Investigating microcrystalline cellulose crystallinity using Raman spectroscopy

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dc.contributor.authorQueiroz, Ana Luiza P.
dc.contributor.authorKerins, Brian M.
dc.contributor.authorYadav, Jayprakash
dc.contributor.authorFarag, Fatma
dc.contributor.authorFaisal, Waleed
dc.contributor.authorCrowley, Mary Ellen
dc.contributor.authorLawrence, Simon E.
dc.contributor.authorMoynihan, Humphrey A.
dc.contributor.authorHealy, Anne Marie
dc.contributor.authorVucen, Sonja
dc.contributor.authorCrean, Abina M.
dc.contributor.funderScience Foundation Irelanden
dc.contributor.funderEuropean Regional Development Funden
dc.date.accessioned2021-11-12T11:16:02Z
dc.date.available2021-11-12T11:16:02Z
dc.date.issued2021-07-27
dc.date.updated2021-11-10T09:40:13Z
dc.description.abstractMicrocrystalline cellulose (MCC) is a semi-crystalline material with inherent variable crystallinity due to raw material source and variable manufacturing conditions. MCC crystallinity variability can result in downstream process variability. The aim of this study was to develop models to determine MCC crystallinity index (%CI) from Raman spectra of 30 commercial batches using Raman probes with spot sizes of 100 µm (MR probe) and 6 mm (PhAT probe). A principal component analysis model separated Raman spectra of the same samples captured using the different probes. The %CI was determined using a previously reported univariate model based on the ratio of the peaks at 380 and 1096 cm−1. The univariate model was adjusted for each probe. The %CI was also predicted from spectral data from each probe using partial least squares regression models (where Raman spectra and univariate %CI were the dependent and independent variables, respectively). Both models showed adequate predictive power. For these models a general reference amorphous spectrum was proposed for each instrument. The development of the PLS model substantially reduced the analysis time as it eliminates the need for spectral deconvolution. A web application containing all the models was developed.en
dc.description.statusPeer revieweden
dc.description.versionPublished Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationQueiroz, A. L. P., Kerins, B. M., Yadav, J., Farag, F., Faisal, W., Crowley, M. E., Lawrence, S. E., Moynihan, H. A., Healy, A. M., Vucen, S. and Crean, A. M. (2021) 'Investigating microcrystalline cellulose crystallinity using Raman spectroscopy', Cellulose, 28(14), pp. 8971-8985. doi: 10.1007/s10570-021-04093-1en
dc.identifier.doi10.1007/s10570-021-04093-1en
dc.identifier.eissn1572-882X
dc.identifier.endpage8985en
dc.identifier.issn0969-0239
dc.identifier.issued14en
dc.identifier.journaltitleCelluloseen
dc.identifier.startpage8971en
dc.identifier.urihttps://hdl.handle.net/10468/12206
dc.identifier.volume28en
dc.language.isoenen
dc.publisherSpringer Nature Switzerland AGen
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2275/IE/Synthesis and Solid State Pharmaceutical Centre (SSPC)/en
dc.rights© 2021, the Authors. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subjectCrystallinityen
dc.subjectMicrocrystalline celluloseen
dc.subjectPartial least square regressionen
dc.subjectR Shinyen
dc.subjectRaman spectroscopyen
dc.titleInvestigating microcrystalline cellulose crystallinity using Raman spectroscopyen
dc.typeArticle (peer-reviewed)en
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