Matthias Weber

• Feinauer J, Brereton T, Spettl A, Weber M, Manke I and Schmidt V (2015). Stochastic 3D modeling of the microstructure of lithium-ion battery anodes via Gaussian random fields on the sphere. Computational Materials Science 109, 137-146.
• Weber M, Spettl A, Dosta M, Heinrich S and Schmidt V (2017). Simulation-based investigation of core-shell agglomerates: Influence of spatial heterogeneity in particle sizes on breakage characteristics. Computational Materials Science 137, 100-106.
• Furat O, Leißner T, Ditscherlein R, Šedivý O, Weber M, Bachmann K, Gutzmer J, Peuker U and Schmidt V (2018). Description of Ore Particles from X-Ray Microtomography (XMT) Images, Supported by Scanning Electron Microscope (SEM)-Based Image Analysis. Microscopy and Microanalysis 24 (5), 461-470.
• Schlüter S, Blaser SRGA, Weber M, Schmidt V and Vetterlein D (2018). Quantification of Root Growth Patterns From the Soil Perspective via Root Distance Models. Frontiers in Plant Science 9, 1084.
• Dosta M, Weber M, Schmidt V and Antonyuk S, DEM Analysis of Breakage Behavior of Bicomponent Agglomerates. In: Antonyuk S (ed.) Particles in Contact. Springer International Publishing, Cham 2019, pp. 165-183.
• Furat O, Prifling B, Westhoff D, Weber M and Schmidt V (2019). Statistical 3D Analysis and Modeling of Complex Particle Systems based on Tomographic Image Data. Practical Metallography 56 (12), 787-796.
• Furat O, Wang M, Neumann M, Petrich L, Weber M, Krill CE and Schmidt V (2019). Machine Learning Techniques for the Segmentation of Tomographic Image Data of Functional Materials. Frontiers in Materials 6, 145.
• Kaack L, Altaner CM, Carmesin C, Diaz A, Holler M, Kranz C, Neusser G, Odstrcil M, Schenk HJ, Schmidt V, Weber M, Zhang Y and Jansen S (2019). Function and three-dimensional structure of intervessel pit membranes in angiosperms: a review. IAWA Journal 40 (4), 673-702.
• Furat O, Frank U, Weber M, Wawra S, Peukert W and Schmidt V (2020). Estimation of bivariate probability distributions of nanoparticle characteristics, based on univariate measurements. Inverse Problems in Science & Engineering, accepted.
• Kaack L, Weber M, Isasa E, Karimi Z, Li S, Pereira L, Trabi CL, Zhang Y, Schenk HJ, Schuldt B, Schmidt V and Jansen S (2020). Pore constrictions in intervessel pit membranes reduce the risk of embolism spreading in angiosperm xylem, submitted.
• Schnepf A, Black CK, Couvreur V, Delory BM, Doussan C, Koch A, Koch T, Javaux M, Landl M, Leitner D, Lobet G, Mai TH, Meunier F, Petrich L, Postma JA, Priesack E, Schmidt V, Vanderborght J, Vereecken H and Weber M (2020). Call for participation: Collaborative benchmarking of functional-structural root architecture models. The case of root water uptake. Frontiers in Plant Science 11, 316.
• Weber M, Bäuerle A, Schmidt M, Neumann M, Fändrich M, Ropinski T and Schmidt V (2020). Automatic identification of crossovers in cryo-EM images of murine amyloid protein A fibrils with machine learning. Journal of Microscopy 277 (1), 12-22.
• Zhang Y, Carmesin C, Kaack L, Klepsch MM, Kotowska M, Matei T, Schenk HJ, Weber M, Walther P, Schmidt V and Jansen S (2020). High porosity with tiny pore constrictions and unbending pathways characterize the 3D structure of intervessel pit membranes in angiosperm xylem. Plant, Cell & Environment 43 (1), 116-130.
• Weber M, Wilhelm T and Schmidt V (2021). Multidimensional characterisation of time-dependent image data: A case study for the peripheral nervous system in ageing mice. Image Analysis & Stereology.

Semester	Veranstaltung
WS 2017/18	Angewandte Stochastik II
SS 2020	Monte Carlo Methods
WS 2020/21	Angewandte Stochastik II
SS 2021	Angewandte Stochastik I