There are no files associated with this item.
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.citation.endPage | 9420 | - |
dc.citation.number | 42 | - |
dc.citation.startPage | 9414 | - |
dc.citation.title | JOURNAL OF PHYSICAL CHEMISTRY A | - |
dc.citation.volume | 125 | - |
dc.contributor.author | Hajibabaei, Amir | - |
dc.contributor.author | Ha, Miran | - |
dc.contributor.author | Pourasad, Saeed | - |
dc.contributor.author | Kim, Junu | - |
dc.contributor.author | Kim, Kwang S. | - |
dc.date.accessioned | 2023-12-21T15:09:43Z | - |
dc.date.available | 2023-12-21T15:09:43Z | - |
dc.date.created | 2021-12-09 | - |
dc.date.issued | 2021-10 | - |
dc.description.abstract | Machine learning (ML) interatomic potentials (ML-IAPs) are generated for alkane and polyene hydrocarbons using on-the-fly adaptive sampling and a sparse Gaussian process regression (SGPR) algorithm. The ML model is generated based on the PBE+D3 level of density functional theory (DFT) with molecular dynamics (MD) for small alkane and polyene molecules. Intermolecular interactions are also trained with clusters and condensed phases of small molecules. It shows excellent transferability to long alkanes and closely describes the ab inito potential energy surface for polyenes. Simulation of liquid ethane also shows reasonable agreement with experimental reports. This is a promising initiative toward a universal ab initio quality force-field for hydrocarbons and organic molecules. | - |
dc.identifier.bibliographicCitation | JOURNAL OF PHYSICAL CHEMISTRY A, v.125, no.42, pp.9414 - 9420 | - |
dc.identifier.doi | 10.1021/acs.jpca.1c05819 | - |
dc.identifier.issn | 1089-5639 | - |
dc.identifier.scopusid | 2-s2.0-85118141843 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/55351 | - |
dc.identifier.url | https://pubs.acs.org/doi/10.1021/acs.jpca.1c05819 | - |
dc.identifier.wosid | 000713417800016 | - |
dc.language | 영어 | - |
dc.publisher | AMER CHEMICAL SOC | - |
dc.title | Machine Learning of First-Principles Force-Fields for Alkane and Polyene Hydrocarbons | - |
dc.type | Article | - |
dc.description.isOpenAccess | FALSE | - |
dc.relation.journalWebOfScienceCategory | Chemistry, Physical; Physics, Atomic, Molecular & Chemical | - |
dc.relation.journalResearchArea | Chemistry; Physics | - |
dc.type.docType | Article | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | MOLECULAR-DYNAMICS SIMULATIONS | - |
dc.subject.keywordPlus | ARTIFICIAL PERIODICITY | - |
dc.subject.keywordPlus | ELECTROSTATICS | - |
Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Tel : 052-217-1404 / Email : scholarworks@unist.ac.kr
Copyright (c) 2023 by UNIST LIBRARY. All rights reserved.
ScholarWorks@UNIST was established as an OAK Project for the National Library of Korea.