Marian, J.; Cereceda, D.; Diehl, M.; Roters, F.; Raabe, D.: Unraveling the temperature dependence of the yield strength of tungsten single crystals using atomistically-informed crystal plasticity. 8th International Conference on Multiscale Materials Modeling, MMM2016, Dijon, France (2016)
Cereceda, D.; Diehl, M.; Roters, F.; Raabe, D.; Marian, J.: Unraveling the temperature dependence of the yield strength in BCC metals from atomistically-informed crystal plasticity calculation. Dislocations 2016, Purdue University, West Lafayette, IN, USA (2016)
Diehl, M.; Eisenlohr, P.; Shanthraj, P.; Roters, F.: Using the Spectral Solver. 5th International Symposium on Computational Mechanics of Polycrystals, CMCn 2016 and first DAMASK User Meeting, Düsseldorf, Germany (2016)
Diehl, M.; Naunheim, Y.; Morsdorf, L.; An, D.; Roters, F.; Raabe, D.: Crystal Plasticity Simulations on Real Data: Towards Highly Resolved 3D Microstructures. 26th International Workshop on Computational Mechanics of Materials - IWCMM 26, Tomsk, Russia (2016)
Wong, S. L.; Roters, F.: Multiscale micromechanical modelling for advanced high strength steels including both the TRIP and TWIP effect. MSE 2016, Darmstadt, Germany (2016)
Roters, F.; Diehl, M.; Shanthraj, P.: Crystal Plasticity Simulations - Fundamentals, Implementation, Application. Micromechanics of Materials, Zernike Institute for Advanced Materials, University of Groningen
, Groningen, The Netherlands (2016)
Roters, F.; Diehl, M.; Shanthraj, P.: DAMASK Evolving From a Crystal Plasticity Subroutine Towards a Multi-Physics Simulation Tool. Focus Group Meeting “Metals”, SPP 1713, Bad Herrenalb, Germany (2016)
Roters, F.; Zhang, C.; Eisenlohr, P.; Shanthraj, P.; Diehl, M.: On the usage of HDF5 in the DAMASK crystal plasticity toolkit. 2nd International Workshop on Software Solutions for Integrated Computational Materials Engineering - ICME 2016, Barcelona, Spain (2016)
Demura, M.; Raabe, D.; Roters, F.; Hirano, T.: Computational analysis of irregular rolling deformation in Nickel Aluminide single crystals. Thermec 2016, Graz, Austria (2016)
Liu, B.; Arsenlis, T.; Raabe, D.; Roters, F.: Interfacial dislocation motion in single-crystal superalloys: dislocation interactions, vacancy supersaturation, and directional coarsening. Plasticity '16: The 22nd International Symposium on Plasticity & Its Cur
rent Applications
, Keauhou Bay, HI, USA (2016)
Roters, F.; Zhang, S.; Shantraj, P.: Including damage modelling into crystal plasticity simulation. Plasticity '16: The 22nd International Symposium on Plasticity & Its Cur
rent Applications
, Keauhou Bay, HI, USA (2016)
Wong, S. L.; Roters, F.: Multiscale micromechanical modelling for advanced high strength steels including both the TRIP and TWIP effect. Thermec 2016, Graz, Austria (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
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…
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…