Particle Cluster Size Research Articles

Sulfate Doping Promotes Agglomeration of Calcium Fluoride Crystals.

Calcium salt precipitation is an effective solution to wastewater fluoride pollution. The purity and precipitation efficiency of calcium fluoride is critical for its removal and recovery. This study aimed to reveal the role of coexisting sulfates in the precipitation of calcium fluoride. A low sulfate concentration promoted calcium fluoride precipitation. The size of calcium fluoride-aggregated particle clusters increased from 750 to 2000 nm when the molar ratio of sulfate to fluoride was increased from 0 to 3:100. Sulfate doped in the calcium fluoride crystals neutralized the positive charge of the calcium fluoride. Online atomic force microscopy measurements showed that sulfate reduced the repulsive force between calcium fluoride crystals and increased the adhesion force from 1.62 to 2.46 nN, promoting the agglomeration of calcium fluoride crystals. Sulfate improved the precipitation efficiency of calcium fluoride by promoting agglomeration; however, the purity of calcium fluoride was reduced by doping. Sulfate reduced the induction time of calcium fluoride crystallization and improved the nucleation rate of calcium fluoride. Sulfate should be retained to improve the precipitation of calcium fluoride and to avoid its loss from the effluents. However, it is necessary to separate sulfate from fluoride to obtain high-purity calcium fluoride. Therefore, sulfate concentration regulation in high-fluoride wastewater is key to achieving the efficient removal and recovery of fluoride ions.

Photoreforming of glycerol to produce hydrogen from natural water in a compound parabolic collector solar photoreactor

To improve TiO2 for H2 generation, one strategy for the separation of photogenerated charges is the formation of heterostructures with other materials. In particular, NiO is a photocatalyst known for its good stability and low cost. However, no studies at pilot scale using solar energy have been described. Consequently, an evaluation of a physical NiO:TiO2 mixture at pilot scale (25 L) with natural irradiation (2.10 m2 of sun-exposed surface) and with simultaneous glycerol photoreforming was explored. NiO:TiO2 50 mg·L−1 resulted in the highest hydrogen production, showing an STH = 1.44%, considering only the UV fraction of the solar irradiation. H2 and CO2 production were analysed by on-line GC; Glycerol, dissolved organic carbon, carboxylic acids and nickel leaching were also evaluated. The NiO:TiO2 mixtures rendered a systematically lower H2 production in natural water than in high-purity water. The increase of ionic strength increased the mean size of particle clusters, promoting rapid sedimentation. All this indicates the importance of testing under real field conditions for attaining reliable solar to hydrogen (STH) efficiency.

Effects of incoming particle energy and cluster size on the G-value of hydrated electrons

In hydrated electron (e−aq) dosimetry, absorbed radiation dose to water is measured by monitoring the concentration of radiation-induced e−aq. However, to obtain accurate dose, the radiation chemical yield of e−aq, G(e−aq), is needed for the radiation quality/setup under investigation. The aim of this study was to investigate the time-evolution of the G-values for the main generated reactive species during water radiolysis using GEANT4-DNA. The effects of cluster size and linear energy transfer (LET) on G(e−aq) were examined. Validity of GEANT4-DNA for calculation of G(e−aq) for clinically relevant energies was studied. Three scenarios were investigated with different phantom sizes and incoming electron energies (1 keV to 1 MeV). The time evolution of G(e−aq) was in good agreement with published data and did not change with decreasing phantom size. The time-evolution of the G-values increases with increasing LET for all radiolytic species. The particle tracks formed with high-energy electrons are separated and the resulting reactive species develop independently in time. With decreasing energy, the mean separation distance between reactive species decreases. The particle tracks might not initially overlap but will overlap shortly thereafter due to diffusion of reactive species, increasing the probability of e−aq recombination with other species. This also explains the decrease of G(e−aq) with cluster size and LET. Finally, if all factors are kept constant, as the incoming electron energy increases to clinically relevant energies, G(e−aq) remains similar to its value at 1 MeV, hence GEANT4-DNA can be used for clinically relevant energies.

