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 (R2) 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.
Keywords: Dialdehyde cellulose; Infrared spectroscopy; Multivariate calibration modelling; Near-infrared spectroscopy; Partial least-squares regression; Periodate oxidation.
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