A big data approach to the ultra-fast prediction of DFT-calculated bond energies

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Standort: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1758-2946

Umfang: Online-Ressource

Sprache: Englisch

Anmerkungen: online resource.

Erschienen in: A big data approach to the ultra-fast prediction of DFT-calculated bond energies ; volume:5 ; number:1 ; day:12 ; month:7 ; year:2013 ; pages:1-13 ; date:12.2013
Journal of cheminformatics ; 5, Heft 1 (12.7.2013), 1-13, 12.2013

Urheber: Qu, Xiaohui
Latino, Diogo ARS
Aires-de-Sousa, Joao

Beteiligte Personen und Organisationen: SpringerLink (Online service)

DOI: 10.1186/1758-2946-5-34

URN: urn:nbn:de:101:1-2021083121083595243205

Rechteinformation: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Letzte Aktualisierung: 15.08.2025, 07:27 MESZ

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Beteiligte

Qu, Xiaohui
Latino, Diogo ARS
Aires-de-Sousa, Joao
SpringerLink (Online service)

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A big data approach to the ultra-fast prediction of DFT-calculated bond energies

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