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.
(19) effectively sepa- ratesFinto ground-state configurational contributions, characterised byη, and the size-dependent terms, char- acterised by parametersαandτ
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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.