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Please use this identifier to cite or link to this item: http://hdl.handle.net/1843/64084
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dc.creatorPaulo Henrique Ribeiro Amaralpt_BR
dc.creatorJosé Rachid Mohallempt_BR
dc.date.accessioned2024-02-16T17:35:29Z-
dc.date.available2024-02-16T17:35:29Z-
dc.date.issued2020-
dc.citation.volume102pt_BR
dc.citation.issue5pt_BR
dc.citation.spage052808-1pt_BR
dc.citation.epage052808-5pt_BR
dc.identifier.doihttps://doi.org/10.1103/PhysRevA.102.052808pt_BR
dc.identifier.issn2469-9934pt_BR
dc.identifier.urihttp://hdl.handle.net/1843/64084-
dc.description.resumoMachine-learning techniques are used to check the theoretical and experimental predictions of positron binding to general molecules. The bound or unbound character of previous calculations for polar molecules are mostly confirmed. Binding for so far unexplored polar molecules is predicted. For apolar molecules, a formula for the binding energy in terms of isotropic polarizability and ionization potential is obtained, leading to unprecedented agreement with experiments as well as prediction of previously unidentified bound systems. The role of the ionization potential is suggested as a consequence of enhanced formation of virtual positronium at short distances.pt_BR
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológicopt_BR
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superiorpt_BR
dc.languageengpt_BR
dc.publisherUniversidade Federal de Minas Geraispt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.departmentICX - DEPARTAMENTO DE FÍSICApt_BR
dc.publisher.initialsUFMGpt_BR
dc.relation.ispartofPhysical Review A-
dc.rightsAcesso Restritopt_BR
dc.subjectMachine learningpt_BR
dc.subjectPositron complexespt_BR
dc.subjectIonization potentialpt_BR
dc.subject.otherElétronspt_BR
dc.titleMachine learning predictions of positron binding to moleculespt_BR
dc.typeArtigo de Periódicopt_BR
dc.url.externahttps://journals.aps.org/pra/abstract/10.1103/PhysRevA.102.052808pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0003-0799-4143pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-4776-4417pt_BR
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