Sreekala, L.; Dey, P.; Hickel, T.; Neugebauer, J.: Unveiling nonmonotonic chemical trends in the solubility of H in complex Fe–Cr–Mn carbides by means of ab initio based approaches. Physical Review Materials 6 (1), 014403 (2022)
Hickel, T.; McEniry, E.; Nazarov, R.; Dey, P.: Ab initio basierte Simulation zur Wasserstoffversprödung in hoch-Mn Stählen. Seminar der Staatlichen Materialprüfungsanstalt Darmstadt, Institut für Werkstoffkunde, Darmstadt, Germany (2020)
Dey, P.: Materials design based on ab initio methods: Coherent microstructure & its impact on real application. Seminar at TU Delft, Delft, The Netherlands (2018)
Dey, P.; Yao, M.; Friák, M.; Hickel, T.; Raabe, D.; Neugebauer, J.: Ab-initio investigation of the role of kappa carbide in upgrading Fe–Mn–Al–C alloy to the class of advanced high-strength steels. ArcelorMittal Global R&D Gent, Thessaloniki, Greece (2017)
Dey, P.: Ab initio investigation of the interaction of hydrogen with carbides in advanced high-strength steels. Seminar at Southern University of Science and Technology, Shenzhen, China (2017)
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 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.