Po, G.; Admal, N. C.; Svendsen, B.: Non-local Thermoelasticity Based on Equilibrium Statistical Thermodynamics. Journal of Elasticity 139, pp. 37 - 59 (2020)
Kochmann, J.; Wulfinghoff, S.; Ehle, L.; Mayer, J.; Svendsen, B.: Efficient and accurate two-scale FE-FFT-based prediction of the effective material behavior of elasto-viscoplastic polycrystals. Computational Mechanics 61, pp. 751 - 764 (2018)
Alipour, A.; Wulfinghoff, S.; Bayat, H. R.; Reese, S.; Svendsen, B.: The concept of control points in hybrid discontinuous Galerkin methods—Application to geometrically nonlinear crystal plasticity. International Journal for Numerical Methods in Engineering 114 (5), pp. 557 - 579 (2018)
Svendsen, B.; Shanthraj, P.; Raabe, D.: Finite-deformation phase-field chemomechanics for multiphase, multicomponent solids. Journal of the Mechanics and Physics of Solids 112, pp. 619 - 636 (2018)
Dusthakar, D. K.; Menzel, A.; Svendsen, B.: Laminate-based modelling of single and polycrystalline ferroelectric materials – application to tetragonal barium titanate. Mechanics of Materials 117, pp. 235 - 254 (2018)
Hütter, M.; Svendsen, B.: Formulation of strongly non-local, non-isothermal dynamics for heterogeneous solids based on the GENERIC with application to phase-field modeling. Materials Theory (1), 4, pp. 1 - 20 (2017)
Mianroodi, J. R.; Hunter, A. G. M.; Beyerlein, I. J.; Svendsen, B.: Theoretical and computational comparison of models for dislocation dissociation and stacking fault/core formation in fcc crystals. Journal of the Mechanics and Physics of Solids 95, pp. 719 - 741 (2016)
Kochmann, J.; Wulfinghoff, S.; Reese, S.; Mianroodi, J. R.; Svendsen, B.: Two-scale FE–FFT- and phase-field-based computational modeling of bulk microstructural evolution and macroscopic material behavior. Computer Methods in Applied Mechanics and Engineering 305, pp. 89 - 110 (2016)
Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances
The project’s goal is to synergize experimental phase transformations dynamics, observed via scanning transmission electron microscopy, with phase-field models that will enable us to learn the continuum description of complex material systems directly from experiment.
In order to prepare raw data from scanning transmission electron microscopy for analysis, pattern detection algorithms are developed that allow to identify automatically higher-order feature such as crystalline grains, lattice defects, etc. from atomically resolved measurements.
The general success of large language models (LLM) raises the question if they could be applied to accelerate materials science research and to discover novel sustainable materials. Especially, interdisciplinary research fields including materials science benefit from the LLMs capability to construct a tokenized vector representation of a large…
Crystal Plasticity (CP) modeling [1] is a powerful and well established computational materials science tool to investigate mechanical structure–property relations in crystalline materials. It has been successfully applied to study diverse micromechanical phenomena ranging from strain hardening in single crystals to texture evolution in…