1. ABOUT THE DATASET -------------------- Title: Data for Dissolution of a commercial regenerated cellulosic fibre (Cordenka) in the ionic liquid 1-ethyl-3-methylimidazolium acetate studied using time-temperature superposition Creator(s): Michael Ries Organisation(s): University of Leeds Rights-holder(s): Copyright 2023 University of Leeds Publication Year: 2023 Description: Wide-angle X-ray diffraction (WAXS) and mechanical testing techniques are used to track the dissolution of a regenerated commercial cellulose fibre (Cordenka) in the ionic liquid 1-ethyl-3-methyl-imidazolium acetate [C2mim]+ [OAc]- for different times and temperatures. In the dissolution process, the oriented cellulose II crystals in the regenerated cellulose fibres dissolve and then reform into randomly oriented crystals to form a matrix phase, and this change in orientation enables us to follow the dissolution process using WAXS, and hence determine the dissolved matrix volume fraction . The change in the average molecular orientation determined from an azimuthal ) X-ray scan, allows the growth of the matrix volume fraction to be calculated with time and temperature. The growth of was found to follow time temperature superposition, with an Arrhenius behaviour, giving a value for the activation energy of Ea= 149 ± 4 kJ/mol. Young’s modulus was measured on all the resulting composite fibres. The fall of Young’s modulus with dissolution time and temperature was also found to follow time-temperature superposition, with an Arrhenius behaviour giving a value for Ea= 198± 29 kJ/mol. The Young’s Modulus results plotted against determined from the WAXS measurements fitted well to the Voigt upper bound parallel Rule of Mixtures Cite as: Ries, Michael (2023): Data for Dissolution of a commercial regenerated cellulosic fibre (Cordenka) in the ionic liquid 1-ethyl-3-methylimidazolium acetate studied using time-temperature superposition [Dataset]. https://doi.org/10.5518/1276 Contact: Michael Ries m.e.ries@leeds.ac.uk 2. TERMS OF USE --------------- Copyright 2023 University of Leeds. This dataset is licensed under a Creative Commons Attribution 4.0 International Licence: https://creativecommons.org/licenses/by/4.0/.]