Particle Size Analysis Method Research Articles

Particle size analysis: A comparison of laboratory-based techniques and their application to geoscience

In sedimentary geoscience, the particle size distribution (PSD) of a sediment has a fundamental effect on a sediment's ability to be entrained, eroded, and deposited. Therefore, it is crucial to accurately measure the PSD of sediments. Several laboratory-based methods of particle size analysis are commonly employed in geoscience; however, each method is based on different principles and the comparison of data from one technique to another is challenging. In this study, we have compared the output of four commonly-used laboratory-based techniques: Laser Particle Size Analysis (LPSA), optical point counting, 2D automated image analysis, and X-ray Computed Tomography (XCT). Each technique has been used to measure eight samples of spherical silica particles, all prepared with known particle size ranges. Spherical particles have been used to minimise the effects of variable sorting and particle shape on data output. Here we have compared the differences between the measured PSD and descriptors of each PSD, showing that, at small particle diameters (<150 μm), all techniques agree. However, at particle diameters >150 μm, LPSA overestimates the size of particles, due to limitations in the way that particle diameter is calculated by this technique. In contrast, 2D automated image analysis and optical point counting underestimate the diameters of particles, due to stereology (e.g., the effect of slicing particles during thin section preparation). Results from XCT analyses have the lowest values of sorting (range of measured particle diameters) and are therefore the most tightly constrained. In addition, XCT is the only 3D analysis method, allowing particle shape, orientation, and intraparticle porosity to be measured for a volume of material. We therefore conclude that XCT is the most accurate way to determine a grain size distribution in sediments.

Микропузырьковая безреагентная гидрофобизация поверхности угля

The paper describes methodological features of coal surface hydrophobization the using a microbubble gas-liquid medium to intensify the process of flotation concentration of coal. Air microbubbles were generated using decompression of liquid saturated under air pressure. The influence of water saturation pressure with gas on the size of the bubbles and their stability over time has been established. It is shown that addition of microbubbles leads to formation of an intermediate hydrophobic air layer on the surface of coal, which is the basis for catching bubbles of the flotation size. The results of coking coals flotation using a microbubble gas-liquid mixture are presented. By means of the method of differential particle size analysis, the preferred flotation of fine coal particles &lt; 50 microns in size by micro-bubbles of air was established. It was found that for low-ash coals, the efficiency of reagentless microbubble flotation can be comparable with the results of concentration using traditional petrochemical reagents. In the reagent mode, the micro-bubbles are attached to the oil-hydrophobized surface of small particles with the formation of carbon-air complexes.

An Automated Particle Size Analysis Method for SEM Images of Powder Coating Particles

The particle size of powder coatings is an important factor affecting flow and fluidization performance, which in turn determines the quality of the coating. Powder coating particles, such as boron nitride, titanium dioxide, barium titanate, niobium oxide, and tungsten oxide, can be seen in SEM images as circular or polygonal shapes, with irregular edges and sizes, as well as aggregation and stacking between them. This paper introduces a novel method of automatic particle identification and size analysis applied in SEM images for the investigation of coating quality. Firstly, a fast gradient segmentation algorithm (Split–Merge) is utilized to automatically generate samples through determining the adhesive particles and particle groups. The samples are then manually checked and corrected to further segment the particles in order to form the dataset. Finally, the YOLOv5, a mature target detection algorithm, is used to train the labeled data in order to produce a multi-target detection recognition model. The model can be applied to identify more pictures of the same substance, and the particles’ long and short axes are estimated using the elliptical coverage of the particles within the identified image boundary box. Experiment results from four kinds of powders suggest that this method can provide automatic particle size analysis for industrial SEM particle images.

