| Physical basis of amyloid fibril polymorphism W Close, M Neumann, A Schmidt, M Hora, K Annamalai, M Schmidt, ... Nature communications 9 (1), 699, 2018 | 176 | 2018 |
| Predicting effective conductivities based on geometric microstructure characteristics O Stenzel, O Pecho, L Holzer, M Neumann, V Schmidt AIChE Journal 62 (5), 1834-1843, 2016 | 130 | 2016 |
| Quantitative relationships between microstructure and effective transport properties based on virtual materials testing G Gaiselmann, M Neumann, V Schmidt, O Pecho, T Hocker, L Holzer AIChE Journal 60 (6), 1983-1999, 2014 | 110 | 2014 |
| Machine learning techniques for the segmentation of tomographic image data of functional materials O Furat, M Wang, M Neumann, L Petrich, M Weber, CE Krill III, V Schmidt Frontiers in Materials 6, 145, 2019 | 88 | 2019 |
| Hierarchical Structuring of NMC111-Cathode Materials in Lithium-Ion Batteries: An In-Depth Study on the Influence of Primary and Secondary Particle Sizes on Electrochemical … AC Wagner, N Bohn, H Geßwein, M Neumann, M Osenberg, A Hilger, ... ACS Applied Energy Materials 3 (12), 12565-12574, 2020 | 79 | 2020 |
| Quantifying the influence of microstructure on effective conductivity and permeability: virtual materials testing M Neumann, O Stenzel, F Willot, L Holzer, V Schmidt International Journal of Solids and Structures 184, 211-220, 2020 | 74 | 2020 |
| Role of mutations and post-translational modifications in systemic AL amyloidosis studied by cryo-EM L Radamaker, S Karimi-Farsijani, G Andreotti, J Baur, M Neumann, ... Nature communications 12 (1), 6434, 2021 | 67 | 2021 |
| 3D microstructure effects in Ni-YSZ Anodes: Prediction of effective transport properties and optimization of redox stability O Pecho, O Stenzel, B Iwanschitz, P Gasser, M Neumann, V Schmidt, ... Materials 8 (9), 5554-5585, 2015 | 63 | 2015 |
| Stochastic 3D modeling of complex three-phase microstructures in SOFC-electrodes with completely connected phases M Neumann, J Staněk, OM Pecho, L Holzer, V Beneš, V Schmidt Computational Materials Science 118, 353-364, 2016 | 61 | 2016 |
| Stochastic 3D modeling of La0. 6Sr0. 4CoO3− δ cathodes based on structural segmentation of FIB–SEM images G Gaiselmann, M Neumann, L Holzer, T Hocker, MR Prestat, V Schmidt Computational Materials Science 67, 48-62, 2013 | 61 | 2013 |
| Hydrostatic Pressure Increases the Catalytic Activity of Amyloid Fibril Enzymes TQ Luong, N Erwin, M Neumann, A Schmidt, C Loos, V Schmidt, ... Angewandte Chemie International Edition 55 (40), 12412-12416, 2016 | 56 | 2016 |
| Large-scale statistical learning for mass transport prediction in porous materials using 90,000 artificially generated microstructures B Prifling, M Röding, P Townsend, M Neumann, V Schmidt Frontiers in Materials, 497, 2021 | 44 | 2021 |
| Big data for microstructure‐property relationships: A case study of predicting effective conductivities O Stenzel, O Pecho, L Holzer, M Neumann, V Schmidt AIChE Journal 63 (9), 4224-4232, 2017 | 44 | 2017 |
| Estimation of geodesic tortuosity and constrictivity in stationary random closed sets M Neumann, C Hirsch, J Staněk, V Beneš, V Schmidt Scandinavian Journal of Statistics, 2019 | 43 | 2019 |
| Tortuosity and microstructure effects in porous media: classical theories, empirical data and modern methods L Holzer, P Marmet, M Fingerle, A Wiegmann, M Neumann, V Schmidt Springer, Cham,, 2023 | 42 | 2023 |
| Detection of Colchicum autumnale in drone images, using a machine-learning approach L Petrich, G Lohrmann, M Neumann, F Martin, A Frey, A Stoll, V Schmidt Precision Agriculture 21, 1291-1303, 2020 | 37 | 2020 |
| On a pluri-Gaussian model for three-phase microstructures, with applications to 3D image data of gas-diffusion electrodes M Neumann, M Osenberg, A Hilger, D Franzen, T Turek, I Manke, ... Computational Materials Science 156, 325-331, 2019 | 28 | 2019 |
| Analysis of the 3D microstructure of tape-cast open-porous materials via a combination of experiments and modeling SH Ibrahim, M Neumann, F Klingner, V Schmidt, T Wejrzanowski Materials & Design 133, 216-223, 2017 | 24 | 2017 |
| Classification of FIB/SEM-tomography images for highly porous multiphase materials using random forest classifiers M Osenberg, A Hilger, M Neumann, A Wagner, N Bohn, JR Binder, ... Journal of Power Sources 570, 233030, 2023 | 21 | 2023 |
| On variability and interdependence of local porosity and local tortuosity in porous materials: a case study for sack paper M Neumann, E Machado Charry, K Zojer, V Schmidt Methodology and computing in applied probability 23 (2), 613-627, 2021 | 21 | 2021 |
Volker SchmidtUlm University, Institute of StochasticsVahvistettu sähköpostiosoite verkkotunnuksessa uni-ulm.de
