Particle Shape Distribution Research Articles

Predicting filtration of needle-like crystals: A Monte Carlo simulation study of polydisperse packings of spherocylinders

The development of pharmaceutical production processes is frequently hindered by challenging filtration operations. The particle size and shape distribution is known to be a major contributor to filtration performance: here a strategy to understand how this distribution controls the filter cake structure is proposed. We employ Monte Carlo sampling to generate packings/filter cakes of needle-like crystals, a common morphology in the pharmaceutical industry. The cake porosity, particle orientation and size segregation are characterized. The simulations demonstrate the remarkable impact of polydispersity on cake structure and they confirm the influence of particle aspect ratio. Porosity ranges from 40 to 85% in the investigated domain. Porosity increases with increasing polydispersity of the particle length, while polydispersity along the diameter causes the opposite effect. Even though these simulations only account for particle shape and size and neglect flow and particle interactions, they successfully predict the porosity trends of experimental systems of l-Glutamic Acid.

Characterization of Commercial Metal Oxide Nanomaterials: Crystalline Phase, Particle Size and Specific Surface Area.

Physical chemical characterization of nanomaterials is critical to assessing quality control during production, evaluating the impact of material properties on human health and the environment, and developing regulatory frameworks for their use. We have investigated a set of 29 nanomaterials from four metal oxide families (aluminum, copper, titanium and zinc) with a focus on the measurands that are important for the basic characterization of dry nanomaterials and the determination of the dose metrics for nanotoxicology. These include crystalline phase and crystallite size, measured by powder X-ray diffraction, particle shape and size distributions from transmission electron microscopy, and specific surface area, measured by gas adsorption. The results are compared to the nominal data provided by the manufacturer, where available. While the crystalline phase data are generally reliable, data on minor components that may impact toxicity is often lacking. The crystal and particle size data highlight the issues in obtaining size measurements of materials with broad size distributions and significant levels of aggregation, and indicate that reliance on nominal values provided by the manufacturer is frequently inadequate for toxicological studies aimed at identifying differences between nanoforms. The data will be used for the development of models and strategies for grouping and read-across to support regulatory human health and environmental assessments of metal oxide nanomaterials.

Optimization of nanostructured/nano sized rice husk ash preparation

The objective of the study is developing a procedure for production and characterization of rice husk ash (RHA). The effects of rice husk (RH) amount, burning/cooling conditions combined with stirring on producing of RHA with amorphous silica, highest SiO2, lowest loss on ignition (LOI), uniform particle shape distribution and nano structured size have been studied. It is concluded that the best amount is 20 g RH in 125 ml evaporating dish Porcelain with burning for 2 h at temperature 700 °C combined with cooling three times during burning to produce RHA with amorphous silica, SiO2 90.78% and LOI 1.73%. On the other hand, cooling and stirring times affect the variation of nano structured size and particle shape distribution. However, no crystalline phases were found in RHA in all cases. Results proved that the Attritor ball mill was more suitable than vibration disk mill for pulverizing nano structured RHA with 50% of particle size (D50) lower than 45 mm and 99 % of particle size (D99) lower than 144 mm to nanosized RHA with D50 lower than 36 nm and D99 lower than 57 nm by grinding time 8.16 min to every 1 g RHA without changes in morphousity of silica.

Effect of shape and particle size distribution of inert surface particles on the oxygen exchange kinetics of oxide ceramics

The effect of size distribution and shape of inert surface particles on the oxygen exchange kinetics of solid oxides is investigated. In particular, relaxation curves are calculated numerically for both thick (bulk) samples (thickness: 0.05 cm) and thin samples (thickness: 0.5–5 μm) by means of the finite element method. A “bimodal” size distribution, comprising coarse particles and many tiny particles, as well as a distribution of coarse and smaller particles of comparable size (“monomodal” distribution) are taken into account. Apparent kinetic parameters (chemical surface exchange coefficient and chemical diffusion coefficient) are extracted from the calculated relaxation curves. A significant deviation from the linear relationship between the surface exchange coefficient and the surface coverage is found, if the surface is primarily covered by coarse particles owing to flux constriction effects caused by lateral diffusion underneath the surface particles. In the case of thin samples the relaxation process can exhibit two or more time constants. The effect of the particle shape is investigated by a systematic variation of the aspect ratio of particles with a rectangular cross section. The shorter side length is decisive for the occurrence of flux constriction effects which are negligible for large aspect ratios.