Topologically directed confocal Raman imaging (TD-CRI): Advanced Raman imaging towards compositional and micromeritic profiling of a commercial tablet components

Particle size distribution (PSD), spatial location and particle cluster size of ingredients, polymorphism, compositional distribution of a pharmaceutical product are few of the most important attributes in establishing the drug release-controlling microstructural and solid state properties that would be used to (re)design or reproduce similar products. There are numerous solid-state techniques available for PSD analysis. Laser diffraction (LD) is mostly used to study PSD of raw materials. However, a constraint of LD is the interference between the active pharmaceutical ingredients (API) and excipients, where it is very challenging to measure API size in a tablet. X-ray powder diffraction (XRPD) is widely employed in establishing the polymorphism of API and excipients. This research examined a commercial osmotic tablet in terms of extracting solid state properties of API and functional excipient by Raman Imaging. Establishing repeatability, reproducibility, and sample representativeness when the samples are non-uniform and inhomogeneous necessitates multiple measurements. In such scenarios, when employing imaging-based techniques, it can be time-consuming and tedious. Advanced statistical methodologies are used to overcome these disadvantages and expedite the characterization process. Overall, this study demonstrates that Raman imaging can be employed as a non-invasive and effective offline method for assessing the solid-state characteristics of API and functional excipients in complex dosage forms like osmotic tablets.

Charge sharing investigation in a Timepix3 (TPX3) detector through ion probing

The phenomenon of charge sharing in pixelated particle detectors and its relationship to a variety of physical parameters is investigated using a Timepix3 (TPX3) detector with a 500 μm thick silicon sensor. A probing technique is used with H, Li, and C ion beams produced at the Tandem Van de Graaff (VdG) accelerator at the University of Montreal (UdeM), as well as alpha particles from an 241Am radioactive source, to determine a direct relationship between particle depth and cluster size. Additionally, the primacy of a particle's energy on the determination of its corresponding cluster's size is confirmed.

Optical Imaging of Magnetic Particle Cluster Oscillation and Rotation in Glycerol.

Magnetic particles have been evaluated for their biomedical applications as a drug delivery system to treat asthma and other lung diseases. In this study, ferromagnetic barium hexaferrite (BaFeO) and iron oxide (FeO) particles were suspended in water or glycerol, as glycerol can be 1000 times more viscous than water. The particle concentration was 2.50 mg/mL for BaFeO particle clusters and 1.00 mg/mL for FeO particle clusters. The magnetic particle cluster cross-sectional area ranged from 15 to 1000 m, and the particle cluster diameter ranged from 5 to 45 m. The magnetic particle clusters were exposed to oscillating or rotating magnetic fields and imaged with an optical microscope. The oscillation frequency of the applied magnetic fields, which was created by homemade wire spools inserted into an optical microscope, ranged from 10 to 180 Hz. The magnetic field magnitudes varied from 0.25 to 9 mT. The minimum magnetic field required for particle cluster rotation or oscillation in glycerol was experimentally measured at different frequencies. The results are in qualitative agreement with a simplified model for single-domain magnetic particles, with an average deviation from the model of 1.7 ± 1.3. The observed difference may be accounted for by the fact that our simplified model does not include effects on particle cluster motion caused by randomly oriented domains in multi-domain magnetic particle clusters, irregular particle cluster size, or magnetic anisotropy, among other effects.

Surface roughness effect on the shear thinning of non-colloidal suspensions

The shear thinning behavior of non-colloidal suspensions is investigated experimentally with emphasis on the effect of surface roughness of suspending particles. The first shear thinning at a low shear-rate is observed, which originates from particle–particle interaction, and the second shear thinning at a high shear rate is also reported as the polymeric solvent shear thins. Due to the decrease of the size of particle clusters, the viscosity of suspensions decreases in the first shear thinning regime. The surface asperities on rough particles hinders the lubricative interaction between close-contact particles suppressing the growth of clusters, and therefore, the first shear thinning behavior weakens. The shielding of the lubricative interaction also prevents the local shear rate enhancement, corresponding to the suppressions second shear thinning and the rising of a second-order first normal stress difference from the polymeric solvent. A theoretical model describing the first shear thinning behavior of non-colloidal suspension is developed, and the predications agree well with experimental data. The roughness effect on dynamic rheological behavior is also investigated.

