Dr. Orkun Furat

Semester	Course	Task
WS 2022/23	Advanced Statistics	Lecturer
SS 2021	Seminar: Spatial stochastic modeling, supported by methods of machine learning	Seminar advisor
WS 2020/21	Markov Chains	Teaching assistant
SS 2019	Point processes	Teaching assistant
SS 2018	Point processes	Teaching assistant

Publications and preprints

 

• O. Furat, T. Leißner, R. Ditscherlein, O. Sedivy, M. Weber, K. Bachmann, J. Gutzmer, U. Peuker and V. Schmidt, Description of ore particles from XMT images, supported by SEM-based image analysis. Microscopy and Microanalysis 24 (2018), 461-470.
• M. Neumann, O. Furat, D. Hlushkou, U. Tallarek, L. Holzer and V. Schmidt, On microstructure-property relationships derived by virtual materials testing with an emphasis on effective conductivity. In: M. Baum, G. Brenner, J. Grabowski, T. Hanschke, S. Hartmann, and A. Schöbel (eds.), Simulation Science: Proceedings of the Clausthal-Göttingen International Workshop on Simulation Science, Göttingen 2017. Communications in Computer and Information Science (CIS), Springer 2018, pp. 145-158.
• B. Prifling, O. Furat, D. Schmidt, H. Markötter, I. Manke, T. Bernthaler, V. Knoblauch and V. Schmidt, 3D-Mikrostrukturanalyse von Elektroden in Lithium-Ionen-Batterien. DGM-Jahresmagazin Materialographie 2018, pp. 88-91.
• C. Baldermann, A. Baldermann, O. Furat, M. Krüger, M. Nachtnebel, H. Schroettner, J. Juhart, V. Schmidt and J. Tritthart, Mineralogical and microstructural response of hydrated cement blends to leaching. Construction & Building Materials 229 (2019), 116902.
• O. Furat, T. Leißner, K. Bachmann, J. Gutzmer, U. Peuker and V. Schmidt, Stochastic modeling of multidimensional particle characteristics using parametric copulas. Microscopy and Microanalysis 25 (2019), 720-734.
• O. Furat, B. Prifling, D. Westhoff, M. Weber and V. Schmidt, Statistische Analyse und Modellierung von komplexen Partikelsystemen in 3D mittels tomographischer Bilddaten. Practical Metallography 56 (2019), 787-796.
• O. Furat, M.Y. Wang, M. Neumann, L. Petrich, M. Weber, C.E. Krill III and V. Schmidt, Machine learning techniques for the segmentation of tomographic image data of functional materials. Frontiers in Materials 6 (2019), 145.
• O. Furat, M. Masuhr, F.E. Kruis and V. Schmidt, Stochastic modeling of classifying aerodynamic lenses for separation of airborne particles by material and size. Advanced Powder Technology 31 (2020), 2215-2226.
• R. Ditscherlein, O. Furat, M. de Langlard, J. Martins de Souza e Silva, J. Sygusch, M. Rudolph, T. Leißner, V. Schmidt and U.A. Peuker, Multi-scale tomographic analysis for micron-sized particulate samples. Microscopy and Microanalysis 26 (2020), 676-688.
• J. Schreier, O. Furat, M. Cankaya, V. Schmidt and U. Bröckel, Automated evaluation of contact angles in a three-phase system of selective agglomeration in liquids. Image Analysis & Stereology 20 (2020), 179-188.
• O. Furat, D. Finegan, D. Diercks, F. Usseglio-Viretta, K. Smith and V. Schmidt, Mapping the architecture of single electrode particles in 3D, using electron backscatter diffraction and machine learning segmentation. Journal of Power Sources 483 (2021), 229148.
• O. Furat, L. Petrich, D. Finegan, D. Diercks, F. Usseglio-Viretta, K. Smith and V. Schmidt, Artificial generation of representative single Li-ion electrode particle architectures from microscopy data. npj Computational Materials 7 (2021), 105.
• O. Furat, A. Baldermann, C. Baldermann, M. Dietzel and V. Schmidt, Quantitative assessment of microstructural changes of hydrated cement blends due to leaching and carbonation, based on statistical analysis of image data. Construction and Building Materials 302 (2021), 124370.
• O. Furat, U. Frank, M. Weber, S. Wawra, W. Peukert and V. Schmidt, Estimation of bivariate probability distributions of nanoparticle characteristics, based on univariate measurements. Inverse Problems in Science and Engineering 29 (2021), 1343-1368.
• J. Allen, P.J. Weddle, A. Verma, A. Mallarapu, F. Usseglio-Viretta, D.P. Finegan, A. Colclasure, W. Mai, V. Schmidt, O. Furat, D. Diercks, T. Tanim and K. Smith, Quantifying the influence of charge rate and cathode-particle architectures on degradation of Li-ion cells through 3D continuum-level damage models. Journal of Power Sources 512 (2021), 230415.
• L. Petrich, O. Furat, M.Y. Wang, C.E. Krill III and V. Schmidt, Efficient fitting of 3D tessellations to curved polycrystalline grain boundaries. Frontiers in Materials 8 (2021), 507.
• R. Ditscherlein, O. Furat, E. Löwer, R. Mehnert, R. Trunk, T. Leißner, M.J. Krause, V. Schmidt and U.A. Peuker, PARROT - A pilot study on the open access provision of particle discrete tomographic datasets. Microscopy and Microanalysis 28 (2022), 350-360.
• 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. npj Computational Materials 8 (2022), 68.
• O. Furat, D.P. Finegan, Z. Yang, T. Tanim, K. Smith and V. Schmidt, Quantifying the Impact of Charge Rate and Number of Cycles on Structural Degeneration of Li-Ion Battery Electrodes. Journal of The Electrochemical Society 169 (2022), 100541.
• S. Englisch, R. Ditscherlein, T. Kirstein, L. Hansen, O. Furat, D. Drobek, T. Leißner, B. Apeleo 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. Powder Technology 419 (2023), 118343.
• T. Wilhelm, J. Sandbrink, O. Furat, K. Bachmann, M. Rudolph and V. Schmidt, Parametric stochastic modeling of particle descriptor vectors for studying the influence of ultrafine particle wettability and morphology on flotation-based separation behavior. Powders 2 (2023), 353-371.