Evaluation of Dynamic Image Analysis for Characterizing Granular Soils

Abstract This study investigates the efficacy of dynamic image analysis (DIA) for determining particle size and shape distribution. The method employs a high-frame-rate camera to image individual particles of sand that have been transported and separated using a stream of pressurized air. DIA can generate both particle size and shape information and provides a quantitative statistical description of the grain size and shape distribution within the specimen. The feasibility, repeatability, and accuracy of DIA for routine analysis of particle size and shape distribution was investigated using 16 granular soils spanning a number of common sizes and shapes. Several particle shape descriptors were evaluated, including aspect ratio, convexity, and sphericity. The effect of a variety of test parameters including moisture content, sample weight, primary air pressure, and test duration were explored to determine the optimal specimen weight and equipment settings for DIA. Finally, the efficacy of DIA in resolving mixtures of fine and coarse sands was also explored. The method proved to be feasible, repeatable, and accurate for providing particle size distributions spanning four orders of magnitude, in terms of particle size. DIA offers a number of advantages; the method is quick, requires small specimen sizes, and provides quantitative information on approximately 3–4 % of the particles in the specimen.

Explicit estimates versus numerical bounds for the electrical conductivity of dispersions with dissimilar particle shape and distribution

An effective-medium theory for the electrical conductivity of Ohmic dispersions taking explicit account of particle shape and spatial distribution independently is available from the work of Ponte Castañeda and Willis [J Mech Phys Solids 43:1919–1951, 1996]. When both shape and distribution take particular “ellipsoidal” forms, the theory provides analytically explicit estimates. The purpose of the present work is to evaluate the predictive capabilities of these estimates when dispersions exhibit dissimilar particle shape and distribution. To this end, comparisons are made with numerical bounds for coated ellipsoid assemblages computed via the finite element method. It is found that estimates and bounds exhibit good agreement for the entire range of volume fractions, aspect ratios, and conductivity contrasts considered, including those limiting values corresponding to an isotropic distribution of circular cracks. The fact that the explicit estimates lie systematically within the numerical bounds hints at their possible realizability beyond the class of isotropic dispersions.

Effect of particle reinforcement on the progressive failure of alumina trihydrate filled Poly(Methyl methacrylate)

Particle reinforced polymers are of interest because of their low density and desirable mechanical, thermal, and electrical properties. By adjusting the particle type, size, shape, and spatial distribution, significant changes in those properties can be obtained. Efforts to understand the role that the particle reinforcement plays in the overall mechanical behavior of the material system has historically been performed via ex-situ characterization and testing methods. This investigation aims, for the first time to the best of the authors knowledge, to observe not only the ex-situ parameter-induced effects on material properties but also the microstructure evolution via in-situ scanning electron microscopy coupled with Nondestructive Evaluation (NDE) techniques with the objective to link the progressive activation and development of damage mechanisms to the measured mechanical behavior. This investigation reports a correlation between particle size and distribution and the measured progressive failure in two types of alumina trihydrate filled poly (methyl methacrylate) composites which provides useful insights into the design of such class of materials.