Structure formation in suspensions under uniform electric or magnetic field

The structure formation of particles with induced dipoles dispersed in a viscous fluid, under a spatially and temporarily uniform external electric or magnetic field, is investigated by means of Brownian Dynamics simulations. Dipole–dipole interactions forces, excluded volume forces and thermal fluctuations are accounted for. The resulting structures are characterized in terms of average orientation of their inter-particle vectors (second Legendre polynomial), network structure, size of particle clusters, anisotropy of the gyration tensor of every cluster and existence of (cluster) percolation. The magnitude of the strength of the external field and the volume fraction of particles are varied and the structural evolution of the system is followed in time. The results show that the characteristic timescale calculated from the interaction of only two dipoles is also valid for the collective dynamics of many-particle simulations. In addition, the magnitude of the strength of the external field in the range of values we investigate influences only the magnitude of the deviations around the average behavior. The main characteristics (number density of branch-points and thickness of branches) of the structure are mainly affected by the volume fraction. The possibility of 3D printing these systems is explored. While the paper provides the details about the case of an electric field, all results presented here can be translated directly into the case of a magnetic field and paramagnetic particles.

Experimental investigation of proppant clustering in intersected fractures

This paper investigates the dynamics of proppant agglomerations during flow and transport within fractures intersected at the angles typical for the joint of pre-existing and newly formed fractures. The study considers variations and coupling of fluid flow rates, proppant volumetric concentrations, fluid dynamic viscosities and fracture intersection angles. Proppants are widely used during hydraulic fracturing to keep fractures open and enhance reservoir permeability. This study uses plexiglas experimental slots and visual analysis for identifying particle displacements. Geo-Particle Image Velocimetry–Reliability-Guided (GeoPIV-RG) method tracks particle movements among images by comparing the reference and subsequent snapshots at the point and time of interest. Results of this study show that the proppant volumetric concentration and the fluid flow rate are closely correlated with each other for affecting proppant flow, transport, and agglomeration formation. Increasing the proppant volumetric concentration generally promotes particle agglomeration, with different extent when coupled with the fluid flow rate. Proppant volumetric concentration affects the size, shape, and distribution of particle clusters. Increasing the fluid flow rate increases the occurrence of particle agglomerates at low proppant volumetric concentration; however, this trend is absent under high proppant volumetric concentrations. Sizes and shapes of proppant agglomerates change as the fluid flow rate changes. Changes of fracture intersection angle minimally affect shape, size and distance between proppant agglomerates and clusters. Furthermore, increasing the fluid dynamic viscosity strongly promotes proppant agglomeration. Although fluid dynamic viscosity changes do not affect the shape and size of particle clusters, the distance between adjacent clusters decreases at higher fluid dynamic viscosity.

Using Otsu's Method for Image Segmentation to Determine the Particle Density, Surface Coverage and Cluster Size Distribution of 3 nm Si Nanoparticles

