J
Julian Feinauer
Researcher at University of Ulm
Publications - 18
Citations - 454
Julian Feinauer is an academic researcher from University of Ulm. The author has contributed to research in topics: Microstructure & Electrode. The author has an hindex of 12, co-authored 18 publications receiving 325 citations. Previous affiliations of Julian Feinauer include Daimler AG.
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Journal ArticleDOI
Quantifying microstructural dynamics and electrochemical activity of graphite and silicon-graphite lithium ion battery anodes
Patrick Pietsch,Daniel Westhoff,Julian Feinauer,Jens Eller,Federica Marone,Marco Stampanoni,Marco Stampanoni,Volker Schmidt,Vanessa Wood +8 more
TL;DR: It is shown that microstructural changes that occur during (de)lithiation of a pure graphite electrode are of the same order of magnitude as spatial inhomogeneities within it, while strain in composite electrodes is locally pronounced and introduces significant micro structural changes.
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Stochastic 3D modeling of the microstructure of lithium-ion battery anodes via Gaussian random fields on the sphere
TL;DR: A stochastic model is developed that is able to produce realistic microstructures of lithium-ion battery anodes, which can serve as input for the simulations and uses the use of Gaussian random fields on the sphere as models for the particles that form the anodes.
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Stochastic microstructure modeling and electrochemical simulation of lithium-ion cell anodes in 3D
Simon Hein,Simon Hein,Julian Feinauer,Daniel Westhoff,Ingo Manke,Volker Schmidt,Arnulf Latz,Arnulf Latz +7 more
TL;DR: In this paper, the authors compare 3D images of real anode microstructures from lithium-ion batteries to virtual ones created by a parametric stochastic 3D microstructure model.
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Crack detection in lithium-ion cells using machine learning
Lukas Petrich,Daniel Westhoff,Julian Feinauer,Donal P. Finegan,Sohrab R. Daemi,Paul R. Shearing,Volker Schmidt +6 more
TL;DR: A classification model is proposed which is able to decide whether a pair of particles is the result of breakage, of the image segmentation, or neither, and its validity is tested by applying the methodology to hand-labelled data from a real electrode.
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Structural characterization of particle systems using spherical harmonics
TL;DR: In this paper, the spherical harmonics expansion is used to approximate particles obtained from tomographic 3D images, which yields an analytic representation of the particles which can be used to calculate structural characteristics.