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)
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
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 HyWay aims to promote the design of advanced materials that maintain outstanding mechanical properties while mitigating the impact of hydrogen by developing flexible, efficient tools for multiscale material modelling and characterization. These efficient material assessment suites integrate data-driven approaches, advanced…
A novel design with independent tip and sample heating is developed to characterize materials at high temperatures. This design is realized by modifying a displacement controlled room temperature micro straining rig with addition of two miniature hot stages.
Many important phenomena occurring in polycrystalline materials under large plastic strain, like microstructure, deformation localization and in-grain texture evolution can be predicted by high-resolution modeling of crystals. Unfortunately, the simulation mesh gets distorted during the deformation because of the heterogeneity of the plastic…
Here, we aim to develop machine-learning enhanced atom probe tomography approaches to reveal chemical short/long-range order (S/LRO) in a series of metallic materials.
Hydrogen embrittlement is one of the most substantial issues as we strive for a greener future by transitioning to a hydrogen-based economy. The mechanisms behind material degradation caused by hydrogen embrittlement are poorly understood owing to the elusive nature of hydrogen. Therefore, in the project "In situ Hydrogen Platform for…
The Atom Probe Tomography group in the Microstructure Physics and Alloy Design department is developing integrated protocols for ultra-high vacuum cryogenic specimen transfer between platforms without exposure to atmospheric contamination.