A fast and accurate near infrared spectroscopy method for the determination of cellulose content of alkali cellulose applicable for process control (original) (raw)
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Cellulose, 2017
The amount of secondary cell wall (SCW) cellulose in the fiber affects the quality and commercial value of cotton. Accurate assessments of SCW cellulose are essential for improving cotton fibers. Fourier transform infrared (FT-IR) spectroscopy enables distinguishing SCW from other cell wall components in a rapid and non-invasive way. Thus it has been used for monitoring SCW development in model plants. Recently, several FT-IR methods have been proposed for monitoring cotton fiber development. However, they are rarely utilized for assessing SCW cellulose from cotton fiber due to limited validation with various cotton species grown in different conditions. Thus, we compared and validated three FT-IR methods including two previously proposed methods analyzing entire spectra or specific bands as well as a new method analyzing FT-IR spectral regions corresponding to cellulose with various cotton fibers grown in planta and in vitro. Comparisons of the FT-IR methods with reference methods showed that the two FT-IR methods analyzing the entire spectra or cellulose regions by principal component analysis monitored SCW qualitatively, whereas the FT-IR method analyzing specific bands (708, 730, and 800 cm-1) by a simple algorithm allowed the monitoring of SCW cellulose levels quantitatively. The quantitative FT-IR method is a potential substitute for lengthy and laborious chemical assays for monitoring SCW cellulose levels from cotton fibers, and it can be used for a better understanding of cotton fiber SCW development and as a part of the quality assessment tools used to guide choices for improving fiber quality. Keywords Attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopy Á Cotton fiber property Á Cellulose Á Crystallinity Á Secondary cell wall (SCW)
Effect of the chemical treatments on the characteristics of natural cellulose
2014
In order to characterize the morphology and size distribution of the cellulose fibers, natural cellulose from kenaf bast fibers was extracted using two chemical treatments; (1) alkali-bleaching-ultrasonic treatment and (2) alkalibleaching-hydrolysis. Solutions of NaOH, H 2 O 2 and H 2 SO 4 were used for alkalization, bleaching and hydrolysis, respectively. The hydrolyzed fibers were centrifuged at a rotation speed of 10000 rpm for 10 min to separate the nanofibers from the microfibers. The separation was repeated in 7 steps by controlling pH of the solution in each step until neutrality was reached. Fourier transform infrared (FTIR) spectroscopy was performed on the fibers at the final step of each treatment: i.e. either ultrasonic treated-or hydrolyzed microfibers. Their FTIR spectra were compared with FTIR spectrum of a reference commercial α-cellulose. Changes in morphology and size distribution of the treated fibers were examined by scanning electron microscopy (SEM). FTIR spectra of ultrasonic treated-and hydrolyzed microfibers nearly coincided with the FTIR spectrum of commercial α-cellulose, suggesting successful extraction of cellulose. Ultrasonic treatment for 6 h resulted in a specific morphology in which cellulose nanofibers (≥100 nm) were distributed across the entire surface of cellulose microfibers (5 m). Constant magnetic stirring combined with acid hydrolysis resulted in an inhomogeneous size distribution of both cellulose rods (500 nm-3 m length, 100-200 nm diameter) and particles 100-200 nm in size. Changes in morphology of the cellulose fibers depended upon the stirring time; longer stirring time resulted in shorter fiber lengths.
Near infrared spectroscopy for estimating sugarcane bagasse content in medium density fiberboard
BioResources, 2011
Medium density fiberboard (MDF) is an engineered wood product formed by breaking down selected lignin-cellulosic material residuals into fibers, combining it with wax and a resin binder, and then forming panels by applying high temperature and pressure. Because the raw material in the industrial process is ever-changing, the panel industry requires methods for monitoring the composition of their products. The aim of this study was to estimate the ratio of sugarcane (SC) bagasse to Eucalyptus wood in MDF panels using near infrared (NIR) spectroscopy. Principal component analysis (PCA) and partial least square (PLS) regressions were performed. MDF panels having different bagasse contents were easily distinguished from each other by the PCA of their NIR spectra with clearly different patterns of response. The PLS-R models for SC content of these MDF samples presented a strong coefficient of determination (0.96) between the NIR-predicted and Lab-determined values and a low standard error of prediction (~1.5%) in the cross-validations. A key role of resins (adhesives), cellulose, and lignin for such PLS-R calibrations was shown. PLS-DA model correctly classified ninety-four percent of MDF samples by cross-validations and ninety-eight percent of the panels by independent test set. These NIR-based models can be useful to quickly estimate sugarcane bagasse vs. Eucalyptus wood content ratio in unknown MDF samples and to verify the quality of these engineered wood products in an online process.
