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Machine learning models for predicting the experimental frontier orbital energies
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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Sungnam Park | - |
| dc.date.accessioned | 2022-04-23T05:40:35Z | - |
| dc.date.available | 2022-04-23T05:40:35Z | - |
| dc.date.created | 2022-04-23 | - |
| dc.date.issued | 2022-04-14 | - |
| dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/140368 | - |
| dc.publisher | 대한화학회 | - |
| dc.title | Machine learning models for predicting the experimental frontier orbital energies | - |
| dc.title.alternative | Machine learning models for predicting the experimental frontier orbital energies | - |
| dc.type | Conference | - |
| dc.contributor.affiliatedAuthor | Sungnam Park | - |
| dc.identifier.bibliographicCitation | 제129회 대한화학회 학술발표회 | - |
| dc.relation.isPartOf | 제129회 대한화학회 학술발표회 | - |
| dc.relation.isPartOf | 제129회 대한화학회 학술발표회 초록집 | - |
| dc.citation.title | 제129회 대한화학회 학술발표회 | - |
| dc.citation.conferencePlace | KO | - |
| dc.citation.conferenceDate | 2022-04-13 | - |
| dc.type.rims | CONF | - |
| dc.description.journalClass | 2 | - |
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