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Data-driven direct diagnosis of li-ion batteries connected to photovoltaics

dc.contributor.authorDubarry, M.
dc.contributor.authorCosta Cortéz, Nahuel Alejandro 
dc.contributor.authorMatthews, D.
dc.date.accessioned2023-10-25T08:55:30Z
dc.date.available2023-10-25T08:55:30Z
dc.date.issued2023
dc.identifier.citationNature Communications, 14(1) (2023); doi:10.1038/s41467-023-38895-7
dc.identifier.issn2041-1723
dc.identifier.urihttps://hdl.handle.net/10651/70009
dc.description.sponsorshipThis research was funded by the Office of Naval Research (ONR), grant numbers N00014-19-1-2159 and N00014-22-1-2045. Nahuel Costa has been partially supported by the Ministry of Economy, Industry and Competitiveness (Ministerio de Economía, Industria y Competitividad) from Spain/FEDER under grant PID2020-112726-RB-I00 and by Principado de Asturias, grant SV-PA-21-AYUD/2021/50994.
dc.language.isoeng
dc.relation.ispartofNature Communications
dc.rights© The Author(s) 2023
dc.rightsCC Reconocimiento 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceScopus
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85160605482&doi=10.1038%2fs41467-023-38895-7&partnerID=40&md5=f8baaef6e751b065539cd9701a5ee3b8
dc.titleData-driven direct diagnosis of li-ion batteries connected to photovoltaics
dc.typejournal article
dc.identifier.doi10.1038/s41467-023-38895-7
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-112726RB-I00/ES/INTELIGENCIA COMPUTACIONAL PARA LA MITIGACION DE EMISIONES: NUEVAS METODOLOGIAS DE APRENDIZAJE CON DATOS INCOMPLETOS/
dc.relation.projectIDSV-PA-21-AYUD/2021/50994
dc.relation.publisherversionhttp://dx.doi.org/10.1038/s41467-023-38895-7
dc.rights.accessRightsopen access
dc.type.hasVersionVoR


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