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The analysis of defects and defect dynamics in crystalline materials isimportant for fundamental science and for a wide range of applied engineering.With increasing system size the analysis of molecular-dynamics simulation databecomes non-trivial. Here, we present a workflow for semi-automaticidentification and classification of defects in crystalline structures,combining a new approach for defect description with several already existingopen-source software packages. Our approach addresses the key challenges posedby the often relatively tiny volume fraction of the modified parts of thesample, thermal motion and the presence of potentially unforeseen atomicconfigurations (defect types) after irradiation. The local environment of anyatom is converted into a rotation-invariant descriptive vector ('fingerprint'),which can be compared to known defect types and also yields a distance metricsuited for classification. Vectors which cannot be associated to knownstructures indicate new types of defects. As proof-of-concept we apply ourmethod on an iron sample to analyze the defects caused by a collision cascadeinduced by a 10 keV primary-knock-on-atom. The obtained results are in goodagreement with reported literature values.

FaVAD: A software workflow for characterisation and visualizing of defects in crystalline structures