Effect of particle morphology on mechanical behavior of rock mass

The effects on geotechnical properties of rock mass from the constituent particle morphology have been acknowledged since long. Particle morphology is among the most important parameters affecting the mechanical characteristics of rock, such as shear strength, cohesion, friction angle, porosity, groundwater seepage, and angle of repose. This review summarizes the current advancement in numerical simulation-related particle morphology and its impact on the mechanical behavior of rock mass. Several scholars assessed the influence of particle morphology on macroscopic mechanical response using experimental and numerical simulation techniques. The clump particle approach based on discrete elements methods (DEM) reproduces mechanisms between rock particles to illustrate the correlation of mechanical performance and particle morphology. However, this approach presents the statistical limits of particle shape and size distribution of clump particles to rock particles. Particle shape has distinct effect on geotechnical properties of rock; conversely, each descriptor is case sensitive to a specific attribute of shape. The diversity of the outcomes of the conducted study in the geotechnical field revealed an ambiguity associated with the correlation of particle size distribution with the mechanical behavior of rock and granular material. Nevertheless, further research is essential to address some of the issues that have not yet been tackled, few of which are identified throughout this review article.

Advanced quantification of the carbide spacing and correlation with dimple size in a high-strength medium carbon martensitic steel

Interparticle spacing in materials science is a key parameter controlling ductile fracture. It is generally evaluated as the distance between particle centers of mass. High strength medium carbon martensitic steels contain a high density of carbides, whose size is non-negligible with respect to the distance between them. Current microstructural quantification methods do not take the shape of analyzed particles into account, thus being not necessarily relevant to materials containing a high density of particles that trigger void nucleation and ductile fracture.This work reports on the potency of a simple full field particle quantification method based on a watershed algorithm that takes the shape and spatial distribution of particles into account. Three microstructures were produced by heat treating a hot-rolled 40CrMo4 steel bar. Cementite carbide populations of each microstructure were quantified using carbon extractive replicas, conventional image processing and application of the developed algorithm. A comparison of results from a full field Voronoi tiling algorithm revealed pronounced differences in the shape of distributions. The watershed-based method was shown to allow efficient interpretation of the relationships between carbide distribution and ductile fracture features.

The influence of different shapes and size distributions of coating pigments on packing and dewatering

Particle shape and particle-size distribution (PSD) are important factors for pigment packing and water retention in the pigment coating process, being closely associated with many runnability problems. Diverse experimental investigations on the packing and dewatering of pigment slurries have been made. However, theoretical approaches remain lacking. This paper presents a joint experimental and theoretical analysis of the influence of pigment shape and PSD on pigment packing and dewatering. The relative viscosities of very dilute pigment slurries were measured and used to determine the intrinsic viscosity, based on the Einstein equation. The deviation of pigment shape from spherical caused an increase in viscosity of the slurries. Acicular precipitated calcium carbonates gave lower shape factor values than platy clay particles, which indicated that the needle-like particles could rotate more easily around their long axes under shearing conditions. The packing of pigments, which determines porosity, permeability, light scattering, and mechanical properties, was examined. The packing volumes of nonspherical pigments were estimated based on their respective PSDs, using an algorithm developed for spherical particles, modified with a correction factor. This model is based on the close random-packing volume fraction ( $$\emptyset_{\text{p}}^{ 2}$$ ) of particles of uniform size being an independent variable, regardless of their shape. Therefore, it was valid as long as the particles always achieve the same close random-packing volume ( $$\emptyset_{\text{p}}^{ 1}$$ ) by sedimentation or tapping. Overall, the effect of the particle shape and PSD on the dewatering and filter-cake permeability (Kf) was analyzed. The dewatering rates were measured with a common pressure filtration method, and the permeability of the filter cakes was obtained by fitting the data to a filtration equation. The particle size and PSD were found to influence the permeability constant, but there was little correlation between the permeability and particle shape.

Polysaccharide-Based Controlled Release Systems for Antipsychotic Therapeutics Delivery

