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A Round Robin study has been carried out to estimate the impact of the human element in small-angle scattering data analysis. Four corrected datasets were provided to participants ready for analysis. All datasets were measured on samples containing spherical scatterers, with two datasets in dilute dispersions, and two from powders.
Most of the 46 participants correctly identified the number of populations in the dilute dispersions, with half of the population mean entries within 1.5 % and half of the population width entries within 40 %, respectively. Due to the added complexity of the structure factor, much fewer people submitted answers on the powder datasets.
For those that did, half of the entries for the means and widths were within 44 % and 86 % respectively. This Round Robin experiment highlights several causes for the discrepancies, for which solutions are proposed.
A round-robin study has been carried out to estimate the impact of the human element in small-angle scattering data analysis. Four corrected datasets were provided to participants ready for analysis. All datasets were measured on samples containing spherical scatterers, with two datasets in dilute dispersions and two from powders. Most of the 46 participants correctly identified the number of populations in the dilute dispersions, with half of the population mean entries within 1.5% and half of the population width entries within 40%. Due to the added complexity of the structure factor, far fewer people submitted answers on the powder datasets. For those that did, half of the entries for the means and widths were within 44 and 86%, respectively. This round-robin experiment highlights several causes for the discrepancies, for which solutions are proposed.
Spherical lignin nanoparticles (LNPs) fabricated via nanoprecipitation of dissolved lignin are among the most attractive biomass-derived nanomaterials. Despite various studies exploring the methods to improve the uniformity of LNPs or seeking more application opportunities for LNPs, little attention has been given to the fundamental aspects of the solvent effects on the intrinsic properties of LNPs. In this study, we employed a variety of experimental techniques and molecular dynamics (MD) simulations to investigate the solvent effects on the intrinsic properties of LNPs. The LNPs were prepared from softwood Kraft lignin (SKL) using the binary solvents of aqueous acetone or aqueous tetrahydrofuran (THF) via nanoprecipitation. The internal morphology, porosity, and mechanical properties of the LNPs were analyzed with electron tomography (ET), small-angle X-ray scattering (SAXS), atomic force microscopy (AFM), and intermodulation AFM (ImAFM). We found that aqueous acetone resulted in smaller LNPs with higher uniformity compared to aqueous THF, mainly ascribing to stronger solvent−lignin interactions as suggested by MD simulation results and confirmed with aqueous 1,4-dioxane (DXN) and aqueous dimethyl sulfoxide (DMSO).
More importantly, we report that both LNPs were compact particles with relatively homogeneous density distribution and very low porosity in the internal structure. The stiffness of the particles was independent of the size, and the Young’s modulus was in the range of 0.3−4 GPa. Overall, the fundamental understandings of LNPs gained in this study are essential for the design of LNPs with optimal performance in applications.