Abstract

The near infrared (NIR) spectroscopy presents itself as an interesting non-destructive test tool as it enables a fast, simple and reliable way for characterizing large samplings of biological materials in a short period of time. This work aimed to establish multivariate models to estimate the crystallinity indices and tensile and burst strength of cellulosic and nanocellulosic films through NIR spectroscopy. NIR spectra were recorded from the films before tensile and bursting strength, and crystallinity tests. Spectral information were correlated with reference values obtained by laboratory procedures through partial least square regression (PLS-R). The PLS-R model for estimating the crystallinity index presented a coefficient of determination in cross-validation (R2cv) of 0,94 and the ratio of performance to deviation (RPD) was 3,77. The mechanical properties of the films presented a high correlation with the NIR spectra: R2p = 0,85 (RPD = 2,23) for tensile and R2p = 0,93 (RPD = 3,40) for burst strength. The statistics associated to the models presented have shown that the NIR spectroscopy has the potential to estimate the crystallinity index and resistance properties of cellulose and nanocellulose films on in-line monitoring systems.

Highlights

  • The development of products from new technologies can create important breakthroughs in various sectors

  • The magnitude range of the first derivative Near Infrared (NIR) spectra is higher in unbleached materials (Figure 1b) because these materials present a Kappa number of 51,7 and, are darker

  • The results presented in this study show that NIR Spectroscopy and least square regression present the potential to predict the crystallinity index, and tensile and burst properties of nanocellulosic and cellulosic films

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Summary

Introduction

The development of products from new technologies can create important breakthroughs in various sectors. Research for the innovation and improvement of products obtained from wood have been incentivized (Missoum et al 2013). Wood is a complex material shaped by nanometric structures that exhibit biometric properties, as well as by the architecture and the organization of these structures (Kollmann and Côté 1968, Déjardin et al 2010). The most adequate and rational use of wood as a raw material can be reached through extensive knowledge of its properties, and the understanding that each property could present greater or less importance, depending on the intended final product (Walker 2006). Near Infrared (NIR) spectroscopy has been applied in the forestry field to evaluate the properties of wood (Tsuchikawa and Schwanninger 2013). The technique allows the analysis of organic compounds, including nanostructured films, since the spectral occurrences in this region derive mainly from the following

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