Researches in pharmaceutical fields are now focusing on biopolymer-based drug delivery systems for treatment of mild to severe diseases. Amongst all biopolymers, pectin is one of the frequently available and eco-friendly bio-polymer extracted from different fruit peels and abundantly available in nature. This study focuses to extract the pectin from two different fruits using different methods namely hot water-based extraction and cold maceration, involving two different fruit peels. Post extraction and isolation of polymer, study was performed for characterization of pectin powder by particle shape, particle size distribution, surface area angle of repose, flowability and tapped density. The obtained pectin was used for anti-psychotic drug delivery when incorporated into microspheres by solvent evaporation method. It’s surface morphology and release kinetics was analyzed using in vitro methods and in vivo models and kinetics of drug release (goodness of fit) was assessed. The result revealed that the pectin extracted from mango peel using soxhlation method showed good flow rate, minimum particle size and shape distribution, porosity etc. Moreover, it showed the better drug release data in both invitro and in-vivo analysis. The study concludes that in future the natural biopolymer like pectin stands as a potential candidate for formulation of drug release system for efficient delivery of drug

Measurement of flow properties coupled to experimental and numerical analyses of dense, granular flows for solar thermal energy storage

Granular flows of sintered bauxite proppants were examined along an inclined plane for solar thermal energy storage applications. Granular flow properties needed to drive numeric granular models were measured for improved numerical model predictions for Carbobead CP 50/140, 40/100, and 30/60 particles. Particle shape and size distributions were determined by coupling optical microscopy to an in-house image processing algorithm. The impulse excitation technique was used to measure elastic and shear moduli, and compute Poisson’s ratio. The coefficient of static sliding friction was measured using the slip-stick method, and the static rolling friction was determined from measured shear on particles positioned between two hot-pressed plates. The coefficient of restitution was measured by dropping particles on a surface and determining the kinetic energy before and after impact with the surface using high resolution particle tracking velocimetry. Particle size did not significantly impact the coefficients of restitution and static rolling friction, however, particle shape distribution resulted in a large variation in measurements. An inclined flow experiment was performed to characterize granular flows of Carbobead CP 30/60 particles using particle image velocimetry. Numerical models of the experiment using discrete element method were generated with the measured mechanical properties as inputs for comparison with experimental results. A constant directional torque rolling friction model best predicted bulk granular flow behavior. Good agreement between the model and experiment was achieved at ambient, steady state conditions, with average velocity differences <10%.

Influence of particle shape and size distribution on coating mortar properties

This paper investigates the influence of aggregates grading and shape in coating mortar performance, both fresh and hardened stages (mechanical properties and durability). Eight samples of mortar were prepared, using Portland cement type CP II-E-32 (corresponding to American cement: I (SM) ASTM - C 595), natural quartzous aggregate, crushed gneiss artificial aggregate, hydrated lime and water. It was analyzed the packaging of aggregates by determining their grading curves, unitary gravity and void ratio. Aggregates shape was analyzed through images obtained with a stereoscopic magnifying. Regarding coating mortar properties, mechanical properties and durability were analyzed as an aggregates shape function and its granulometric distribution through evaluation of consistency, fresh and hardened state density, air entrained content, water absorption by immersion and porosity, pull-off strength, compressive strength - fc, flexural strength - ft and elasticity modulus - Ed and assessing fissurability. In general, results showed that the particle size curve and the type of aggregate influence significantly the properties analyzed and should be considered during dosing process of coating Portland cement mortar specification, hence many standards to concrete may not be suitable for these composite parts.

Impact of Mass–Size Parameterizations of Frozen Hydrometeors on Microphysical Retrievals: Evaluation by Matching Radar to In Situ Observations from GCPEx and OLYMPEx

AbstractThis article illustrates how multifrequency radar observations can refine the mass–size parameterization of frozen hydrometeors in scattering models and improve the correlation between the radar observations and in situ measurements of microphysical properties of ice and snow. The data presented in this article were collected during the GPM Cold Season Precipitation Experiment (GCPEx) (2012) and Olympic Mountain Experiment (OLYMPEx) (2015) field campaigns, where the true mass–size relationship was not measured. Starting from size and shape distributions of ice particles measured in situ, scattering models are used to simulate an ensemble of reflectivity factors for various assumed mass–size parameterizations (MSP) of the power-law type. This ensemble is then collocated to airborne and ground-based radar observations, and the MSPs are refined by retaining only those that reproduce the radar observations to a prescribed level of accuracy. A versatile “retrieval dashboard” is built to jointly analyze the optimal MSPs and associated retrievals. The analysis shows that the optimality of an MSP depends on the physical assumptions made in the scattering simulators. This work confirms also the existence of a relationship between parameters of the optimal MSPs. Through the MSP optimization, the retrievals of ice water contentMand mean diameterDmseem robust to the change in meteorological regime (between GCPEx and OLYMPEx); whereas the retrieval of the diameter spreadSmseems more campaign dependent.

