Deep learning detection of topological defects in confined two-dimensional nematics

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dc.contributor.authorIgnacio Palos-Reynoso
dc.contributor.authorHumberto Híjar
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T19:59:01Z
dc.date.available2026-03-22T19:59:01Z
dc.date.issued2026
dc.identifier.doi10.1016/j.commatsci.2026.114508
dc.identifier.urihttps://doi.org/10.1016/j.commatsci.2026.114508
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/79291
dc.language.isoen
dc.publisherElsevier BV
dc.relation.ispartofComputational Materials Science
dc.sourceUniversidad La Salle
dc.subjectTopological defect
dc.subjectMesoscopic physics
dc.subjectLiquid crystal
dc.subjectTopology (electrical circuits)
dc.subjectDeep learning
dc.subjectConvolutional neural network
dc.subjectArtificial neural network
dc.subjectArtificial intelligence
dc.subjectPhysics
dc.subjectComputer science
dc.titleDeep learning detection of topological defects in confined two-dimensional nematics
dc.typearticle

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