Dutta, B.; Opahle, I.; Hickel, T.: Interface effects on the magnetic properties of layered Ni2MnGa/Ni2MnSn alloys: A first-principles investigation. Functional Materials Letters 9 (6), 1642010 (2016)
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)
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
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…