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利用热重分析和化学计量学对混合纤维素基再生纤维进行快速定量成分分析。

Fast and quantitative compositional analysis of hybrid cellulose-based regenerated fibers using thermogravimetric analysis and chemometrics.

作者信息

Guizani Chamseddine, Trogen Mikaela, Zahra Hilda, Pitkänen Leena, Moriam Kaniz, Rissanen Marja, Mäkelä Mikko, Sixta Herbert, Hummel Michael

机构信息

Department of Bioproducts and Biosystems, Aalto University, P. O. Box 16300, 00076 Espoo, Finland.

VTT Technical Research Centre of Finland, Ltd, PO Box 1000, 02044 Espoo, Finland.

出版信息

Cellulose (Lond). 2021;28(11):6797-6812. doi: 10.1007/s10570-021-03923-6. Epub 2021 May 28.

Abstract

UNLABELLED

Cellulose can be dissolved with another biopolymer in a protic ionic liquid and spun into a bicomponent hybrid cellulose fiber using the Ioncell technology. Inside the hybrid fibers, the biopolymers are mixed at the nanoscale, and the second biopolymer provides the produced hybrid fiber new functional properties that can be fine-tuned by controlling its share in the fiber. In the present work, we present a fast and quantitative thermoanalytical method for the compositional analysis of man-made hybrid cellulose fibers by using thermogravimetric analysis (TGA) in combination with chemometrics. First, we incorporated 0-46 wt.% of lignin or chitosan in the hybrid fibers. Then, we analyzed their thermal decomposition behavior in a TGA device following a simple, one-hour thermal treatment protocol. With an analogy to spectroscopy, we show that the derivative thermogram can be used as a predictor in a multivariate regression model for determining the share of lignin or chitosan in the cellulose hybrid fibers. The method generated cross validation errors in the range 1.5-2.1 wt.% for lignin and chitosan. In addition, we discuss how the multivariate regression outperforms more common modeling methods such as those based on thermogram deconvolution or on linear superposition of reference thermograms. Moreover, we highlight the versatility of this thermoanalytical method-which could be applied to a wide range of composite materials, provided that their components can be thermally resolved-and illustrate it with an additional example on the measurement of polyester content in cellulose and polyester fiber blends. The method could predict the polyester content in the cellulose-polyester fiber blends with a cross validation error of 1.94 wt.% in the range of 0-100 wt.%. Finally, we give a list of recommendations on good experimental and modeling practices for the readers who want to extend the application of this thermoanalytical method to other composite materials.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10570-021-03923-6.

摘要

未标注

纤维素可与另一种生物聚合物在质子离子液体中溶解,并使用离子纤维素技术纺制成双组分混合纤维素纤维。在混合纤维内部,生物聚合物在纳米尺度上混合,第二种生物聚合物为所生产的混合纤维提供了新的功能特性,可通过控制其在纤维中的比例进行微调。在本工作中,我们提出了一种快速且定量的热分析方法,通过热重分析(TGA)结合化学计量学对人造混合纤维素纤维进行成分分析。首先,我们在混合纤维中加入了0 - 46 wt.%的木质素或壳聚糖。然后,我们按照简单的一小时热处理方案,在TGA设备中分析它们的热分解行为。通过与光谱学类比,我们表明微商热重曲线可作为多元回归模型中的预测器,用于确定纤维素混合纤维中木质素或壳聚糖的比例。该方法对木质素和壳聚糖产生的交叉验证误差在1.5 - 2.1 wt.%范围内。此外,我们讨论了多元回归如何优于更常见的建模方法,如基于热重曲线去卷积或参考热重曲线线性叠加的方法。而且,我们强调了这种热分析方法的通用性——只要其成分能够热分解,该方法就可应用于广泛的复合材料——并用另一个例子说明了它在测量纤维素和聚酯纤维共混物中聚酯含量方面的应用。该方法能够预测纤维素 - 聚酯纤维共混物中聚酯含量,在0 - 100 wt.%范围内交叉验证误差为1.94 wt.%。最后,对于希望将这种热分析方法扩展应用于其他复合材料的读者,我们给出了关于良好实验和建模实践的建议清单。

补充信息

在线版本包含可在10.1007/s10570 - 021 - 03923 - 6获取的补充材料。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b689/8550718/622089c53b1a/10570_2021_3923_Fig1_HTML.jpg

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