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The origin and evolution of Saturn’s rings is critical to understanding the Saturnian system as a whole. Here, we discuss the physical and chemical composition of the rings, as a foundation for evolutionary models described in subsequent chapters. We review the physical characteristics of the main rings, and summarize current constraints on their chemical composition. Radial trends are observed in temperature and to a limited extent in particle size distribution, with the C ring exhibiting higher temperatures and a larger population of small particles. The C ring also shows evidence for the greatest abundance of silicate material, perhaps indicative of formation from a rocky body. The C ring and Cassini Division have lower optical depths than the A and B rings, which contributes to the higher abundance of the exogenous neutral absorber in these regions. Overall, the main ring composition is strongly dominated by water ice, with minor silicate, UV absorber, and neutral absorber components. Sampling of the innermost D ring during Cassini’s Grand Finale provides a new set of in situ constraints on the ring composition, and we explore ongoing work to understand the linkages between the main rings and the D ring. The D ring material is organic- and silicate-rich and water-poor relative to the main rings, with a large population of small grains. This composition may be explained in part by volatile losses in the D ring, and current constraints suggest some degree of fractionation rather than sampling of the bulk D ring material.

One of the key aspects of the laser powder bed fusion (L-PBF) process is the quality of the raw powder since it affects the final properties of the manufactured parts. In this study, 13 batches of Inconel® 718 powder were analysed, all of them being specially designed for L-PBF technology and meeting similar requirements but coming from different suppliers. Therefore, these batches have certain differences in their characteristics, including the particle size distribution (PSD). This study presents the relationship between the PSD of each batch and the surface roughness obtained in the manufactured parts. For the roughness study, Sa and Sz parameters are presented; in addition, the size and frequency of the particles adhered to the surface were quantified, and an autocorrelation analysis was carried out. Furthermore, after this analysis, the parts were sandblasted in order to repeat the same analysis after removing the adhered particles from the surface. This work points to the fact that the particles adhered to the surface are the smallest particles in the powder batch, and their size affects the roughness of the final part. This means that the surface roughness is strongly related to the fraction of smaller particles within the PSD of the batch, while there is no relationship between the surface roughness and the larger particles.

Particle size measurements of cellulose nanocrystals (CNCs) are challenging due to their broad size distribution, irregular shape and propensity to agglomerate. Particle size is one of the key parameters that must be measured for quality control purposes and to differentiate materials with different properties. We report the results of an interlaboratory comparison (ILC) which examined atomic force microscopy (AFM) data acquisition and data analysis protocols. Samples of CNCs deposited on poly-L-lysine coated mica were prepared in the pilot laboratory and sent to 10 participating laboratories including academic, government and industrial organizations with varying levels of experience with imaging CNCs. The participant data sets indicated that the central location, width and asymmetry varied considerably for both length and height distributions. To deal with this variability we used a skew normal distribution to model the data from each laboratory and to obtain the consensus distribution that describes the CNC particle size. The skew normal distribution has 3 parameters: a central location (mean), distribution width (standard deviation) and asymmetry (shape) factor. This approach gave consensus distributions with mean, standard deviation and asymmetry factor of 94.9 nm, 37.3 nm and 6.0 for length and 3.4 nm, 1.2 nm and 2.8 for height, respectively. The use of multiple probes and/or deterioration of the probe with increased use are significant contributing factors to the variability in mean length between laboratories. There is less variability in height across participating laboratories and tests of applied imaging force indicate that it is possible to image without significant compression of the CNCs. The number of CNCs necessary to obtain a reliable data set depends on the probes and operating conditions, but with careful control of various parameters analysis of 250 and 300 CNCs should provide consistent data sets for height and length, respectively for one sample. Comparison of AFM with transmission electron microscopy (TEM) data obtained in the same ILC demonstrated excellent agreement between measured lengths for the 2 methods. By contrast AFM height was approximately one half the TEM width, a result that indicates the presence of a significant number of laterally agglomerated particles, consistent with literature data.Graphic abstract

