Simon Jonas, Tsetsgee Otgontuul, Iqbal Nohman Arshad, Sapkota Janak, Ristolainen Matti, Rosenau Thomas, Potthast Antje
Department of Chemistry, Institute of Chemistry of Renewable Resources, University of Natural Resources and Life Sciences Vienna (BOKU), Konrad-Lorenz-Strasse 24, Tulln 3430, Austria.
Department of Chemistry, Faculty of Sciences and Engineering, Sorbonne University, Campus Pierre et Marie Curie, 4 place Jussieu, Paris 75005, France.
Data Brief. 2021 Dec 23;40:107757. doi: 10.1016/j.dib.2021.107757. eCollection 2022 Feb.
This dataset is related to the research article entitled ``A fast method to measure the degree of oxidation of dialdehyde celluloses using multivariate calibration and infrared spectroscopy''. In this article, 74 dialdehyde cellulose samples with different degrees of oxidation were prepared by periodate oxidation and analysed by Fourier-transform infrared (FTIR) and near-infrared spectroscopy (NIR). The corresponding degrees of oxidation were determined indirectly by periodate consumption using UV spectroscopy at 222 nm and by the quantitative reaction with hydroxylamine hydrochloride followed by potentiometric titration. Partial least squares regression (PLSR) was used to correlate the infrared data with the corresponding degree of oxidation (DO). The developed NIR/PLSR and FTIR/PLSR models can easily be implemented in other laboratories to quickly and reliably predict the degree of oxidation of dialdehyde celluloses.
该数据集与题为《一种使用多元校准和红外光谱法测量二醛纤维素氧化程度的快速方法》的研究文章相关。在本文中，通过高碘酸盐氧化制备了74个不同氧化程度的二醛纤维素样品，并使用傅里叶变换红外光谱（FTIR）和近红外光谱（NIR）进行分析。相应的氧化程度通过在222 nm处使用紫外光谱法测定高碘酸盐消耗量以及通过与盐酸羟胺的定量反应随后进行电位滴定间接确定。使用偏最小二乘回归（PLSR）将红外数据与相应的氧化程度（DO）相关联。所开发的近红外/PLSR和傅里叶变换红外光谱/PLSR模型可以很容易地在其他实验室中实施，以快速、可靠地预测二醛纤维素的氧化程度。
