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Article Dans Une Revue Computational Materials Science Année : 2023

MultiSOM: Multi-layer Self Organizing Maps for local structure identification in crystalline structures

Franco Aquistapace
Nicolás Amigo
  • Fonction : Auteur
Orlando Deluigi
  • Fonction : Auteur
Eduardo Bringa

Résumé

Identification of defects in crystalline structures is of vital importance when describing the plastic behavior of metals. Despite the increasing number of tools available in the literature, additional techniques are still required to classify different types of defects. Here we present a novel tool based on Multi-layer Self Organizing Maps (MultiSOM), which can be employed in the identification of vacancies, dislocations and free surfaces at the atomic scale. Three case-studies were analyzed and the performance of MultiSOM was compared to traditional tools, such as common neighbor analysis and polyhedral template matching, revealing that our algorithm is able to identify local structures while other methods are unable to. We demonstrate that excellent results can be obtained for identifying local structural patterns in solids through the MultiSOM framework when combining per-atom properties such as coordination numbers and centrosymmetry parameter; though alone, each property is insufficient. Overall, MultiSOM is an open-source software, that works under the Python programming language with user-selected features.

Domaines

Matériaux
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Dates et versions

hal-04106720 , version 1 (25-05-2023)

Identifiants

Citer

Franco Aquistapace, Nicolás Amigo, Javier Troncoso, Orlando Deluigi, Eduardo Bringa. MultiSOM: Multi-layer Self Organizing Maps for local structure identification in crystalline structures. Computational Materials Science, 2023, 227, pp.112263. ⟨10.1016/j.commatsci.2023.112263⟩. ⟨hal-04106720⟩
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