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)
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.
International research team shows how hydrogen affects Nickel-base superalloys at elevated temperatures. Latest results published in journal Nature Materials.
Max Planck team explains dendrite propagation, paving the way for safer and longer-lasting next-generation batteries. They publish their findings in the journal Nature.