AI for metallurgy
AI-guided alloy and process screening
Combine partner data with thermodynamic descriptors and characterization features to rank candidate alloys, processing windows, or recycling routes for experimental validation.
Expertise
AI & data-driven design.
Turn experimental, thermodynamic and characterization data into practical alloy and process decisions.
MPI-SusMat lists artificial intelligence, machine learning and digitalization among its materials-research topics, including algorithms that combine experimental data with computational modelling (MPI-SusMat overview).
Data-driven alloy and process screening, mechanism-based modelling, crystal plasticity, CALPHAD and integrated computational materials engineering. MPI-SusMat highlights artificial intelligence, machine learning, computational modelling and algorithms for predicting new alloy-property combinations.
Example project sprint
Usecases we address
Start a conversation
Bring us a materials challenge.
Confidential, NDA-friendly scoping calls. We listen first, then suggest the smallest engagement that can answer your question with technical confidence.