Predicting the inhibition efficiencies of magnesium dissolution modulators using sparse machine learning models
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
-
Englisch
- Bibliographic citation
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In: npj Computational Materials 7 (1): 193 (2021-12)
- Event
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Veröffentlichung
- (where)
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Hamburg
- (who)
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Universitätsbibliothek der Technischen Universität Hamburg-Harburg
- (when)
-
2021
- Creator
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Schiessler, Elisabeth J.
Würger, Tim
Lamaka, Sviatlana
Meißner, Robert
Cyron, Christian J.
Zheludkevich, Mikhail L.
Feiler, Christian
Aydin, Roland C.
- DOI
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10.15480/882.4040
- URN
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urn:nbn:de:gbv:830-882.0162947
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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25.03.2025, 1:50 PM CET
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Schiessler, Elisabeth J.
- Würger, Tim
- Lamaka, Sviatlana
- Meißner, Robert
- Cyron, Christian J.
- Zheludkevich, Mikhail L.
- Feiler, Christian
- Aydin, Roland C.
- Universitätsbibliothek der Technischen Universität Hamburg-Harburg
Time of origin
- 2021
Other Objects (12)
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Challenging the Status Quo : Predicting Violence with Sparse Decision-Making Data
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Dissolution
Value pluralism, trade-offs and efficiencies
Approaching dissolution
Searching the chemical space for effective magnesium dissolution modulators: a deep learning approach using sparse features
In silico screening of modulators of magnesium dissolution
Exploring structure-property relationships in magnesium dissolution modulators
Predicting corrosion inhibition efficiencies of small organic molecules using data-driven techniques
Predicting solar cell efficiencies from bulk lifetime images of multicrystalline silicon bricks
Challenging the Status Quo : Predicting Violence with Sparse Decision-Making Data
Efficiencies in merger analysis
Mergers, Managerial Incentives, and Efficiencies
Mergers, managerial incentives, and efficiencies
Dissolution
Value pluralism, trade-offs and efficiencies
Approaching dissolution
Searching the chemical space for effective magnesium dissolution modulators: a deep learning approach using sparse features
In silico screening of modulators of magnesium dissolution
Exploring structure-property relationships in magnesium dissolution modulators
Predicting corrosion inhibition efficiencies of small organic molecules using data-driven techniques
Predicting solar cell efficiencies from bulk lifetime images of multicrystalline silicon bricks
Challenging the Status Quo : Predicting Violence with Sparse Decision-Making Data
Efficiencies in merger analysis
Mergers, Managerial Incentives, and Efficiencies
Mergers, managerial incentives, and efficiencies
Dissolution
Value pluralism, trade-offs and efficiencies