New Method for Determining the Degree of Cellulose I Crystallinity by Means of FT Raman Spectroscopy

Schenzel, Karla; Fischer, Steffen; Brendler, Erica

doi:10.1007/s10570-004-3885-6

Cited by 168 publications

(115 citation statements)

References 18 publications

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“…Crystallinity measurements using Raman on semicrystalline polymers including cellulose (Stuart 1995;Paradkar et al 2003;Schenzel et al 2005) have been performed. The principle behind Raman methodology is the same as in FT-IR and NMR and has to do with using the spectral features whose intensity, bandwidth, and/or position are affected by crystallinity.…”

Section: Introductionmentioning

confidence: 99%

“…The principle behind Raman methodology is the same as in FT-IR and NMR and has to do with using the spectral features whose intensity, bandwidth, and/or position are affected by crystallinity. To develop FT-Raman-based cellulose I crystallinity quantitation method, Schenzel et al (2005) used the weak bands at 1,462 and 1,481 cm -1 (CH 2 bending modes) in conjunction with spectral deconvolution. However, considering that the intensities of the selected bands are quite low and that the process of deconvolution is not free of the band fitting problems (Maddams 1980;Meier 2005), a better approach is desired.…”

Section: Introductionmentioning

confidence: 99%

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Cellulose I crystallinity determination using FT–Raman spectroscopy: univariate and multivariate methods

2010

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Two new methods based on FT-Raman spectroscopy, one simple, based on band intensity ratio, and the other using a partial least squares (PLS) regression model, are proposed to determine cellulose I crystallinity. In the simple method, crystallinity in cellulose I samples was determined based on univariate regression that was first developed using the Raman band intensity ratio of the 380 and 1,096 cm -1 bands. For calibration purposes, 80.5% crystalline and 120-min milled (0% crystalline) Whatman CC31 and six cellulose mixtures produced with crystallinities in the range 10.9-64% were used. When intensity ratios were plotted against crystallinities of the calibration set samples, the plot showed a linear correlation (coefficient of determination R 2 = 0.992). Average standard error calculated from replicate Raman acquisitions indicated that the cellulose Raman crystallinity model was reliable. Crystallinities of the cellulose mixtures samples were also calculated from X-ray diffractograms using the amorphous contribution subtraction (Segal) method and it was found that the Raman model was better. Additionally, using both Raman and X-ray techniques, sample crystallinities were determined from partially crystalline cellulose samples that were generated by grinding Whatman CC31 in a vibratory mill. The two techniques showed significant differences. In the second approach, successful Raman PLS regression models for crystallinity, covering the 0-80.5% range, were generated from the ten calibration set Raman spectra. Both univariateRaman and WAXS determined crystallinities were used as references. The calibration models had strong relationships between determined and predicted crystallinity values (R 2 = 0.998 and 0.984, for univariateRaman and WAXS referenced models, respectively). Compared to WAXS, univariate-Raman referenced model was found to be better (root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) values of 6.1 and 7.9% vs. 1.8 and 3.3%, respectively). It was concluded that either of the two Raman methods could be used for cellulose I crystallinity determination in cellulose samples.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cellulose I crystallinity determination using FT–Raman spectroscopy: univariate and multivariate methods

2010

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“…Even at higher NaOH concentrations (18.25% or 27.5%) there was an appreciable extent of gel formation in CMC water solutions if the initial pulp had a high fraction of cellulose II. The cellulose crystallinity after the carboxymethylation reaction was quantified by analysing the FT Raman spectral data of the samples, using the models described earlier (Schenzel and Fischer 2005;Schenzel et al 2009). In this manner, the contents of crystalline and amorphous cellulose in the original dissolving pulp as well as the average content of cellulose I / cellulose II before and after its alkaline pre-treatment and in the CMC samples were determined.…”

Section: Resultsmentioning

confidence: 99%

Carboxymethyl Cellulose Produced at Different Mercerization Conditions and Characterized by NIR FT Raman Spectroscopy in Combination with Multivariate Analytical Methods

2013

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aCarboxymethyl cellulose (CMC) is produced commercially in a two-stage process consisting of a mercerization stage followed by an etherification stage. In this work, extended mercerization stages were used when producing CMC from a spruce dissolving pulp. Near infra-red (NIR) Fourier transform (FT) Raman spectroscopy was used to analyse the molecular structures of the CMC and the gel fractions formed in the CMC preparation. Three different CMC groups were obtained, representing backbone structures of cellulose I, cellulose II, and amorphous cellulose. By applying principal component analyses (PCA) to the spectral data, two CMC classes were identified with different degrees of substitution (DS). Thus, a low degree of substitution was obtained in the CMC if the alkaline concentration in the mercerization stage was only 9.0%, and the backbone structure was cellulose I or II. However, if the alkaline concentration was higher (18.25% or 27.5%), then the degree of substitution in the CMC was also higher, and the backbone structure was more amorphous.

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“…The crystallinity of cellulose plays an important role in the accessibility and longevity of cellulosic fiber (Awadel-Karim et al 1999;Schenzel et al 2005). Li and Pickering (2008) and Nasir et al (2013a) studied the effect of laccase on cellulosic fiber and observed an up to 22% and 10% increase in the crystallinity index, respectively.…”

Section: Crystallinity Index Improvementmentioning

confidence: 99%

Laccase, an Emerging Tool to Fabricate Green Composites: A Review

Mahmood¹,

Hashim²,

Sulaiman³

et al. 2015

BioResources

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In the last two decades, laccases have received much attention from researchers because of their specific ability to oxidize lignin. This function of laccase is very useful for applications in several biotechnological processes, including delignification in the pulp and paper industry and the detoxification of industrial effluents from the textile and petrochemical industries. This review focuses on laccase-mediated fiberboard synthesis. Growing concerns regarding the emission of formaldehyde from wood composites has prompted industrialists to consider the fabrication of green composites. Laccase-mediated fiber treatments oxidize the lignin component without affecting the cellulose structure. As a result, free radicals are generated on the fiber surface, and these can act as potential reactive sites for further cross-linking reactions in board manufacturing. Binderless fiberboards prepared using such methods can be considered as green composites because the manufacturing process involves no additional resin.

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New Method for Determining the Degree of Cellulose I Crystallinity by Means of FT Raman Spectroscopy

Cited by 168 publications

References 18 publications

Cellulose I crystallinity determination using FT–Raman spectroscopy: univariate and multivariate methods

Cellulose I crystallinity determination using FT–Raman spectroscopy: univariate and multivariate methods

Carboxymethyl Cellulose Produced at Different Mercerization Conditions and Characterized by NIR FT Raman Spectroscopy in Combination with Multivariate Analytical Methods

Laccase, an Emerging Tool to Fabricate Green Composites: A Review

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