Cellulose nanocrystals (CNCs) are bio-based building blocks for sustainable advanced materials with prospective applications in polymer composites, emulsions, electronics, sensors, and biomedical devices. However, their high surface area-to-volume ratio promotes agglomeration, which restrains their performance in size-driven applications, thereby hindering commercial CNC utilization. In this regard, ultrasonication is commonly applied to disperse CNCs in colloidal suspensions; however, ultrasonication methodology is not yet standardized and knowledge of the effects of ultrasound treatments on CNC size distribution is scarce. The major goals of this study were attributed to targeted breakage of CNC agglomerates and clusters by ultrasound. The evolution of particle size distribution and potential de-sulfation by ultrasonication as well as the long-term stability of ultrasonicated CNC suspensions were investigated. Colloidal suspensions of sulfated CNCs were isolated from cotton α-cellulose. Effects of ultrasonication on particle size distribution were determined by asymmetrical flow field-flow fractionation (AF4) coupled with on-line multi-angle light scattering and ultraviolet spectroscopy. These results were complemented with off-line dynamic light scattering. High ultrasound energy densities facilitated cumulative dispersion of CNC clusters. Consequently, the mean rod length decreased logarithmically from 178.1 nm at an ultrasound energy input of 2 kJ g−1 CNC to 141.7 nm (− 20%) at 40 kJ g−1 CNC. Likewise, the hydrodynamic diameter of the particle collective decreased logarithmically from 94.5 to 73.5 nm (− 22%) in the same processing window. While the rod length, below which 95 wt% of the CNCs were found, decreased from 306.5 to 231.8 nm (− 24%) from 2 to 40 kJ g−1 CNC, the shape factor of the main particle fraction ranged from 1.0 to 1.1, which indicated a decreasing number of dimers and clusters in the particle collective. In summary, progressing ultrasonication caused a shift of the particle length distribution to shorter particle lengths and simultaneously induced narrowing of the distribution. The suspension’s electrical conductivity concurrently increased, which has been attributed to faster diffusion of smaller particles and exposure of previously obscured surface charges. Colloidal stability, investigated through electrical AF4 and electrophoretic light scattering, was not affected by ultrasonication and, therefore, indicates no de-sulfation by the applied ultrasound treatment. Occurrence of minor CNC agglomeration at low ultrasound energy densities over the course of 6 months suggest the effect was not unmitigatedly permanent.

This paper presents an investigation into the effects of particle-size distribution on the critical state behavior of granular materials using discrete element method (DEM) simulations on both spherical and non-spherical particle assemblies. A series of triaxial test DEM simulations examine the influence of particle-size distribution (PSD) and particle shape, which were independently assessed in the analyses presented. Samples were composed of particles with varying shapes characterized by overall regularity (OR) and different PSDs. The samples were subjected to the axial compression through different loading schemes: constant volume, constant mean effective stress, and constant lateral stress. All samples were sheared to large strains to ensure that a critical state was reached. Both the macroscopic and microscopic behaviors in these tests are discussed here within the framework of the anisotropic critical state theory. It is shown that both OR and PSD may affect the response of the granular assemblies in terms of the stress–strain relations, dilatancy, and critical state behaviors. For a given PSD, both the shear strength and fabric norm decrease with an increase in OR. The critical state angle of shearing resistance is highly dependent on particle shape. In terms of PSD, uniformly distributed assemblies mobilize higher shear strength and experience more dilative responses than specimens with a greater variation of particle sizes. The position of the critical state line in the e–p′ space is also affected by PSD. However, the effects of PSD on critical strength and evolution of fabric are negligible. These findings highlight the importance of particle shape and PSD that should be included in the development of constitutive models for granular materials.

Particle size normally varies over wide ranges in any commercial transportation of solids through the pipeline. In the present study, the three-dimensional numerical modeling of the conventional 90o bend transporting multi-sized particulate slurry using granular Eulerian-Eulerian model is performed. The mixture of water and six different sizes of zinc tailing particles ranging from 37.5 µm to 575 µm are considered. The effect of variation in velocity and concentration on pressure drop and flow field of the multi-sized particulate slurry is investigated. The simulations are performed in the velocity range of 2.25 m/s to 3.5 m/s for the weighted solid concentration range of 9.82 to 44.26%. The comparison of pressure drop data from the available experimental results and the present numerical modeling with multisized particulate slurry shows maximum deviation within ±6%. Further, the suspension behavior of different size particles in the multi-sized slurry flow inside the bend is analyzed with the variation in the flow velocity and solid concentration. The particles of different size in the multi-sized slurry showed different suspension characteristics.