An image segmentation method of pulverized coal for particle size analysis

An important index to evaluate the process efficiency of coal preparation is the mineral liberation degree of pulverized coal, which is greatly influenced by the particle size and shape distribution acquired by image segmentation. However, the agglomeration effect of fine powders and the edge effect of granular images caused by scanning electron microscopy greatly affect the precision of particle image segmentation. In this study, we propose a novel image segmentation method derived from mask regional convolutional neural network based on deep learning for recognizing fine coal powders. Firstly, an atrous convolution is introduced into our network to learn the image feature of multi-sized powders, which can reduce the missing segmentation of small-sized agglomerated particles. Then, a new mask loss function combing focal loss and dice coefficient is used to overcome the false segmentation caused by the edge effect. The final comparative experimental results show that our method achieves the best results of 94.43% and 91.44% on AP50 and AP75 respectively among the comparison algorithms. In addition, in order to provide an effective method for particle size analysis of coal particles, we study the particle size distribution of coal powders based on the proposed image segmentation method and obtain a good curve relationship between cumulative mass fraction and particle size.

Preparation of ultrafine Mo powder by the H2 reduction of MoO2: Parameter optimization, reaction kinetic, and its reduction mechanism

The influences of different parameters, such as reaction temperature, yttrium (Y) content, and H2 concentration, on the particle size and morphological structure of Mo powder prepared via the H2 reduction of MoO2, were investigated in the work. TG, XRD, FE-SEM, laser particle size analysis, model fitting, and orthogonal design experiment methods were adopted to analyze the reaction kinetic and reduction mechanism. The results showed that the optimum conditions for preparing ultrafine Mo powder were recognized as 1073 K, 1 mass% Y content, and a H2 concentration of 0.000576 mol·cm−2·min−1, which enabled the as-prepared Mo powder with a particle size as small as 107 nm. A new interfacial chemical reaction model with the consideration of reaction temperature, H2 concentration, and sample thickness, was proposed to analyze the reaction kinetic. It was found that the curves predicted by the model agreed well with the experimental data, with the apparent activation energy extracted to be 94.686 kJ/mol. The effect of different individual parameter on the reaction rate and the possible reduction mechanism were also elucidated.

An autoadaptive Haar wavelet transform method for particle size analysis of sands

An autoadaptive Haar wavelet transform method for particle size analysis of sands

Express method for particle size analysis in solid, liquid, and amorphous materials using 3D calibration curve and 2D-DLS dynamic light scattering

This study proposes a new method for particle size studying based on the use of topological descriptors for various media and types of matter. The sizes of supramolecular particles in water-lactose complexes were studied using the diffuse dynamic light scattering (DLS) method. Mist-Standart latex balls were used to generate a 3D calibration curve, followed by empirical particle size determination. In order to confirm the output, the resulting sizes were compared for a number of silver proteinate solutions, preliminary analyzed by laser light scattering (using ZetaSizer equipment by Malvern Instruments Ltd, UK). The new method uses a simplified procedure, provides a quick solution and may be used for both quality control of cloudy and opaque medicinal substances and excipients as well as in other fields of nanotechnology.&#x0D; Keywords: nanoparticles, particle size, silver proteinate, latex nanoparticles, dynamic light scattering

Study of air pollution in the area of compact accommodation of students (campuses) of three universities in Vladivostok city

The article presents the results of the study of airborne particulate matter in Vladivostok city in three areas of compact residence of students (university campuses) using the methods of laser particle size analysis and atomic emission spectrometry. It is shown that the atmospheric air in these areas of the city is polluted with airborne particulate matter with diameter less than 10 μm (PM10). In 5 out of 13 points, we found PM10 microparticles hazardous to health in significant proportions – from 39.9% to 99.5%. The maximum content of particles of the smallest fraction was detected in the Maritime State University campus (railway dead end near the Vladivostok commercial port). The content of particles of heavy metals (I and II hazard class) in the air was identified as well.

On the grinding effects of high-silicon iron tailings.