Influences of ball-milled limestone particle sizes and shapes on asphalt mastic stress relaxation behavior

Asphalts often have filler particles added to improve their mechanical properties. Three distinct filler particle fractions were produced by a planetary high-energy ball mill from limestone aggregates (2.36–4.75 mm). Their particle sizes and shapes were studied by binary image processing and related to milling time and aperture size. The relaxation properties of asphalt mastics prepared with fillers of various sizes and shapes were investigated at a constant strain. Insights into the effects of particle size and shape on mastic relaxation behavior were gained by single regression analysis (SRA) in conjunction with grey relational analysis (GRA). The results show that particle size distributions had noticeable local differences in their slopes and spread, while particle shape distributions showed a narrow range of variability for the studied shape descriptors. Based on stress relaxation curves, fine particles were found to cause binders to become stressed more rapidly than coarse particles. Modified mastics showed much faster stress relaxation than corresponding base mastics at stage I, and exhibited higher stable stress levels than base mastics at stage II. A stress relaxation model was established and found to agree well with experimental data, indicating that mastic relaxation properties can be effectively modeled. Furthermore, the SRA coupled with GRA can provide a simple and effective approach to predicting the effects of particle size and shape on mastic relaxation behavior.

Preparation of hydrogel calcium-alginate microparticles via microfluidic device for Cu&lt;sup&gt;2+&lt;/sup&gt; treatment

Alginate-based hydrogels are attracted much attention in biomedical and chemical field, and their size and shape are significant to their applications like drug delivery and cell encapsulation. Monodisperse sodium alginate microdroplets are produced using a flow-focusing microfluidic device (MFFD) by adjusting the flow rate on the continuous phase (soybean oil) and the dispersed phase (sodium alginate solution). The external gelation process of sodium alginate microdroplets occurs outside the chanel in a calcium chloride solution to form calcium alginate hydrogel particales. The shape, size and size distribution of these calcium alginate hydrogel particles depend strongly on the flow rate inside the MFFD. By optimizing the parameters, the hydrogel microparticles were obtained with diameters ranging from 70 µm to 100 µm with size distribution under 10%, depending on experimental conditions. The removal of Cu2+ ions by the absorption of hydrogel microparticles was also demonstrated.

The effect of contact resistance on electrical conductivity in filled elastomer materials

This paper is focused on studying the charge transport between the particles in filled elastomer composites, and suggests a new modeling approach that would allow predicting the electrical conductivity of this material. Our approach is based on a combination of non-equilibrium Green's function (DFTB-NEGF) analysis for atomic-level electron quantum transport, and effective medium theory for calculating the said macroscopic transport properties of the material. The model can be used for predicting macroscopic material conductivity based on the information of material microstructure received by electron microscopy; explain changes of conductivity in deformed material and with temperature variation, and finally it can assist in finding the optimal material parameters such as particle shape, size distribution, and volume fraction to maximize the performance. The results of our modeling re-attest the known phenomenon that the electrical conductivity in percolated network is always dominated by direct particle-to-particle charge transport. We studied the electrical conductivity in a medium of high volume fraction of metallic particles dispersed in polymer matrix where thin polymer matrix layer covalently attached to the metallic particle contacts, and the thin polymer layer undergoes high local shear strain when hard particles slide along each other during deformation. These conditions allow the redistribution of electron density from metal to the polymer, and the conductance through normally insulating matrix can become comparable with the pinpoint conductance through the metal. These conditions can only occur in the place of direct particle contacts, therefore all criteria for percolated conductive network hold valid in this case. The integral conductance of thin “sandwiched” polymer layer strongly, but predictably depends on local contact geometry, mostly on particle surface curvature at place of contact. This allows predicting composite conductivity from the properties of each phase, loading, and particle shape and size distributions. Further, the conductance of polymer chain can significantly increase with the fluctuations of molecular shape caused by temperature and/or deformation. We infer that this effect is responsible for the major part of strain and temperature dependence of the conductivity that has been reported in the literature, although particle orientation and stacking at larger deformations may also contribute to the strain dependence.

