Efficient machine-learning based interatomic potentialsfor exploring thermal conductivity in two-dimensional materials
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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In: Mortazavi, B.; Podryabinkin, E.V.; Novikov, I.S.; Roche, S.; Rabczuk, T. et al.: Efficient machine-learning based interatomic potentialsfor exploring thermal conductivity in two-dimensional materials. In: JPhys Materials (Journal of Physics: Materials) 3 (2020), Nr. 2, 02LT02. DOI: https://doi.org/10.1088/2515-7639/ab7cbb
- Ereignis
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Veröffentlichung
- (wo)
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Hannover
- (wer)
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Gottfried Wilhelm Leibniz Universität Hannover
- (wann)
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2020
- Ereignis
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Veröffentlichung
- (wo)
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Hannover
- (wer)
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Technische Informationsbibliothek (TIB)
- (wann)
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2020
- Urheber
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Mortazavi, Bohayra
Podryabinkin, Evgeny V.
Novikov, Ivan S.
Roche, Stephan
Rabczuk, Timon
Zhuang, Xiaoying
Shapeev, Alexander V.
- DOI
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10.15488/16435
- URN
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urn:nbn:de:101:1-2024022901281370289219
- Rechteinformation
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Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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14.08.2025, 10:59 MESZ
Datenpartner
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Beteiligte
- Mortazavi, Bohayra
- Podryabinkin, Evgeny V.
- Novikov, Ivan S.
- Roche, Stephan
- Rabczuk, Timon
- Zhuang, Xiaoying
- Shapeev, Alexander V.
- Gottfried Wilhelm Leibniz Universität Hannover
- Technische Informationsbibliothek (TIB)
Entstanden
- 2020
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