Studying Cobalt Based Superalloys with Machine Learning

Materials discovery is a catalyst for human progression. Modern computational approaches seek to predict new superalloys, high-performance materials to extend and improve human potential. A recent high throughput search for ternary superalloys revealed six promising candidates including CoTaV and CoNbV. Further experimental investigation on these two ternary systems confirmed the superalloy phase but found them to be metastable. We explored the theoretical phase diagrams of these two ternary systems by computing total energies of more than 200k structures for exploring the stable phases. We do this using a class of systematically improvable potentials called the Moment Tensor Potential (MTP).