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dc.date.accessioned2021-04-28T19:23:23Z
dc.date.available2021-04-28T19:23:23Z
dc.date.created2020-01-06T10:51:09Z
dc.date.issued2019
dc.identifier.citationRemonato, Filippo Løvvik, Ole Martin Flage-Larsen, Espen . Effectiveness of Neural Networks for Research on Novel Thermoelectric Materials. A Proof of Concept.. Nordic Artificial Intelligence Research and Development: Third Symposium of the Norwegian AI Society, NAIS 2019. 2019, 69-77 Springer
dc.identifier.urihttp://hdl.handle.net/10852/85705
dc.description.abstractThis paper describes the application of neural network approaches to the discovery of new materials exhibiting thermoelectric properties. Thermoelectricity is the ability of a material to convert energy from heat to electricity. At present, only few materials are known to have this property to a degree which is interesting for use in industrial applications like, for example, large-scale energy harvesting [3, 8]. We employ a standard neural network architecture with supervised learning on a training dataset representing materials and later predict the properties on a disjoint test set. At this proof of concept stage, both sets are synthetically generated with plausible values of the features. A substantial increase in performance is seen when utilising available physical knowledge in the machine learning model. The results show that this approach is feasible and ready for future tests with experimental laboratory data.
dc.languageEN
dc.publisherSpringer
dc.relation.ispartofCommunications in Computer and Information Science
dc.relation.ispartofseriesCommunications in Computer and Information Science
dc.titleEffectiveness of Neural Networks for Research on Novel Thermoelectric Materials. A Proof of Concept.
dc.typeChapter
dc.creator.authorRemonato, Filippo
dc.creator.authorLøvvik, Ole Martin
dc.creator.authorFlage-Larsen, Espen
cristin.unitcode185,15,4,40
cristin.unitnameStrukturfysikk
cristin.ispublishedtrue
cristin.fulltextpostprint
dc.identifier.cristin1766634
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.btitle=Nordic Artificial Intelligence Research and Development: Third Symposium of the Norwegian AI Society, NAIS 2019&rft.spage=69&rft.date=2019
dc.identifier.startpage69
dc.identifier.endpage77
dc.identifier.pagecount148
dc.identifier.doihttp://doi.org/10.1007/978-3-030-35664-4_7
dc.identifier.urnURN:NBN:no-88365
dc.type.documentBokkapittel
dc.type.peerreviewedPeer reviewed
dc.source.isbn978-3-030-35664-4
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/85705/1/Remonato2019effectiveness.pdf
dc.type.versionAcceptedVersion
cristin.btitleNordic Artificial Intelligence Research and Development: Third Symposium of the Norwegian AI Society, NAIS 2019
dc.relation.projectNOTUR/NORSTORE/NN2615K


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