A neuro-evolution machine learning potential for accurately describing defect-dependent mechanical behaviors in Mo-Nb alloys.
In this work, a neuro-evolution machine learning potential integrated with the Ziegler-Biersack-Littmark repulsive potential is developed for accurately describing defect-dependent mechanical behaviors of molybdenum-niobium (Mo-Nb) alloys using only 721 training structures. Molecular dynamics simulations are then perfo...