| |  Online-Ressource |
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| Verfasst von: | Neumann, Matthias [VerfasserIn]  |
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| | Wetterauer, Sven [VerfasserIn] |
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| | Osenberg, Markus [VerfasserIn] |
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| | Hilger, André [VerfasserIn] |
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| | Gräfensteiner, Phillip [VerfasserIn] |
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| | Wagner, Amalia [VerfasserIn] |
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| | Bohn, Nicole [VerfasserIn] |
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| | Binder, Joachim R. [VerfasserIn] |
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| | Manke, Ingo [VerfasserIn] |
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| | Carraro, Thomas [VerfasserIn] |
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| | Schmidt, Volker [VerfasserIn] |
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| Titel: | A data-driven modeling approach to quantify morphology effects on transport properties in nanostructured NMC particles |
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| Verf.angabe: | Matthias Neumann, Sven E Wetterauer, Markus Osenberg, André Hilger, Phillip Gräfensteiner, Amalia Wagner, Nicole Bohn, Joachim R Binder, Ingo Manke, Thomas Carraro, Volker Schmidt |
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| E-Jahr: | 2023 |
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| Jahr: | 19 Juni 2023 |
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| Umfang: | 12 S. |
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| Fussnoten: | Online verfügbar: 19 Juni 2023, Version des Artikels: 7 Juli 2023 ; Gesehen am 14.11.2023 |
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| Titel Quelle: | Enthalten in: International journal of solids and structures |
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| Ort Quelle: | New York, NY [u.a.] : Elsevier, 1965 |
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| Jahr Quelle: | 2023 |
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| Band/Heft Quelle: | 280(2023), Artikel-ID 112394, Seite 1-12 |
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| Abstract: | We present a data-driven modeling approach to quantify morphology effects on transport properties in nanostructured materials. Our approach is based on the combination of stochastic modeling of the 3D nanostructure and numerical modeling of effective transport properties, which is used to investigate process-structure-property relationships of hierarchically structured cathode materials for lithium-ion batteries. We focus on nanostructured LiNi1/3Mn1/3Co1/3O2 (NMC) particles, the nanoporous morphology of which has a crucial impact on their effective transport properties (i.e, effective ionic and electric conductivity) and thus on the performance of the cell. First, we develop a parametric stochastic model for the 3D morphology of the nanostructured NMC particles based on excursion sets of so-called χ2-fields. This model, which has only two parameters, is then fitted to FIB-SEM image data of the NMC particles manufactured with different calcination temperatures and different particle sizes. This way it is possible to generate digital twins of the NMC particles. In a second step, measured 3D image data and corresponding digital twins are used as input for the numerical simulation of effective transport properties. Based on the results obtained by these simulations, we can quantify process-structure-property relationships. Overall, we present a methodological framework that allows for an efficient optimization of the fabrication process of nanostructured NMC particles. |
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| DOI: | doi:10.1016/j.ijsolstr.2023.112394 |
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| URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
Volltext: https://doi.org/10.1016/j.ijsolstr.2023.112394 |
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| | Volltext: https://www.sciencedirect.com/science/article/pii/S0020768323002913 |
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| | DOI: https://doi.org/10.1016/j.ijsolstr.2023.112394 |
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| Datenträger: | Online-Ressource |
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| Sprache: | eng |
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| Sach-SW: | Digital twin |
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| | Effective tortuosity |
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| | FIB-SEM tomography |
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| | Finite element modeling |
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| | Nanostructured battery material |
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| | Stochastic 3D modeling |
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| | Transport in porous media |
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| K10plus-PPN: | 1856087603 |
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| Verknüpfungen: | → Zeitschrift |
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A data-driven modeling approach to quantify morphology effects on transport properties in nanostructured NMC particles / Neumann, Matthias [VerfasserIn]; 19 Juni 2023 (Online-Ressource)
