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2024
- A. Chauniyal, P. Thome, M. Stricker. Employing constrained nonnegative matrix factorization for microstructure segmentation. Microscopy and Microanalysis, 30, 712–723, (2024)
- M. Stricker, D. Weygand. A model for physical dislocation transmission through grain boundaries and its implementation in a discrete dislocation dynamics tool. Journal of Materials Science: Materials Theory, 8, 12, (2024)
- L. Zhang, M. Stricker. MatNexus: A comprehensive text mining and analysis suite for materials discovery. SoftwareX, 26, 101654, (2024)
- R. Khachaturyan, Y. Yang, S. Teng et al. Microscopic insights on field induced switching and domain wall motion in orthorhombic ferroelectrics. Physical Review Materials, 8, 024403, (2024)
2023
- A. Demirci, D. Steinberger, M. Stricker et al. Statistical analysis of discrete dislocation dynamics simulations: initial structures, cross-slip and microstructure evolution. Modelling and Simulation in Materials Science and Engineering, 31, 075003, (2023)
- G. Eshlaghi, G. Egels, S. Benito et al. Three-dimensional microstructure reconstruction for two-phase materials from three orthogonal surface maps. Frontiers in Materials, 10, 1-17, (2023)
- M. Ali, O. Shchyglo, M. Stricker et al. Coherency loss marking the onset of degradation in high temperature creep of superalloys: phase-field simulation coupled to strain gradient crystal plasticity. Computational Materials Science, 220, 112069, (2023)
2022
- M. Stricker, M. Ziemann, M. Walter et al. Dislocation structure analysis in the strain gradient of torsion loading: a comparison between modelling and experiment. Modelling and Simulation in Materials Science and Engineering, 30, 035007, (2022)
2021
- P. Stoyanov, R. Merz, M. Stricker et al. Achieving ultra-low friction with diamond/metal systems in extreme environments. Materials, 14, 3791, (2021)
- F. Musil, M. Veit, A. Goscinski et al. Efficient implementation of atom-density representations. The Journal of Chemical Physics, 154, 114109, (2021)
2020
- M. Stricker, W. A. Curtin. Prismatic slip in Magnesium. Journal of Physical Chemistry C, 124, 27230-27240, (2020)
- M. Stricker, B. Yin, E. Mak et al. Machine learning for metallurgy II. A neural-network potential for magnesium. Physical Review Materials, 4, 103602, (2020)