Bévillon, É.; Colombier, J. P.; Dutta, B.; Stoian, R. I.: Ab Initio Nonequilibrium Thermodynamic and Transport Properties of Ultrafast Laser Irradiated 316L Stainless Steel. The Journal of Physical Chemistry C 119 (21), pp. 11438 - 11446 (2015)
Dutta, B.; Hickel, T.; Entel, P.; Neugebauer, J.: Ab Initio Predicted Impact of Pt on Phase Stabilities in Ni–Mn–Ga Heusler alloys. Journal of Phase Equilibra and Diffusion 35 (6), pp. 695 - 700 (2014)
Hickel, T.; Aydin, U.; Sözen, H. I.; Dutta, B.; Pei, Z.; Neugebauer, J.: Innovative concepts in materials design to boost renewable energies. Seminar of Institute for Innovative Technologies, SRH Berlin University of Applied Sciences, Berlin, Germany (2020)
Dutta, B.: Role of temperature dependent excitations and the coupling between them in functional materials: Ab-initio insights. IFM at Linköping University, Linköping, Sweden (2018)
Dutta, B.; Körmann, F.; Hickel, T.; Neugebauer, J.: Temperature-driven effects in functional materials: Ab initio insights. Talk at University Pierre and Marie CURIE (UPMC), Paris, France (2017)
Dutta, B.; Olsen, R. J.; Mu, S.; Hickel, T.; Samolyuk, G. D.; Specht, E. D.; Bei, H.; Lindsay, L. R.; Neugebauer, J.; Stocks , M.et al.; Larson, B. C.: Lattice dynamics in high entropy alloys: understanding the role of fluctuations. EUROMAT 2017, Thessaloniki, Greece (2017)
Dutta, B.: Coupling of magnetic and lattice degrees of freedom in magnetic Heusler alloys: Consequences for phase diagrams. Seminar at Materials Research Centre, Indian Institute of Science, Bengaluru, India (2017)
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.