Modeling the solubility of light hydrocarbon gases and their mixture in brine with machine learning and equations of state
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
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2045-2322
- Extent
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Online-Ressource
- Language
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Englisch
- Notes
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online resource.
- Bibliographic citation
-
Modeling the solubility of light hydrocarbon gases and their mixture in brine with machine learning and equations of state ; volume:12 ; number:1 ; day:2 ; month:9 ; year:2022 ; pages:1-25 ; date:12.2022
Scientific reports ; 12, Heft 1 (2.9.2022), 1-25, 12.2022
- Creator
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Mohammadi, Mohammad-Reza
Hadavimoghaddam, Fahimeh
Atashrouz, Saeid
Abedi, Ali
Hemmati-Sarapardeh, Abdolhossein
Mohaddespour, Ahmad
- Contributor
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SpringerLink (Online service)
- DOI
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10.1038/s41598-022-18983-2
- URN
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urn:nbn:de:101:1-2022112009052719225493
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:36 AM CEST
Data provider
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Associated
- Mohammadi, Mohammad-Reza
- Hadavimoghaddam, Fahimeh
- Atashrouz, Saeid
- Abedi, Ali
- Hemmati-Sarapardeh, Abdolhossein
- Mohaddespour, Ahmad
- SpringerLink (Online service)
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Hydrocarbon molar water solubility predicts NMDA vs. GABAA receptor modulation
Effects of ultrasonic waves on carbon dioxide solubility in brine at different pressures and temperatures
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