The deposition techniques of silicon nanoparticles (Si-NPs) have been widely researched because of the plethora of promising applications. An accurate calculation of the nanoparticle density is of paramount significance for the understanding of device performance. In this work, we statistically evaluate the deposition of 3 nm Si-NPs via spin coating and drop casting. We image the Si-NP samples using optical microscopy combined with ultra-violet illumination, under which they exhibit red photoluminescence. We then perform image segmentation through a computer vision technique, particularly Otsus method, which works by detecting an automatic threshold value to segment the micrograph into its foreground (Si-NPs) and background (substrate). Finally, we utilize a counting algorithm to determine the particle density, surface coverage and cluster size distribution (CSD) on each sample, and hence evaluate the outcome of the two deposition techniques. For spin coating, the effect of drop volume (from 505 L to 2505 L) at constant speed, and the effect of spin speed (100, 300, 400 and 500 RPM) are both investigated while for drop casting, drop volumes of 100, 300 and 500 L were examined. It was found that the nanoparticle cluster density increases with increasing volume until 300 L while increasing the spin speed decreases the cluster of NPs deposited but results in higher uniformity of particle distribution. For spin coating, the highest cluster density recorded was 410⁶ particles/cm² for the sample with 1005 L at a speed of 400 RPM while for drop casting it was 8.7510⁶ particles/cm² at a volume of 300 L. Moreover, the relation between particle density, size distribution and the deposition techniques is discussed in terms of the strong centrifugal force the particles experience during spin coating compared to drop casting, as well as the interdependency of bonding of the Si-NPs with the solvent molecules on the deposition efficiency.

Hybrid Particle Cluster CPFD Simulation in the Acceleration and Stabilized Sections of a Downflow Circulating Fluidized Bed

This study reports a numerical hybrid cluster simulation of a downer reactor unit using CPFD Barracuda VR software. This model includes an experimentally determined particle cluster size distribution to describe the particle cluster morphological changes as well as the cluster acceleration. Gas–solid flows are considered for a fluid catalytic cracking catalyst with an apparent particle density of 1722 kg/m3, flowing in a 5.08 cm-ID column with air at 300 K and with a pressure close to atmospheric. Conditions for the simulations consist of 1.0–1.6 m/s superficial gas velocity and 30–50 kg/m2 s solid mass flux ranges. Calculations developed involve the Hölzer–Sommerfeld and Ganser drag correlations. The proposed numerical model is validated by comparing experimental and simulated radial cluster particle velocities and particle volume fractions. Simulations developed show that the Hölzer–Sommerfeld drag function in conjunction with a proper selection of cluster geometry provides good cluster velocities and particle volume fraction values both in the cluster acceleration and cluster-stabilized flow unit sections.

Magnetization Reversal of Ferromagnetic CoFeB Films and CoFeB/Ta/CoFeB Heterostructures in the Stray Field of Fe/Fe3O4 Nanoparticles

The magnetization reversal of the MgO/CoFeB/Ta/CoFeB/MgO/Ta/GaAs heterostructures and the ultrathin MgO/CoFeB/MgO/Ta/GaAs films with a perpendicular anisotropy in the magnetic field of clusters of Fe/Fe3O4 nanoparticles is experimentally observed. The stray magnetic field of Fe/Fe3O4 nanoparticles increases the field of switching the magnetization of spin valves and monolayer platforms. The size of the magnetization reversal region of the ferromagnetic platform under Fe/Fe3O4 nanoparticles as a function of the cluster size was determined by atomic force and magnetic force microscopy. The size of the magnetization reversal region is found to be larger than the particle cluster size, which is caused by the stray field of a cluster of Fe/Fe3O4 nanoparticles. The local magnetization orientations in the CoFeB layers under clusters of nanoparticles and the magnetization reversal region diameter are determined as functions of the magnetic moment and the size of the cluster using micromagnetic simulation.

Numerical Simulation of Particle Size Influence on the Breakage Mechanism of Broken Coal

