University of Utah

The University of Utah will use physical metallurgy principles and artificial intelligence to identify the chemistry of new niobium (Nb)-based refractory alloys to ensure they have excellent high-temperature properties without being brittle at low temperatures. The artificial intelligence approach will discover promising compositions for the new alloys based on existing knowledge of simple alloys. The computational materials models will be used to predict the proper processing conditions for the material chemistries. This two-step process can down-select the alloy compositions and manufacturing conditions from millions of possibilities, greatly reducing the time and cost for the search of new materials. The team will use advanced microscopy techniques to characterize the sample microstructures. Successful chemistries will be selected for scale-up experiments. If successful, the project will identify the alloy compositions and processing conditions to potentially mass produce turbine blades that can operate at temperatures significantly higher than the current state of the art.

Combining development of new ultrahigh temperature materials with compatible coatings and manufacturing technologies has the potential to increase gas turbine efficiency up to 7%, which will significantly reduce wasted energy and carbon emissions.