The main chemical component of high-silicon iron tailings (HSITs) is SiO2; HSITs also include some oxides such as Al2O3 and CaO. Mechanical activation can reduce the particle size of HSITs and enhance their pozzolanic activity such that they can be used as a type of mineral admixture for cement-based materials (CBMs). This study aims to investigate the mechanical activation (ultrafine grinding) effects of HSITs, including physical and crystallization structure effects. The particle distribution, specific surface area, density, and solubility of HSITs were tested using laser particle size analysis and other routine physical testing methods. Their crystal structures were analyzed using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and differential scanning calorimetry-thermogravimetry (DSC-TG). Grinding reduced the particle size of HSIT particles and increased their specific surface area, wherein the minimum D50 was 5.75 μm, the maximum specific surface area was 7608 m2/kg, and the corresponding grinding time was 3.5 h. With an increase in grinding time, the solubility showed an increasing trend; however, the density showed a decreasing trend. The change was fast before 3.5 h or 4 h and then slowed down, but the final solubility was still higher than its initial level, while the final density was still lower than its initial level. Grinding reduced the degree of crystallization of the minerals in HSITs and increased the microscopic strain and disorder of its crystal structure. These changes were significant for a grinding time of 0-3.5 h, after which the changes tended to be slow. The symmetry and integrity of the SiO2 structure decreased with grinding. The activity index of the HSIT powder was higher than 0.6. Ultrafine grinding improves the particle size distribution of HSITs and reduces the crystallinity of their main minerals, which in turn increases their chemical reactivity. It can be said that ultra-finely ground HSIT powder is pozzolanic and can be used as a mineral admixture for CBMs, and its grinding limit can be inferred to be 3.5 h.

Revisiting soil texture analysis: Practices towards a more accurate Bouyoucos method

The Bouyoucos method lacks sample pre-treatment whereby samples are dispersed for only 2 min after being soaked in 5% sodium hexametaphosphate (calgon) for 15–20 h. This study aimed to improve the accuracy of the Bouyoucos (Hydrometer) method of particle size analysis by proposing the best sample pre-treatment and analysis practices. The Pipette method was used as standard reference due to its precision and reproducibility. Treatments modified from the hydrometer method were compared with the Pipette method through Pearson's correlation. The treatments involved variation in the concentration of the pre-treating and dispersing material, time of hydrometer readings, method of agitation and that of dispersing. The proposed improvement suits the Food and Agriculture Organization (FAO) and United States Department of Agriculture (USDA) standard 2–50 μm system. Measurements made using the hydrometer variations overestimated the sand fraction in all samples. There was a positive correlation in the clay proportion between the Pipette method and Shaking + Stirring treatment (r = 0.644, p-value = 0.044). Treatments involving shaking instead of stirring, increased concentrations of hydrogen peroxide and calgon estimated the clay proportion with sufficient accuracy. These observations are indicative of the need for soil pre-treatment with hydrogen peroxide to remove organic matter and also the use 10% calgon as a dispersing agent.

Preparation and Characterization of Butterfly Pea (Clitoria ternatea L.) Nanoemulgel

BACKGROUND: Butterfly Pea or Asian pigeonwing (Clitoria ternatea L.) has been widely used by people. This flower species contains flavonoid and phenolic with antioxidant activities. Further, the antioxidant in flowers can be processed into nanoemulgel facial makeup. The emulgel is expected to provide better drug delivery, thus maximizing the anti-aging effects. AIM: The aim of this study was to identify the effect of the gel basis variation in the preparation and characterization of the nanoemulgel of Asian pigeonwing extract using the particle size analysis or PSA method. METHODS: In this experimental laboratory research, the independent variable comprised the variants of gelling agent bases, namely, carbopol 940, hydroxy prophyl methyl cellulose, and sodium carboxy methyl cellulose. Research tools involved magnetic stirrer, atomizer, spectrophotometer ultraviolet–visible, and particle size analyzer. The dependent variable consisted of the particle size, polydispersity index, and physical stability of nanoemulgel preparations. Instruments of the research encompassed three formula of emulgel, namely, F1 (using carbopol 940 0.2% base), F2 (using HPMC 0.2% base), and F3 (using Na CMC 0.2% base). All data were analyzed using the one-way ANOVA and Kruskal–Wallis test. The research was conducted from January to May 2021 at the Laboratory of Pharmacy Technology, Gorontalo Polytechnic of Health, the Natural Medicine Laboratory of the National Food and Drug Control Agency, and UII Laboratory Yogyakarta. RESULTS: The present work revealed that the F3 formula with Na CMC base is the best and most stable formula with the particle size measuring at 14.7 nm and polydispersity index (PDI) at 0.271. CONCLUSION: The gel base variation of the preparation produces different physical quality of Asian pigeonwing nanoemulgel with the best characteristics in the formula based on Na CMC.

