Artificial intelligence-engineering magnetic materials

dc.contributor.authorPERIGO, ELIO A.pt_BR
dc.contributor.authorFARIA, RUBENS N. dept_BR
dc.coverageInternacionalpt_BR
dc.date.accessioned2021-10-27T19:06:38Z
dc.date.available2021-10-27T19:06:38Z
dc.date.issued2021pt_BR
dc.description.abstractThe implementation of artificial intelligence into the research and development of (currently) the most economically relevant classes of engineering hard and soft magnetic materials is addressed. Machine learning is nowadays the key approach utilized in the discovery of new compounds, physical–chemical properties prediction, microstructural/magnetic characterization, and applicability of permanent magnets and crystalline/amorphous soft magnetic alloys. Future opportunities are envisioned on at least two fronts: (a) ultra-low losses materials, as well as processes that enable their manufacturing, unlocking the next step for higher efficiency electrification, power conversion, and distribution; (b) additively manufactured magnetic materials by predicting and developing novel powdered materials properties, generative design concepts, and optimal processing conditions.pt_BR
dc.format.extent1-11pt_BR
dc.identifier.citationPERIGO, ELIO A.; FARIA, RUBENS N. de. Artificial intelligence-engineering magnetic materials: current status and a brief perspective. <b>Magnetochemistry</b>, v. 7, n. 6, p. 1-11, 2021. DOI: <a href="https://dx.doi.org/10.3390/magnetochemistry7060084">10.3390/magnetochemistry7060084</a>. Disponível em: http://repositorio.ipen.br/handle/123456789/32308.
dc.identifier.doi10.3390/magnetochemistry7060084pt_BR
dc.identifier.fasciculo6pt_BR
dc.identifier.issn2312-7481pt_BR
dc.identifier.percentilfi49.72pt_BR
dc.identifier.percentilfiCiteScore47.33
dc.identifier.urihttp://repositorio.ipen.br/handle/123456789/32308
dc.identifier.vol7pt_BR
dc.relation.ispartofMagnetochemistrypt_BR
dc.rightsopenAccesspt_BR
dc.subjectmagnetic materials
dc.subjectprogramming
dc.subjectartificial intelligence
dc.subjectartificial intelligence
dc.subjectamorphous state
dc.subjectmachine learning
dc.titleArtificial intelligence-engineering magnetic materialspt_BR
dc.typeArtigo de periódicopt_BR
dspace.entity.typePublication
ipen.autorRUBENS NUNES DE FARIA JUNIOR
ipen.codigoautor227
ipen.contributor.ipenauthorRUBENS NUNES DE FARIA JUNIOR
ipen.date.recebimento21-10
ipen.identifier.fi3.336pt_BR
ipen.identifier.fiCiteScore3.0
ipen.identifier.ipendoc28076pt_BR
ipen.identifier.iwosWoSpt_BR
ipen.identifier.ods9
ipen.range.fi3.000 - 4.499
ipen.range.percentilfi25.00 - 49.99
ipen.subtitulocurrent status and a brief perspectivept_BR
ipen.type.genreArtigo
relation.isAuthorOfPublication20cb7788-3957-4550-9e5c-cf7f5261eec4
relation.isAuthorOfPublication.latestForDiscovery20cb7788-3957-4550-9e5c-cf7f5261eec4
sigepi.autor.atividadeFARIA, RUBENS N. de:227:730:Npt_BR

Pacote Original

Agora exibindo 1 - 1 de 1
Carregando...
Imagem de Miniatura
Nome:
28076.pdf
Tamanho:
4.96 MB
Formato:
Adobe Portable Document Format
Descrição:

Licença do Pacote

Agora exibindo 1 - 1 de 1
Carregando...
Imagem de Miniatura
Nome:
license.txt
Tamanho:
1.71 KB
Formato:
Item-specific license agreed upon to submission
Descrição:

Coleções