Hyperspectral near infrared imaging quantifies the heterogeneity of carbon materials

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Mäkelä, Mikko
dc.contributor.author Geladi, Paul
dc.date.accessioned 2018-08-08T10:00:39Z
dc.date.available 2018-08-08T10:00:39Z
dc.date.issued 2018-12-01
dc.identifier.citation Mäkelä , M & Geladi , P 2018 , ' Hyperspectral near infrared imaging quantifies the heterogeneity of carbon materials ' Scientific Reports , vol 8 , no. 1 , 10442 . DOI: 10.1038/s41598-018-28889-7 en
dc.identifier.issn 2045-2322
dc.identifier.other PURE UUID: 3b9ae66b-b55d-4c18-9fb6-70e2fd0aad62
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/hyperspectral-near-infrared-imaging-quantifies-the-heterogeneity-of-carbon-materials(3b9ae66b-b55d-4c18-9fb6-70e2fd0aad62).html
dc.identifier.other PURE LINK: http://www.scopus.com/inward/record.url?scp=85049898373&partnerID=8YFLogxK
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/26959850/CHEM_M_kel_Geladi_Hyperspectral_near_2018_Scientific_Reports.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/33058
dc.description.abstract For many applications heterogeneity is a direct indicator of material quality. Reliable determination of chemical heterogeneity is however not a trivial task. Spectral imaging can be used for determining the spatial distribution of an analyte in a sample, thus transforming each pixel of an image into a sampling cell. With a large amount of image pixels, the results can be evaluated using large population statistics. This enables robust determination of heterogeneity in biological samples. We show that hyperspectral imaging in the near infrared (NIR) region can be used to reliably determine the heterogeneity of renewable carbon materials, which are promising replacements for current fossil alternatives in energy and environmental applications. This method allows quantifying the variation in renewable carbon and other biological materials that absorb in the NIR region. Reliable determination of heterogeneity is also a valuable tool for a wide range of other chemical imaging applications. en
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries Scientific Reports en
dc.relation.ispartofseries Volume 8, issue 1 en
dc.rights openAccess en
dc.subject.other General en
dc.subject.other 215 Chemical engineering en
dc.title Hyperspectral near infrared imaging quantifies the heterogeneity of carbon materials en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Clean Technologies
dc.contributor.department Swedish University of Agricultural Sciences
dc.contributor.department Department of Bioproducts and Biosystems en
dc.subject.keyword General
dc.subject.keyword 215 Chemical engineering
dc.identifier.urn URN:NBN:fi:aalto-201808084458
dc.identifier.doi 10.1038/s41598-018-28889-7
dc.type.version publishedVersion

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