Glensk, A.; Grabowski, B.; Hickel, T.; Neugebauer, J.: CALPHAD assessments using T > 0K ab initio data: From quasiharmonic to local anharmonic approximation. CALPHAD 2015, Loano, Italy (2015)
Opahle, I.; Madsen, G. K. H.; Dorigo, M.; Bera, C.; Glensk, A.; Drautz, R.: High-throughput density functional screening of thermoelectric materials. Evaluation ICAMS 2013, Bochum, Germany (2013)
Glensk, A.: Anharmonic contributions to ab initio computed thermodynamic material properties. Dissertation, University of Paderborn, Paderborn, Germany (2015)
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.