The goaf is generally consisted of broken coal and rock mass. During the process of overburden strata subsidence and compaction, the broken characteristics directly affect the mechanism and pore characteristics of the caving coal and rock mass. In order to study the influence of particle size on the breakage mechanism of broken coal in the compaction process, the bonded particle model of broken coal sample was carried out to study the breakage characteristics during the compaction with different particle sizes. The stress–strain model of the broken particle model (BPM) during compaction was given. The particle size affects the maximum vertical strain, em, and the stress–strain curve at the beginning of loading. But the particle size has no effect on the slope of the stress–strain curve in linear stage. During the compaction process, the porosity of the BPM can be divided into three stages: slow decrease stage, accelerated decrease stage and slow decrease stage with the increase in strain. Particle size also affects the change in porosity during compaction. The larger the particle size is, the smaller the porosity is at the same strain, but the particle size has no effect on the porosity–stress curve. The breakage rate of BPM increases in S-shape with the increase in strain. When the strain of BPM is over the maximum vertical strain, the particle is basically no longer broken. The larger the particle size is, the larger the residual particle cluster size will be when the breakage rate is stable. The particle sizes' influence on the evolution characteristics of BPM mechanical properties, porosity and breakage rate was demonstrated. The numerical simulation results in this paper can be used for analyzing the compaction characteristics of caving zone at the engineering scale.

Cluster Acceleration and Stabilization in a Downflow Circulating Fluidized Bed Unit

Particle cluster velocities, cluster sizes and solid holdups were measured in a cold-flow downer unit using CREC-GS-Optiprobes. Runs were developed in a 0.051 m ID and 2 m high acrylic column, and ...

Zerovalent nickel nanoparticles performance towards Cr(VI) adsorption in polluted water

Heavy metals are one of the most common types of pollutants in ground water due to their wide sources, non-degradability and high toxicity. Many traditional wastewater treatments were not capable of removing enough such contaminants in order to meet quality standards. Nanosized zerovalent transition metals have emerged as a great candidate for ground water remediation, due to their simplicity and low fabrication cost, furthermore they can comply with simple chemical synthesis. Here, we present the synthesis of nano zerovalent nickel (nZVN) by a simple grinding reduction method. The obtained nZVN was characterized with XRD, SEM, EDS and BET surface area. The results confirms the formation of nZVN and the active particle cluster size ranges from 100 to 200 nm. N2 adsorption isotherms revealed that the formation mesoporous cluster of nZVN with good surface area. The adsorption of Cr(VI) using nZVN showed 96% removal efficiency for 10 ppm concentration, and even up to 98% when the temperature is slightly raised to 36 °C (309 K). The removal efficiencies of Cr by zerovalent nickel was well fitted by the Langmuir–Hinshelwood first order reaction kinetic model with deceptive rate constant values of 0.6699, 0.7956 and 1.0251 min−1 at temperature 200, 303 and 309 K, respectively. In total, our studies suggest that nanoscale zerovalent iron is a capable material for Cr(VI) remediation from groundwater.

Multi-scale characteristics and gas-solid interaction among multiple beds in a dual circulating fluidized bed reactor system

To investigate the gas-solid mixing and interaction among reactors of Dual Circulating Fluidized Bed Reactor (DCFBR), the detecting methods of acoustic emission and pressure fluctuation are employed to study the effects of operating parameters including riser gas velocity, bubbling bed gas velocity and pot-seal gas velocity on the gas-solid behavior and multi-scale characteristics of the DCFBR system. The experimental results demonstrate that gas disturbance makes bed particles fully mixed and the intensity of inter-particle mixing increases as gas disturbance intensifies. Meanwhile, inter-particle mixing can also cause changes in voidage. Therefore, gas and solid phases in the reactor have a mutual effect on each other. In addition, the particle circulation rate varies as the operating gas velocity changes, which in turn causes variations in both particle and bubble behaviors in the riser and the bubbling bed with particles and bubbles interacting with each other. By combining the methods of Hurst and fractal dimension analysis, the multi-scale variation of acoustic signals in the upper and lower parts of the riser under fast fluidization is obtained. As the results reveal, there are certain differences in particle clusters and bubble phase behaviors between the upper and lower parts of the riser. The larger the particle cluster size, the more uneven the flow inside the bed, indicating an intensified effect of the inter-granular particle cluster. Moreover, the size of particle cluster, which is related to particle concentration, increases as the concentration intensifies.

Effect of Clustering on the Heat Generated by Superparamagnetic Iron Oxide Nanoparticles.

