Should deep eutectic solvents be treated as a mixture of two components or as a pseudo-component?

Deep eutectic solvents (DESs) and dilutions thereof (mainly in H2O but also in many other non-aqueous solvents and co-solvent mixtures) have recently attracted great attention. It is well known that DES dilutions exhibit deviations from ideality. Interestingly, the treatment of DES as a mixture of two components or a pseudo-component is by no means trivial when determining deviations in density and, mainly, in viscosity. Herein, we studied aqueous dilutions of one of the most widely studied DES, this is, that composed of choline chloride and urea in a 1:2 molar ratio (e.g., ChCl2U). Using density and viscosity data reported in previous works, we calculated the excess molar volumes (VE) and excess viscosities (ln ηE) considering ChCl2U as either a mixture of two components or a pseudo-component, that is, taking the DES molecular weight as MChCl2U = fChClMChCl + fUMU = 86.58 g mol-1 (with fChCl = 1/3 and fU = 2/3) or as M* ChCl2U = MChCl + 2 MU = 259.74 g mol-1. We found that neither the sign of VE and VE* nor their evolution with temperature was influenced by the use of either MChCl2U or M* ChCl2U, and only the absolute magnitude of the deviation and the DES content (in wt. %) at which the minimum appears exhibited some differences. However, ln ηE and ln ηE* exhibited opposite signs, negative and positive, respectively. The odd achievement of negative ln ηE in aqueous dilutions of ChCl2U characterized by the formation of HB networks suggest the treatment of ChCl2U as a pseudo-component as more appropriate. Moreover, the role played by the presence of U in the evolution of ln ηE* with temperature was also discussed.

In-depth characterization of the aggregation state of cellulose nanocrystals through analysis of transmission electron microscopy images.

Dispersion of cellulose nanocrystals (CNCs) is of utmost importance to guarantee their reliable application. Nevertheless, there is still no consensual method to characterize CNC aggregation. The hypothesis of this paper is that dispersion could be quantified through the classification of aggregates detected in transmission electron microscopy images. k-Means was used to classify image particulate elements of five CNC samples into groups according to their geometric features. Particles were classified into five groups according to their maximum Feret diameter, elongation, circularity and area. Two groups encompassed the most application-critical aggregates: one integrated aggregates of high complexity and low compactness while the other included elongated aggregates. In addition, the characterization of CNC dispersion after different levels of sonication was achieved by assessing the change in the number of elements belonging to each cluster after sonication. This approach could be used as a standard for the characterization of the aggregation state of CNCs.