Artificial intelligence-engineering magnetic materials
| dc.contributor.author | PERIGO, ELIO A. | pt_BR |
| dc.contributor.author | FARIA, RUBENS N. de | pt_BR |
| dc.coverage | Internacional | pt_BR |
| dc.date.accessioned | 2021-10-27T19:06:38Z | |
| dc.date.available | 2021-10-27T19:06:38Z | |
| dc.date.issued | 2021 | pt_BR |
| dc.description.abstract | The 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.extent | 1-11 | pt_BR |
| dc.identifier.citation | PERIGO, 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.doi | 10.3390/magnetochemistry7060084 | pt_BR |
| dc.identifier.fasciculo | 6 | pt_BR |
| dc.identifier.issn | 2312-7481 | pt_BR |
| dc.identifier.percentilfi | 49.72 | pt_BR |
| dc.identifier.percentilfiCiteScore | 47.33 | |
| dc.identifier.uri | http://repositorio.ipen.br/handle/123456789/32308 | |
| dc.identifier.vol | 7 | pt_BR |
| dc.relation.ispartof | Magnetochemistry | pt_BR |
| dc.rights | openAccess | pt_BR |
| dc.subject | magnetic materials | |
| dc.subject | programming | |
| dc.subject | artificial intelligence | |
| dc.subject | artificial intelligence | |
| dc.subject | amorphous state | |
| dc.subject | machine learning | |
| dc.title | Artificial intelligence-engineering magnetic materials | pt_BR |
| dc.type | Artigo de periódico | pt_BR |
| dspace.entity.type | Publication | |
| ipen.autor | RUBENS NUNES DE FARIA JUNIOR | |
| ipen.codigoautor | 227 | |
| ipen.contributor.ipenauthor | RUBENS NUNES DE FARIA JUNIOR | |
| ipen.date.recebimento | 21-10 | |
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| ipen.identifier.fiCiteScore | 3.0 | |
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| ipen.identifier.iwos | WoS | pt_BR |
| ipen.identifier.ods | 9 | |
| ipen.range.fi | 3.000 - 4.499 | |
| ipen.range.percentilfi | 25.00 - 49.99 | |
| ipen.subtitulo | current status and a brief perspective | pt_BR |
| ipen.type.genre | Artigo | |
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| relation.isAuthorOfPublication.latestForDiscovery | 20cb7788-3957-4550-9e5c-cf7f5261eec4 | |
| sigepi.autor.atividade | FARIA, RUBENS N. de:227:730:N | pt_BR |