Patrick Altschuh

  • Institut für Angewandte Materialien
    Computational Materials Science (IAM-CMS)
    MZE - Geb. 30.48
    Straße am Forum 7
    76131 Karlsruhe

     

Forschung

Porous Microstructures and Microfluidics

  • Modeling of realistic structures, especially porous membrane-like structures
  • Development of methods for characterizing porous structures
  • Coupling the phase-field model with fluid dynamic models
  • Simulation of capillary-driven flows through porous structures

 

        

     

Publikationliste


An Interdisciplinary Approach to Manage Materials Data with Kadi4Mat and Chemotion
Altschuh, P.; Bräse, S.; Hartmann, T.; Jaeger, D.; Jung, N.; Koeppe, A.; Krauss, P.; Leister, C.; Nestler, B.; Schiefer, G.; Schreiber, C.; Selzer, M.; Starmann, M.; Tosato, G.
2023. E-Science-Tage 2023: Empower Your Research – Preserve Your Data. Ed.: Vincent Heuveline, Nina Bisheh, Philipp Kling, 264–269, heiBOOKS. doi:10.11588/heibooks.1288.c18086
A U-Net-Based Self-Stitching Method for Generating Periodic Grain Structures
Ji, Y.; Koeppe, A.; Altschuh, P.; Griem, L.; Rajagopal, D.; Nestler, B.; Chen, W.; Zhang, Y.; Zheng, Y.
2023. arXiv preprint arXiv:2310.20379
Towards automatic feature extraction and sample generation of grain structure by variational autoencoder
Ji, Y.; Koeppe, A.; Altschuh, P.; Rajagopal, D.; Zhao, Y.; Chen, W.; Chen, W.; Zhang, Y.; Zheng, Y.; Nestler, B.
2024. Computational Materials Science, 232, Art.-Nr.: 112628. doi:10.1016/j.commatsci.2023.112628
Establishing structure–property linkages for wicking time predictions in porous polymeric membranes using a data-driven approach
Kunz, W.; Altschuh, P.; Bremerich, M.; Selzer, M.; Nestler, B.
2023. Materials Today Communications, 35, Art.-Nr.: 106004. doi:10.1016/j.mtcomm.2023.106004
An interdisciplinary approach to data management
Altschuh, P.; Bräse, S.; Hartmann, T.; Jaeger, D.; Jung, N.; Krauss, P.; Leister, C.; Nestler, B.; Schiefer, G.; Schreiber, C.; Selzer, M.; Starman, M.; Tosato, G.; Koeppe, A.
2023. E-Science-Tage 2023: Empower Your Research – Preserve Your Data (2023), Heidelberg, Deutschland, 1.–3. März 2023. doi:10.11588/heidok.00033126
Characterization of porous membranes using artificial neural networks
Zhao, Y.; Altschuh, P.; Santoki, J.; Griem, L.; Tosato, G.; Selzer, M.; Koeppe, A.; Nestler, B.
2023. Acta Materialia, 253, Art.-Nr.: 118922. doi:10.1016/j.actamat.2023.118922
A 3D computational method for determination of pores per inch (PPI) of porous structures
Jamshidi, F.; Kunz, W.; Altschuh, P.; Lu, T.; Laqua, M.; August, A.; Löffler, F.; Selzer, M.; Nestler, B.
2023. Materials Today Communications, 34, Art.-Nr.: 105413. doi:10.1016/j.mtcomm.2023.105413
KadiStudio: FAIR Modelling of Scientific Research Processes
Griem, L.; Zschumme, P.; Laqua, M.; Brandt, N.; Schoof, E.; Altschuh, P.; Selzer, M.
2022. Data Science Journal, 21 (1), Art.-Nr: 16. doi:10.5334/dsj-2022-016
Geometric flow control in lateral flow assays: Macroscopic single-phase modeling
Jamshidi, F.; Kunz, W.; Altschuh, P.; Bremerich, M.; Przybylla, R.; Selzer, M.; Nestler, B.
2022. Physics of Fluids, 34 (6), Art.-Nr.: 062110. doi:10.1063/5.0093316
Computational Design and Characterisation of Gyroid Structures with Different Gradient Functions for Porosity Adjustment
Wallat, L.; Altschuh, P.; Reder, M.; Nestler, B.; Poehler, F.
2022. Materials, 15 (10), Art.-Nr.: 3730. doi:10.3390/ma15103730
MoMaF Science Data Center für Molekulare Materialforschung
Altschuh, P.; Bach, F.; Bräse, S.; Hartmann, T.; Jung, N.; Krauß, P.; Nestler, B.; Schiefer, G.; Schreiber, C.; Selzer, M.; Terzijska, D.
2021. E-Science-Tage 2019: Data to Knowledge (2021), Heidelberg, Deutschland, 4.–5. März 2021
MoMaF Science Data Center für Molekulare Materialforschung
Altschuh, P.; Bach, F.; Bräse, S.; Hartmann, T.; Jung, N.; Krauß, P.; Nestler, B.; Schiefer, G.; Schreiber, C.; Selzer, M.; Terzijska, D.
2021. E-Science-Tage 2021: Share Your Research Data, Heidelberg, 04.03. - 05.03.2021. doi:10.11588/heidok.00029699
A digital workflow for learning the reduced-order structure-property linkages for permeability of porous membranes
Yabansu, Y. C.; Altschuh, P.; Hötzer, J.; Selzer, M.; Nestler, B.; Kalidindi, S. R.
2020. Acta materialia, 195, 668–680. doi:10.1016/j.actamat.2020.06.003
Skalenübergreifende Analyse makroporöser Membranen im Kontext digitaler Zwillinge. Dissertation
Altschuh, P.
2020, August 26. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000122904
Progress Report on Phase Separation in Polymer Solutions
Wang, F.; Altschuh, P.; Ratke, L.; Zhang, H.; Selzer, M.; Nestler, B.
2019. Advanced materials, 31 (26), Art.Nr. 1806733. doi:10.1002/adma.201806733
Phase-field study on the growth of magnesium silicide occasioned by reactive diffusion on the surface of Si-foams
Wang, F.; Altschuh, P.; Matz, A. M.; Heimann, J.; Matz, B. S.; Nestler, B.; Jost, N.
2019. Acta materialia, 170, 138–154. doi:10.1016/j.actamat.2019.03.008
Characterization of a macro porous polymer membrane at micron-scale by Confocal-Laser-Scanning Microscopy and 3D image analysis
Ley, A.; Altschuh, P.; Thom, V.; Selzer, M.; Nestler, B.; Vana, P.
2018. Journal of membrane science, 564, 543–551. doi:10.1016/j.memsci.2018.07.062
Data science approaches for microstructure quantification and feature identification in porous membranes
Altschuh, P.; Yabansu, Y. C.; Hötzer, J.; Selzer, M.; Nestler, B.; Kalidindi, S. R.
2017. Journal of membrane science, 540, 88–97. doi:10.1016/j.memsci.2017.06.020
Publikationen
Titel Autor Quelle

Acta Materialia (2019)

Advanced Materials (2019)

Forschung aktuell (2018)