Tom Kirstein




+49 (0)731/50-23528


+49 (0)731/50-23649


  • Raum-Nr. 1.42
    Helmholtzstr. 18
    89069 Ulm


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Publikationen und Preprints

 T. Kirstein, L. Petrich, R. R. P. Purushottam Raj Purohit, J.-S. Micha and V. Schmidt,  CNN-Based Laue Spot Morphology Predictor for Reliable Crystallographic Descriptor Estimation . In:  Materials,  2023.pdf 

O. Furat, T. Kirstein, T. Leißner, K. Bachmann, J. Gutzmer, U. A. Peuker and V. Schmidt,  Multidimensional characterization of particle morphology and mineralogical composition using CT data and R-vine copulas. In: arXiv,   2023. pdf 

S. Englisch, R. Ditscherlein, T. Kirstein, L. Hansen, O. Furat, D. Drobek, T. Leißner, B. A. Zubiri, A. P. Weber, V. Schmidt, U. A. Peuker and E. Spiecker,  3D analysis of equally X-ray attenuating mineralogical phases utilizing a correlative tomographic workflow across multiple length scales. In: Powder Technology 419,   2023. pdf

O. Furat, D. P. Finegan, Z. Yang, T. Kirstein, K. Smith and V. Schmidt,  Super-resolving microscopy images of Li-ion electrodes for fine-feature quantification using generative adversarial networks. In: npj Computational Materials 8,   2022. pdf

F. von Loeper, T. Kirstein, B. Idlbi, H. Ruf, G. Heilscher and V. Schmidt, Probabilistic analysis of solar power supply using D-vine copulas based on meteorological variables. In: S. Goettlich, M. Herty and A. Milde (eds.) Mathematical Modeling, Simulation and Optimization for Power Engineering and Management. Mathematics in Industry, vol 34. Springer, 2021, pp. 51-68.