| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Manke, Ingo
Helmholtz-Zentrum Berlin für Materialien und Energie
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (26/26 displayed)
- 2024R‐Vine Copulas for Data‐Driven Quantification of Descriptor Relationships in Porous Materialscitations
- 2024Opportunities and Challenges of Calendering Sulfide‐Based Separators for Solid‐State Batteriescitations
- 2023Roadmap for focused ion beam technologiescitations
- 2023Roadmap for focused ion beam technologiescitations
- 2023Torsion of a rectangular bar: Complex phase distribution in 304L steel revealed by neutron tomography
- 2023Unveiling the impact of cross-linking redox-active polymers on their electrochemical behavior by 3D imaging and statistical microstructure analysiscitations
- 2023Spectral neutron tomography
- 20223D microstructure characterization of polymer battery electrodes by statistical image analysis based on synchrotron X-ray tomographycitations
- 2022Temperature dependence in Bragg edge neutron transmission measurementscitations
- 2022Phosphonated graphene oxide-modified polyacrylamide hydrogel electrolytes for solid-state zinc-ion batteriescitations
- 2022Quantification of Hydrogen in Metals Applying Neutron Imaging Techniques
- 2022Fabrication and characterization of porous mullite ceramics derived from fluoride-assisted Metakaolin-Al(OH)3 annealing for filtration applications
- 2021Lithium deposition in single-ion conducting polymer electrolytescitations
- 2021Stochastic 3D microstructure modeling of anodes in lithium-ion batteries with a particular focus on local heterogeneitycitations
- 2021Hierarchical Structuring of NMC111-Cathode Materials in Lithium-Ion Batteries: An In-Depth Study on the Influence of Primary and Secondary Particle Sizes on Electrochemical Performance
- 2020Performance and behavior of LLZO-based composite polymer electrolyte for lithium metal electrode with high capacity utilizationcitations
- 2020Hierarchical Structuring of NMC111-Cathode Materials in Lithium-Ion Batteries: An In-Depth Study on the Influence of Primary and Secondary Particle Sizes on Electrochemical Performancecitations
- 2020X‐Ray‐Computed Radiography and Tomography Study of Electrolyte Invasion and Distribution inside Pristine and Heat‐Treated Carbon Felts for Redox Flow Batteries
- 2020Hierarchical Structuring of NMC111-Cathode Materials in Lithium-Ion Batteriescitations
- 2019On a pluri-Gaussian model for three-phase microstructures, with applications to 3D image data of gas-diffusion electrodescitations
- 2019In Operando Neutron Radiography Analysis of a High-Temperature Polymer Electrolyte Fuel Cell Based on a Phosphoric Acid-Doped Polybenzimidazole Membrane Using the Hydrogen-Deuterium Contrast Method
- 2019X‐ray‐computed radiography and tomography study of electrolyte invasion and distribution inside pristine and heat‐treated carbon felts for redox flow batteries
- 2018Correlating Morphological Evolution of Li Electrodes with Degrading Electrochemical Performance of Li/LiCoO2 and Li/S Battery Systemscitations
- 2016Filling in the gaps
- 2015How mobile are protons in the structure of dental glass ionomer cements?citations
- 2013Methodology for Combined Neutron Diffraction and Bragg Edge Imagingcitations
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article
R‐Vine Copulas for Data‐Driven Quantification of Descriptor Relationships in Porous Materials
Abstract
<p>Local variations in the 3D microstructure can control the macroscopic behavior of heterogeneous porous materials. For example, the permittivity through porous sheets or membranes is governed by local high-volume pathways or bottlenecks. Due to local variations, unfeasibly large amounts of microstructure data may be needed to reliably predict such material properties directly from image data. Here it is demonstrated that a vine copula approach provides parametric models for local microstructure descriptors that compactly capture the 3D microstructure including its local variations and efficiently probe it with respect to selected, measurable properties. In contrast to common methods of complexity reduction, the proposed approach creates parametric models for the multivariate probability distribution of high-dimensional descriptor vectors that inherently contain the complex, nonlinear dependencies between these descriptors. Therein, material properties are offered in physically motivated distributions of microstructure descriptors rather than as normally distributed data. Applied to porous fiber networks (paper) before and after unidirectional compression, it is shown that the copula-based models reveal material-characteristic relationships between two or more microstructure descriptors. In this way, the presented modeling approach can provide deeper insight into the microscopic origin of effective macroscopic properties of heterogeneous porous materials.</p>