Venue: The 10th International Conference on Multiscale Materials Modeling

Date: Thursday October 6, 15:15 - 15:35

Symposium: #18 Multiscale Materials Modeling Using Ab-Initio Accuracy Methods

Location: Kent Room - 6th Floor

Synergistic Coupling in Ab Initio-Machine Learning Simulations of Dislocations

Authors: Petr Grigorev, Thomas Swinburne*

Calculations of dislocation-defect interactions are essential to model metallic strength, but the required system sizes are at or beyond ab initio limits. Current estimates thus have extrapolation or finite size errors that are very challenging to quantify. Hybrid methods offer a solution, embedding small ab initio simulations in an empirical medium. However, current implementations can only match mild elastic deformations at the ab initio boundary. We describe a robust method to employ linear-in-descriptor machine learning potentials as a highly flexible embedding medium, precisely matching dislocation migration pathways whilst keeping at least the elastic properties constant. This advanced coupling allows dislocations to cross the ab initio boundary in fully three dimensional defect geometries. Investigating helium and vacancy segregation to edge and screw dislocations in tungsten, we find long-range relaxations qualitatively change impurity-induced core reconstructions compared to those in short periodic supercells. Our approach opens a vast range of mechanisms to ab initio investigation and provides new reference data to both validate and improve interatomic potentials.

For more details on this work please have a look on the description of the corresponding project or this preprint. Unfortunately I could not come to Baltimore to present the work myself due to unexpected visa issues, but I will be happy to answer any questions if you contact me directly by email.