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This item is licensed Korea Open Government License
- dc.contributor.author
- 최성환
- dc.contributor.author
- 김우연
- dc.contributor.author
- 김연준
- dc.contributor.author
- 김지효
- dc.contributor.author
- 김진우
- dc.date.accessioned
- 2019-08-28T07:42:15Z
- dc.date.available
- 2019-08-28T07:42:15Z
- dc.date.issued
- 2018-02-23
- dc.identifier.issn
- 0947-6539
- dc.identifier.uri
- https://repository.kisti.re.kr/handle/10580/14748
- dc.language
- eng
- dc.relation.ispartofseries
- Chemistry - A European Journal
- dc.title
- Feasibility of activation energy prediction of gas-phase reactions via machine learning
- Appears in Collections:
- 7. KISTI 연구성과 > 학술지 발표논문
- Files in This Item:
- There are no files associated with this item.
