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.
The energy ranges consid- ered here are listed in Table S1 in Supplementary Mate- rials, and the width of an energy bin for constructing the histogram is set to 1 eV
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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.