Roters, F.; do Nascimento, A. W. P.; Roongta, S.; Diehl, M.: An optimized method for the simulation-based determination of initial parameters of advanced yield surfaces for sheet metal forming applications. Complas 2021, online (2021)
Raabe, D.; Diehl, M.; Shanthraj, P.; Sedighiani, K.; Roters, F.: Multi-scale and multi-physics simulations of chemo-mechanical crystal plasticity problems for complex engineering materials using DAMASK. Online Colloquium Lecture, Department of Materials Science and Engineering, KTH Royal Institute of Technology, Stockholm, Sweden (2020)
Roters, F.; Diehl, M.; Sedighiani, K.: (Re-) formulation of dislocation density based crystal plasticity models in view of insights from parameter determination. Oberwolfach Workshop: Mechanics of Materials: Towards Predictive Methods for Kinetics in Plasticity, Fracture, and Damage, Oberwolfach, Germany (2020)
Sedighiani, K.; Traka, K.; Diehl, M.; Roters, F.; Bos, K.; Sietsma, J.; Raabe, D.: A Coupled Crystal Plasticity – Cellular Automaton Method for 3D Modeling of Recrystallization: Part I: Crystal Plasticity. International Conference on Plasticity, Damage, and Fracture, Riviera May, Mexico (2020)
Cereceda, D.; Diehl, M.; Roters, F.; Raabe, D.; Perlado, J. M.; Marian, J.: Understanding the Plastic Behavior of Tungsten From First Principles to Crystal Plasticity. International Mechanical Engineering Congress & Exposition (IMECE) 2019, Salt Lake City, UT, USA (2019)
Sedighiani, K.; Traka, K.; Diehl, M.; Roters, F.; Sietsma, J.; Raabe, D.: Determination and validation of BCC crystal plasticity parameters for a wide range of temperatures and strain rates. 7th Conference on Recrystallization and Grain Growth, REX 2019, Ghent, Belgium (2019)
Shah, V.; Diehl, M.; Roters, F.: Prediction of Nucleation Sites for Recrystallization using Crystal Plasticity Simulations. 7th International Conference on Recrystallization and Grain Growth, Ghent, Belgium (2019)
Diehl, M.; Roters, F.; Raabe, D.: Coupled Experimental-Computational Investigations of Grain Scale Mechanics in Complex Metallic Microstructures. 15th U.S. National Congress on Computational Mechanics, Ausrin, TX, USA (2019)
Han, F.; Diehl, M.; Roters, F.; Raabe, D.: Multi-scale modeling of plasticity. ICIAM 2019 - The 9th International Congress on Industrial and Applied Mathematics, Valencia, Spain (2019)
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
In this project we developed a phase-field model capable of describing multi-component and multi-sublattice ordered phases, by directly incorporating the compound energy CALPHAD formalism based on chemical potentials. We investigated the complex compositional pathway for the formation of the η-phase in Al-Zn-Mg-Cu alloys during commercial…
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.
While Density Functional Theory (DFT) is in principle exact, the exchange functional remains unknown, which limits the accuracy of DFT simulation. Still, in addition to the accuracy of the exchange functional, the quality of material properties calculated with DFT is also restricted by the choice of finite bases sets.