Films based on crosslinked TEMPO-oxidized cellulose and predictive analysis via machine learning

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorÖzkan, Merveen_US
dc.contributor.authorBorghei, Maryamen_US
dc.contributor.authorKarakoç, Alpen_US
dc.contributor.authorRojas, Orlando J.en_US
dc.contributor.authorPaltakari, Jounien_US
dc.contributor.departmentDepartment of Bioproducts and Biosystemsen
dc.contributor.groupauthorPaper Converting and Packagingen
dc.contributor.groupauthorBio-based Colloids and Materialsen
dc.date.accessioned2018-05-22T14:48:41Z
dc.date.available2018-05-22T14:48:41Z
dc.date.issued2018-12-01en_US
dc.description.abstractWe systematically investigated the effect of film-forming polyvinyl alcohol and crosslinkers, glyoxal and ammonium zirconium carbonate, on the optical and surface properties of films produced from TEMPO-oxidized cellulose nanofibers (TOCNFs). In this regard, UV-light transmittance, surface roughness and wetting behavior of the films were assessed. Optimization was carried out as a function of film composition following the "random forest" machine learning algorithm for regression analysis. As a result, the design of tailor-made TOCNF-based films can be achieved with reduced experimental expenditure. We envision this approach to be useful in facilitating adoption of TOCNF for the design of emerging flexible electronics, and related platforms.en
dc.description.versionPeer revieweden
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationÖzkan, M, Borghei, M, Karakoç, A, Rojas, O J & Paltakari, J 2018, ' Films based on crosslinked TEMPO-oxidized cellulose and predictive analysis via machine learning ', Scientific Reports, vol. 8, no. 1, 4748 . https://doi.org/10.1038/s41598-018-23114-xen
dc.identifier.doi10.1038/s41598-018-23114-xen_US
dc.identifier.issn2045-2322
dc.identifier.otherPURE UUID: cd37fc95-fe7e-4b69-a7fc-b858b9feaf19en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/cd37fc95-fe7e-4b69-a7fc-b858b9feaf19en_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85044281478&partnerID=8YFLogxKen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/18975708/CHEM_Ozkan_et_al_Films_based_Scientific_Reports_2018.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/31175
dc.identifier.urnURN:NBN:fi:aalto-201805222615
dc.language.isoenen
dc.relation.ispartofseriesScientific Reportsen
dc.relation.ispartofseriesVolume 8, issue 1en
dc.rightsopenAccessen
dc.titleFilms based on crosslinked TEMPO-oxidized cellulose and predictive analysis via machine learningen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
dc.type.versionpublishedVersion
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