine learning interatomic potentials for atomic layer deposition precursors
Autor: Seungpyo Kang, Joonchul Kim, Taehyun Park, Joonghee Won, Chul Baik, Jungim Han, Kyoungmin Min
Publikováno v: Materials Today Advances, Vol 21, Iss , Pp 100474- (2024)
Under thin film deposition, when used in conjunction with the semiconductor atomic layer deposition (ALD) method, the choice of precursor determines the properties and quality of the thin film. Organometallic precursors such as alkaline earth metals
Externí odkaz: https://doaj.org/article/821a4947782242b8b34100e8d4606a9e
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3
Akademický článek
Correlating atomistic characteristics of zeolites to their 3D-Printed Macro structural properties for prediction of mechanical response
Autor: Joonchul Kim, Minseong Hong, JunHo Song, Namjung Kim, Kyoungmin Min
Publikováno v: Materials & Design, Vol 233, Iss , Pp 112189- (2023)
A wide range of mechanical properties are vital in structures, from macro (e.g., load-bearing) down to atomistic (nanomaterial) level. To design structures with the target mechanical properties, it is crucial to understand the correlation between the
Externí odkaz: https://doaj.org/article/6aa84baf7b4443009f4f7ef1b4903e36
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4
Akademický článek
Predicting mechanical properties of newly generated two-dimensional materials with minimum uncertainty
Autor: Inhyo Lee, Joonchul Kim, Taehyun Park, Kyoungmin Min
Publikováno v: Materials Today Advances, Vol 18, Iss , Pp 100374- (2023)
Two-dimensional (2D) materials exhibit exceptional properties. Thus, many studies have been conducted to discover novel 2D materials with unique characteristics or to find new ways of utilizing existing 2D materials. However, the existing open databa
Externí odkaz: https://doaj.org/article/39cacc0d5d854ab882f16c012d4b0eb7
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5
Impact of Data Partitioning to Improve Prediction Accuracy for Remaining Useful Life of Li-Ion Batteries
Autor: Joonchul Kim, Eunsong Kim, Jung-Hwan Park, Kyoung-Tak Kim, Joung-Hu Park, Taesic Kim, Kyoungmin Min
Publikováno v: International Journal of Energy Research. 2023:1-13
Predicting the remaining useful life (RUL) of a battery is critical to ensure the safe management of its manufacture and operation. In this study, a comprehensive investigation of the effect of data partitioning methods on RUL prediction was performe
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c501ecef746099d4975783512e794dbf
https://doi.org/10.1155/2023/9305309
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8
Prediction of dielectric constants of ABO
Autor: Eunsong, Kim, Joonchul, Kim, Kyoungmin, Min
Publikováno v: Physical chemistry chemical physics : PCCP. 24(11)
In this study, the machine-learning method, combined with density functional perturbation theory (DFPT) calculations, was implemented to predict and validate the dielectric constants of ABO
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::512684a2e44056fb82ee08c0fcebfa07
https://pubmed.ncbi.nlm.nih.gov/35258051
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