Development Of Novel Superalloys By Using Computational Materials Science And Production By Powder Metallurgy

In this project, innovative alloys have been developed using both artificial neural networks and first-principles techniques, incorporating experimental data. The effects of alloying elements have been investigated both experimentally and through computational materials engineering. DFT-based CASTEP software was used within the scope of computational materials science. Structure and geometry optimization, as well as unit cells and elastic constants, have been determined for alloys with different compositions. Additionally, phase transformation temperatures have been studied with the help of data obtained from preliminary trials using artificial neural networks. The alloys have been produced using powder metallurgy method. The calculations were performed on a high-performance computing server (supercomputer).