A deep learning approach for complex microstructure inference AR Durmaz, M Müller, B Lei, A Thomas, D Britz, EA Holm, C Eberl, ... Nature communications 12 (1), 6272, 2021 | 52 | 2021 |
Automated Quantitative Analyses of Fatigue-Induced Surface Damage by Deep Learning A Thomas, AR Durmaz, T Straub, C Eberl Materials 13 (15), 3298, 2020 | 21 | 2020 |
Addressing materials’ microstructure diversity using transfer learning A Goetz, AR Durmaz, M Müller, A Thomas, D Britz, P Kerfriden, C Eberl npj Computational Materials 8 (1), 27, 2022 | 16 | 2022 |
Materials fatigue prediction using graph neural networks on microstructure representations A Thomas, AR Durmaz, M Alam, P Gumbsch, H Sack, C Eberl Scientific Reports 13 (1), 12562, 2023 | 8 | 2023 |
Ontology Modelling for Materials Science Experiments M Alam, H Birkholz, D Dessı, C Eberl, H Fliegl, P Gumbsch, P von Hartrott, ... | 4 | 2021 |
Microstructural damage dataset (pytorch geometric dataset) AR Durmaz, A Thomas | 2 | 2023 |
MaterioMiner-An ontology-based text mining dataset for extraction of process-structure-property entities AR Durmaz, A Thomas, L Mishra, R Niranjan Murthy, T Straub | | 2024 |
Author Correction: Materials fatigue prediction using graph neural networks on microstructure representations A Thomas, AR Durmaz, M Alam, P Gumbsch, H Sack, C Eberl Scientific Reports 13 (1), 13598, 2023 | | 2023 |
Messvorrichtung und Verfahren zum Erfassen einer magnetischen Eigenschaft einer mechanisch belasteten Probe A Blug, G Laskin, P Koss, AR Durmaz, T Straub, A Thomas | | 2023 |
Ontology modelling for materials science experiments M Alam, H Birkholz, D Dessi, C Eberl, H Fliegl, G Peter, P von Hartrott, ... CEUR WORKSHOP PROCEEDINGS 2941, 2021 | | 2021 |
MaterialDigital Dataset C Schweizer, A Thomas, P Hartrott, E Augenstein, H Oesterlin, J Lienhard, ... https://publica. fraunhofer. de/handle/publica/300549, 2020 | | 2020 |
Abschlussbericht zu" MaterialDigital" C Schweizer, R Reichenbach, A Butz, J Lienhard, T Herrmann, ... | | 2020 |