By examining the multifractal characteristics of soil particle size distribution (PSD), we can elucidate the distribution patterns of soil particles and identify their primary influencing factors. In this study, soil samples from different areas of a floodplain were analyzed for PSD, physicochemical properties, and heavy metal content. Multifractal parameters were calculated using multifractal theory. Subsequently, the relationships between soil PSD, fractal dimension, and soil physicochemical properties were investigated using correlation analysis, Mantel test, and random forest models. The results indicated that the soil particle size distribution in the study area was dominated by silt (2–20 μm) and sand (20–2000 μm) particles, with average contents ranging from 21.18% to 59.46% and 33.24% to 63.81%, respectively. The mean values of the single fractal dimension ( D ), which represents overall soil structure complexity rather than an average of D (0), D (1), and D (2), ranged from 2.27 to 2.54, indicating coarser soil particles. The multifractal dimensions revealed that the capacity dimension ( D (0)) was greater than the information dimension ( D (1)) and the correlation dimension ( D (2)), i.e., D (0) >  D (1) >  D (2), confirming the multifractal nature of soil particle size distribution. The mean values of spectral width (Δ α ) ranged from 1.28 to 3.68, indicating a relatively complex soil fractal structure and significant variability in soil PSD inhomogeneity. Significant correlations ( P  < 0.05, | r | ≥ 0.35) were found between Zn and D , Δ α , D (1), D (2), and D (1)/ D (0), as well as between Pb and D (2) and D (1)/ D (0), suggesting a relationship between heavy metals and fractal dimensions. Additionally, there was a significant correlation ( P  < 0.05, | r |≥ 0.35) between soil PSD and fractal dimensions. Mantel Test and RF analyses, with soil PSD and physicochemical properties as independent variables and soil fractal dimensions as the dependent variable, demonstrated the significant influence of soil PSD on soil fractal dimensions. Fractal dimensions reflect soil quality characteristics and weathering intensity, with multifractal dimensions offering more descriptive insights, as demonstrated by their significant correlations with key soil properties such as cation exchange capacity (CEC), amorphous aluminum oxide (Al o ), free iron oxide (Fe d ), and free aluminum oxide (Al d ). These findings highlight the critical role of soil fractal dimensions in representing soil particle composition and its spatial variability. By elucidating these relationships, this study enhances the understanding of soil structural variability, which is critical for informing targeted ecological management and restoration strategies in alluvial fan environments.

As a matrix for melt-cast explosives, 3,4-dinitropyrazole (DNP) is a promising alternative to 2,4,6-trinitrotoluene (TNT). However, the viscosity of molten DNP is considerably greater compared with that of TNT, thus, requiring the viscosity of DNP-based melt-cast explosive suspensions to be minimized. In this paper, the apparent viscosity of a DNP/HMX (cyclotetramethylenetetranitramine) melt-cast explosive suspension is measured using a Haake Mars III rheometer. Both bimodal and trimodal particle-size distributions are used to minimize the viscosity of this explosive suspension. First, the optimal diameter ratio and mass ratio (two crucial process parameters) between coarse and fine particles are obtained from the bimodal particle-size distribution. Second, based on the optimal diameter ratio and mass ratio, trimodal particle-size distributions are used to further minimize the apparent viscosity of the DNP/HMX melt-cast explosive suspension. Finally, for either the bimodal or trimodal particle-size distribution, if the original data between the apparent viscosity and solid content are normalized, the resultant plot of the relative viscosity versus reduced solid content collapses to a single curve, and the effect of the shear rate on this curve is further investigated.

Non-uniform particle size distribution enhances a lithium-ion (Li-ion) cell performance by optimizing voltage and current profiles. The present study investigates the effect of non-uniform particle size distribution on the internal short-circuit (ISC) behaviour of a Li-ion cell. A pseudo-two-dimensional (P2D) model is employed to numerically analyse the impact of anode particle size distribution on the ISC characteristics of the cell. Furthermore, an interplay between C-rate and non-uniformity in anode particle size distribution is identified. It is revealed that the performance is found to be better in the case of non-uniform anode particle size distribution as compared to uniform particle distribution. Moreover, the decrease in anode particle size along the negative electrode results in the best performance among all the configurations of non-uniform distribution of particle configurations considered. A notable improvement in the ISC behaviour is found at higher C-rates for non-uniform anode particle size distributions.

In this study, permeability, particle size distribution of the sandy soils and collected data from several research studies were analyzed and modeled using Vipulanandan p–q model and the results of prediction were compared with the Fredlund and Logistic Growth models used in the literature. The Vipulanandan p–q model was modified and used to represent the particle size distribution of soils. The Vipulanandan p–q model parameters were correlated very well to various soil properties such as the diameter in the particle size distribution curve corresponding to 10%, 30%, 60%, and 90% of finer (d 10 , d 30 , d 60 , and d 90 respectively), mean particle size the diameter in the particle size distribution curve corresponding to 50% finer (d 50 ), and fines content (F%). The range of particle sizes investigated in this study was 0.14–0.94 mm, 0.075–1.76 mm, and 0.15–3.59 mm for the d 10 , d 30 , and d 60 , respectively. Also, from the Vipulanandan p–q model parameter, the permeability of the soils have been predicted successfully. A current study also had quantified the lower groutability limit based on the d 50 and the Vipulanandan p–q model parameters. The relationship between fines content and d 50 were also generalized using the Vipulanandan p–q model to quantify the upper and lower groutability limits for sandy-soils.