Fourier transform and near infrared dataset of dialdehyde celluloses used to determine the degree of oxidation with chemometric analysis
Jonas Simon,
Otgontuul Tsetsgee,
Nohman Arshad Iqbal,
Janak Sapkota,
Matti Ristolainen,
Thomas Rosenau,
Antje Potthast
Affiliations
Jonas Simon
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
Otgontuul Tsetsgee
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
Nohman Arshad Iqbal
Department of Chemistry, Faculty of Sciences and Engineering, Sorbonne University, Campus Pierre et Marie Curie, 4 place Jussieu, Paris 75005, France
Janak Sapkota
NE Research Center, UPM Pulp Research and Innovations, Lappeenranta 53200, Finland
Matti Ristolainen
NE Research Center, UPM Pulp Research and Innovations, Lappeenranta 53200, Finland
Thomas Rosenau
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
Antje Potthast
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; Corresponding author.
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.
