Machine learning on dislocation loop energies reveals a single universal irregularity parameter that controls both thermodynamic properties and self-climb dynamics of non-compact prismatic loops.
This constraint effectively prevents the models from producing unphysical, abnormally large values ofE i [111], which might arise due to limited ex- trapolation capability
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Thermodynamics and dynamics of non-compact prismatic dislocation loops simulated using a machine-learning model
Machine learning on dislocation loop energies reveals a single universal irregularity parameter that controls both thermodynamic properties and self-climb dynamics of non-compact prismatic loops.