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
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one. With this project, we aim to…
Atom probe tomography (APT) provides three dimensional(3D) chemical mapping of materials at sub nanometer spatial resolution. In this project, we develop machine-learning tools to facilitate the microstructure analysis of APT data sets in a well-controlled way.
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…