Cellulose, 2010
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 univariate-Raman 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 univariate-Raman 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.
Carbohydrate Polymers, 2012
Rapid and quantitative measurements of cellulose concentrations in ionic liquids (ILs) are difficult. In this study, FTIR operated in attenuated total reflectance (ATR) mode was investigated as a tool to measure cellulose concentration in 1-ethyl-3-methylimidazolium acetate ([emim][OAc]) and the spectra were subjected to partial least squares (PLS) regression for the quantitative determination of cellulose content. Additionally, the spectra were subjected to 7 data preprocessing methods to reduce physical effects in the spectra. Peak normalization was found to be the technique that most improved the prediction of dissolved cellulose in [emim] [OAc]. When peak normalization was used for data preprocessing, a model for the quantitative estimation of cellulose content between 0 wt.% and 4 wt.% with an error of 0.53 wt.% was generated. The methods described here provide the basis for a rapid and facile technique for the determination of dissolved cellulose content in [emim] [OAc].
Modeling and Molecular Spectroscopic Analyses of Cellulose
Journal of Applied Solution Chemistry and Modeling,, 2014
Cellulose is the most abundant biopolymer which is a topic of extensive research work. In this study Fourier Transform Infrared Spectroscopy (FTIR) was utilized to assign the molecular structure of cellulose. B3LYP at 3-21g**, 6-31g** and LANL1DZ then MP2 at 6-31g* levels of theories were conducted to compare the calculated vibrational spectra with the FTIR spectrum. Model molecules of cellulose starting with monomer up to cellulose 18 units were studied with PM3 semiemperical method in order to follow up the effect of polymerization upon some selected physical parameters. Results indicate that final heat of formation and band gap energy have decreased with increasing cellulose units while total dipole moment has increased with increasing cellulose units. It is concluded that the reactivity of cellulose has increased with increasing the units also the unique hydrogen bonding dedicates cellulose to several applications.
2017
The effects of combined scouring-bleaching and reactive dyeing were investigated by characterizing the functional groups changed of cotton, betel nut, banana and jute fibers using caustic soda, Hydrogen peroxide and reactive dyestuffs. FTIR ATR spectroscopy provided a fast and semi-quantitative assessment of the removal of pectin, lignin, Hemicelluloses, oil, waxes etc on those fibers surface by comparing the changes in intensity of the carbonyl peak induced by Hydrogen peroxide and caustic soda treatments well as bond changing in reactive dyeing around 4000 cm -1 . Above all fibers are not reacting identically during changing impurities and covalent bond forming between cellulose and reactive dyes.
Differentiating between Natural and Modified Cellulosic Fibres Using ATR-FTIR Spectroscopy
Heritage
This paper presents the limitations and potential of ATR-FTIR spectroscopy applied to the study of cellulosic textile collections. The technique helps to differentiate natural fibres according to the content of lignin, pectin, hemicellulose, and wax, although some problematic issues should be considered. The spectral differences derived from the environmental humidity uptake and the plant composition are reviewed and discussed in the light of new experimental data. Diagnostic bands are proposed that can discriminate between different fibres from different plants. The contribution of ageing is also considered, demonstrating that sometimes aged fibres cannot be reliably recognised. In contrast, the potential of ATR-FTIR spectroscopy to discriminate between natural and modified fibres is discussed and proven. The best results were obtained when microinvasive ATR-FTIR spectroscopy was coupled with SEM observations. The proposed protocol was tested on microsamples of various cellulosic m...