Machine-learning to predict anharmonic frequencies: a study of models and transferability †
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource, 8 Seiten
- Sprache
-
Englisch
- Erschienen in
-
In: Physical Chemistry Chemical Physics(26), H. 35, S.23495-23502 - ISSN 1463-9076
In: This journal is © the Owner Societies, Cambridge
- Ereignis
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Veröffentlichung
- (wo)
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Jena
- (wer)
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Friedrich-Schiller-Universität Jena
- (wann)
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2024
- Urheber
- URN
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urn:nbn:de:gbv:27-dbt-62475-2
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
25.03.2025, 13:55 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
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Beteiligte
- Khanifaev, Jamoliddin
- Schrader, Tim
- Perlt, Eva
- Friedrich-Schiller-Universität Jena
Entstanden
- 2024
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