Magnetic nanoparticles have been the subject of enormous investigations for their potential use as cancer treatment via hyperthermia. This is due to their ability to generate heat when exposed to an external magnetic field oscillating at sufficiently high frequency. There are many different parameters that need to be considered when designing the optimal nanoparticle formulation for hyperthermia. The effect of the formation of clusters of nanoparticles, which is either an unwanted side effect of poor colloidal stability of the particles, or a desired for- mulation strategy, has poorly understood consequences on the amount of heat generated by the nanoparticles. The objective of this work is to address this problem from the theoretical side by performing detailed simulations to investigate the effect of incorporation of magnetic nanoparticles in clusters on the amount of heat generated as a function of the particle size, cluster size and particles magnetic properties.

Alternating current (AC) susceptibility as a particle-focused probe of coating and clustering behaviour in magnetic nanoparticle suspensions

HypothesisThe functionality of magnetic nanoparticles (MNPs) relies heavily on their surface coating, which in turn affects the interactions between MNPs, and the formation of single-core particles or multi-core clusters. In this study we assessed the use of AC susceptibility (ACS) as a magnetic probe of the kinetics of coating and agglomeration of functionalised nanoparticles. We demonstrate the precision and sensitivity of ACS measurements to small changes in MNP coating using arginine-glycine-aspartic acid (RGD) tripeptide binding, and subsequently discuss how ACS can be used to optimise the preparation of polyethyleneimine (PEI) functionalised MNPs aimed at nanomagnetic transfection applications. ExperimentsWe varied the PEI loading of suspensions of MNPs exhibiting a combination of Brownian and Néel relaxation, and used dialysis to study the movement of excess PEI during the coating process. Numerical ACS simulations were employed to determine particle cluster sizes and polydispersity and the results compared with conventional dynamic light scattering (DLS) size measurements. FindingsACS provided information on the MNP coating and agglomeration process that was not accessible through DLS due to the additional presence of non-magnetic polymer particulates in the suspensions. We consequently derived a simple method to obtain dense, uniform PEI coatings affording high-stability suspensions without excessive quantities of unbound PEI.

Strategies for efficient machine learning of surrogate drag models from three-dimensional mesoscale computations of shocked particulate flows

Macroscale simulations of shocked particulate flows rely on closure laws to model momentum transfer between the fluid and dispersed particles phase. Developing closure models from experimental data is expensive. Robust and accurate closures laws can be obtained through surrogate modeling using high-resolution mesoscale simulations. However, development of surrogate models for drag from 3D high-fidelity simulations of shock interaction with clusters of particles can be computationally prohibitive. This paper explores various strategies to efficiently construct surrogate models for drag on particles in the shocked flow. The cost of generating training data is reduced by selecting optimal grid resolutions, particle arrangements in clusters, and size of particle clusters, i.e., by selecting suitable representative volumes (RVEs). Different surrogate modeling strategies such as multi-fidelity and parameter-by-parameter construction approaches are examined. The surrogate models obtained from the different methods are compared to determine the most cost-effective machine learning based surrogate modeling method in the context of shock-particle interactions.

Start-up rheometry of highly polydisperse magnetorheological fluids: experiments and simulations

An extensive experimental and simulation study is carried out in conventional magnetorheological fluids formulated by dispersion of mixtures of carbonyl iron particles having different sizes in Newtonian carriers. Apparent yield stress data are reported for a wide range of polydispersity indexes (PDI) from PDI = 1.63 to PDI = 3.31, which for a log-normal distribution corresponds to the standard deviation ranging from ν = 0.38 to ν = 0.76. These results demonstrate that the effect of polydispersity is negligible in this range in spite of exhibiting very different microstructures. Experimental data in the magnetic saturation regime are in quantitative good agreement with particle-level simulations under the assumption of dipolar magnetostatic forces. The insensitivity of the yield stresses to the polydispersity can be understood from the interplay between the particle cluster size distribution and the packing density of particles inside the clusters.