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Infrared

Determination of Cellulose, Water, and N-Methylmorpholine N-Oxide during the Production of Lyocell by Attenuated Total Reflection (ATR) – Fourier Transform Infrared (FTIR) Spectroscopy

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Pages 388-398 | Received 21 Jan 2021, Accepted 18 May 2021, Published online: 08 Jun 2021
 

Abstract

Attenuated total reflection (ATR) – Fourier transform infrared (FTIR) spectroscopy with the pretreatment of converting the absorption spectrum into angle spectrum (CASAS) and partial least squares (PLS) was employed to rapidly and simultaneously determine the ingredients of cellulose slurries and solutions during lyocell production. ATR was employed to rapidly and conveniently collect the spectra of the swollen slurries and viscous solutions during production. CASAS was used to eliminate the influence on modeling by the optical path differences due to uneven ingredient distributions in the samples. The PLS models for the cellulose, water, and N-methylmorpholine N-oxide (NMMO) concentrations of the cellulose slurry/solution were constructed using the raw spectra, pretreated spectra by CASAS, and common pretreatment methods, respectively. The results show that CASAS eliminates interferences due to the differences in optical path and improves the performance of PLS model for each analyte. The standard errors of prediction (SEP) of models using CASAS for cellulose, NMMO, and water concentration of cellulose slurry were 0.368, 0.196 and 0.171, while the values for the cellulose solution were 0.442, 0.353, and 0.066, respectively. The standard errors of prediction (SEPs) of CASAS models are significantly lower than the reproducibility requirement of the reference method, 0.5. The reported approach using ATR-FTIR spectroscopy combined with CASAS and PLS is rapid and accurate for determining the ingredients of the cellulose slurries and solutions and offers potential for identifying similar samples.

Disclosure statement

The authors declare no conflicts of interest.

Additional information

Funding

The support from Beijing Science and Technology Plan Project (grant Z181100009318010) is greatly appreciated.

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