Department of Chemistry, Institute of Chemistry of Renewable Resources, University of Natural Resources and Life Sciences Vienna (BOKU), Konrad-Lorenz-Strasse 24, 3430 Tulln, Austria.
Sorbonne University, Faculty of Sciences and Engineering, Department of Chemistry, Campus Pierre et Marie Curie, 4 place Jussieu, 75005 Paris, France.
Carbohydr Polym. 2022 Feb 15;278:118887. doi: 10.1016/j.carbpol.2021.118887. Epub 2021 Nov 26.
The properties of dialdehyde celluloses, which are usually generated by periodate oxidation, are highly dependent on the aldehyde content, i.e. the degree of oxidation (DO). Thus far, the established methods for determining the DO in dialdehyde celluloses lack simplicity or sufficient speed. More than 60 dialdehyde cellulose samples with varying aldehyde content were analysed by near-infrared and Fourier-transform infrared spectroscopy. This was found to be a reliable method for quickly predicting the DO if combined with partial least squares regression (PLSR). The proposed PLSR models can predict the DO with a high determination coefficient (R) of 99% when applied to a single pulp type and 94% when applied to multiple types. This new approach quickly and reliably determines the DO of dialdehyde celluloses. It can be easily implemented in everyday research to save money, time and resources, especially because the raw datasets and measured DO values are provided.
醛基纤维素的性质通常通过高碘酸盐氧化生成，高度依赖于醛基含量，即氧化度（DO）。迄今为止，醛基纤维素 DO 的测定方法要么不够简单，要么速度不够快。近红外和傅里叶变换红外光谱法分析了 60 多个具有不同醛基含量的醛基纤维素样品。结果表明，如果与偏最小二乘回归（PLSR）相结合，该方法是一种快速预测 DO 的可靠方法。当应用于单一纸浆类型时，所提出的 PLSR 模型可以以 99%的高决定系数（R）预测 DO，而当应用于多种类型时，其可以以 94%的高决定系数预测 DO。该新方法可快速、可靠地测定醛基纤维素的 DO。它可以很容易地在日常研究中实施，以节省资金、时间和资源，特别是因为提供了原始数据集和测量的 DO 值。
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