Kontis, P.; Raabe, D.; Gault, B.: The role of systematic characterization on the development of new nickel-based superalloys. Industrial Colloquium - SFB/TR 103 „From Atoms to Turbine Blades“ , Fürth, Germany (2018)
Kwiatkowski da Silva, A.; Inden, G.; Ponge, D.; Gault, B.; Raabe, D.: Precipitation of CFCC-TmC Carbides during Tempering at 450°C of a Medium Mn Steel: A Thermodynamic and Kinetic Study Followed by Atom Probe Tomography. TMS 2018 Annual Meeting & Exhibition, Phoenix, AZ, USA (2018)
Gault, B.; Kontis, P.; Cormier, J.; Raabe, D.: From systematic characterisation to the next generation of high performance materials. THERMEC 2018 , Paris, France (2018)
Stephenson, L.; Rusitzka, A. K.; Gault, B.: Seeing atoms in biological materials: a new frontier for atomic-scale tomography. Volkswagen Stifung Symposium, Bremen, Germany (2018)
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
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…