Accelerating superalloy discovery using moment tensor potentials

Superalloys are used in applications where high-temperature strength is necessary. Their extraordinary mechanical properties rely on the formation of the γ' – L1₂ phase. The discovery of a new superior superalloy will revolutionize the energy and transit industries. Computational methods such as density functional theory (DFT) are used to predict the γ’ phase, but DFT is expensive and it limits how fast we can discover new superalloys. Moment Tensor Potentials (MTP) create an interatomic potential via machine learning that approximates the quantum mechanical energies of a crystal structure many orders of magnitude faster than DFT. We explore the ternary alloy system Al-Co-W, who’s γ' phase was discovered experimentally in 2006, and show that MTP correctly predicts this phase. We also explore the ternary alloy system Hf-Ni-Si, which is a superalloy candidate that was found to have a lower formation enthalpy and smaller decomposition energy than Al-Co-W, and report the results of the investigation.