3D microstructure design of lithium-ion battery electrodes assisted by X-ray nano-computed tomography and modelling

Driving range and fast charge capability of electric vehicles are heavily dependent on the 3D microstructure of lithium-ion batteries (LiBs) and substantial fundamental research is required to optimise electrode design for specific operating conditions. Here we have developed a full microstructure-resolved 3D model using a novel X-ray nano-computed tomography (CT) dual-scan superimposition technique that captures features of the carbon-binder domain. This elucidates how LiB performance is markedly affected by microstructural heterogeneities, particularly under high rate conditions. The elongated shape and wide size distribution of the active particles not only affect the lithium-ion transport but also lead to a heterogeneous current distribution and non-uniform lithiation between particles and along the through-thickness direction. Building on these insights, we propose and compare potential graded-microstructure designs for next-generation battery electrodes. To guide manufacturing of electrode architectures, in-situ X-ray CT is shown to reliably reveal the porosity and tortuosity changes with incremental calendering steps.

Physicochemical Characterization of the Pristine E171 Food Additive by Standardized and Validated Methods.

E171 (titanium dioxide) is a food additive that has been authorized for use as a food colorant in the European Union. The application of E171 in food has become an issue of debate, since there are indications that it may alter the intestinal barrier. This work applied standardized and validated methodologies to characterize representative samples of 15 pristine E171 materials based on transmission electron microscopy (TEM) and single-particle inductively coupled plasma mass spectrometry (spICP-MS). The evaluation of selected sample preparation protocols allowed identifying and optimizing the critical factors that determine the measurement of the particle size distribution by TEM. By combining optimized sample preparation with method validation, a significant variation in the particle size and shape distributions, the crystallographic structure (rutile versus anatase), and the physicochemical form (pearlescent pigments versus anatase and rutile E171) was demonstrated among the representative samples. These results are important for risk assessment of the E171 food additive and can contribute to the implementation of the European Food Safety Authority (EFSA) guidance on risk assessment of the application of nanoscience and nanotechnologies in the food and feed chain.

Using a holographic imager on a tethered balloon system for microphysical observations of boundary layer clouds

Abstract. Conventional techniques to measure boundary layer clouds such as research aircraft are unable to sample in orographically diverse or densely populated areas. In this paper, we present a newly developed measurement platform on a tethered balloon system (HoloBalloon) to measure in situ vertical profiles of microphysical and meteorological cloud properties up to 1 km above ground. The main component of the HoloBalloon platform is a holographic imager, which uses digital in-line holography to image an ensemble of cloud particles in the size range from small cloud droplets to precipitation-sized particles in a three-dimensional volume. Based on a set of two-dimensional images, information about the phase-resolved particle size distribution, shape and spatial distribution can be obtained. The velocity-independent sample volume makes holographic imagers particularly well suited for measurements on a balloon. The unique combination of holography and balloon-borne measurements allows for observations with high spatial resolution, covering cloud structures from the kilometer down to the millimeter scale. The potential of the measurement technique in studying boundary layer clouds is demonstrated on the basis of a case study. We present observations of a supercooled low stratus cloud during a Bise situation over the Swiss Plateau in February 2018. In situ microphysical profiles up to 700 m altitude above the ground were performed at temperatures down to −8 ∘C and wind speeds up to 15 m s−1. We were able to capture unique microphysical signatures in stratus clouds, in the form of inhomogeneities in the cloud droplet number concentration and in cloud droplet size, from the kilometer down to the meter scale.