High entropy alloys determination (predictive thermodynamics and Machine learning) and their fast elaboration by Spark Plasma Sintering


The proposed work aims to create an integrated system combining a computational thermodynamic algorithm (CALPHAD-type (calculation of phase diagrams)) with a multi-objective algorithm (genetic, Gaussian or other) together with data mining techniques in order to select and optimize compositions of High entropy alloys in a 6-element system: Fe-Ni-Co-Cr-Al-Mo. Associated with computational methods, fast fabrication and characterization methods of samples (hardness, density, grain size) will support the selection process. Optimization and validation of the alloy’s composition will be oriented towards two industrial use cases: structural alloys (replacement of Ni-based alloys) and corrosion protection against melted salts (nuclear application)

Doctorat en science des matériaux


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