Testing the integral suspension pressure method for soil particle size analysis across a range of soil organic matter contents

Testing the integral suspension pressure method for soil particle size analysis across a range of soil organic matter contents

A Novel Method for Rapid Particle Size Analysis of Ibuprofen Using Near-infrared Spectroscopy.

Particle size distribution (PSD) is often considered as critical material attribute for active pharmaceutical ingredients (APIs), and the need for regular evaluation stands as an important quality control parameter in the pharmaceutical industry. Near-infrared (NIR) spectroscopy, used routinely for API identification, was introduced as analytical tool for simultaneous determination of particle size of ibuprofen. The demonstrated potential was highlighted by the development of rapid, robust, and noninvasive method coupled with multivariate data analysis (MVA), which can be easily transferred in QC laboratories for routine analysis. Principal component analysis (PCA) and partial least squares (PLS) regression analyses were performed on a calibration set of 61 ibuprofen samples, which differed in their median particle size Dv(50). The score scatterplots revealed evident clustering of ibuprofen samples according to their particle size, as well as occurrence of a distinctive outlying group of ibuprofen samples originating from one manufacturer. Further testing by means of mid-infrared spectroscopy, X-ray powder diffraction, and particle morphology analysis pinpointed particle morphology being responsible for the observed outlying group. Consequently, PLS class modeling based on particle morphology was introduced, which delivered two separate PLS regression models: one for blade-like ibuprofen crystals and another for irregular plate-like ibuprofen crystals. The former regression model exhibited high correlation coefficients and satisfactory predictive power (R2X = 0.999, R2Y = 0.917, Q2 = 0.901), whereas the latter demonstrated lower statistical indicators (R2X = 0.99, R2Y = 0.72, Q2 = 0.55). Additionally, the study underlines the importance of particle shape evaluation and sample classification according to particle morphology similarity prior to building NIRS-based regression models for PSD determination.

Sand Production of the Shale Gas Well in Different Production Periods: Structure and Component

Complex geology and fracturing operations have led to frequent sand production problem in the shale gas well. Sand production brings huge engineering risks and seriously affects the normal production of the shale gas well. In order to study the property and source of the yielded sand, sand samples in three production periods of flowback, production test and gas production are collected from Sichuan Basin of China. Combining the methods of particle size analysis, microscope observation, scanning electron microscope, CT scanning, infrared spectroscopy and energy dispersive spectrum analysis, the multi-scale structure and composition characteristics of the yielded sand from different production periods were investigated. Results show that the sand size is the largest in the production test period and the smallest in the gas production period. The large-size sand is blocky in the flowback period, while it is flaky in the period of production test and gas production. The roundness of sand becomes worse as the sand size decreasing. Sand composition has the characteristics of fracturing proppant and shale mineral. Cementing material between large-size sands has the network structure and the higher content of aluminum and iron. Organic chemicals are found to be adhered to the sand surface in all three periods. Both shale fracture and proppant failure can generate particles that provide the material source for sand production. This research provides the source of the yielded sand and a theoretical guidance for the sand production mechanism.

The improved integral suspension pressure method (ISP+) for precise particle size analysis of soil and sedimentary materials

The Integral Suspension Pressure (ISP) method is a technique to determine the continuous particle size distribution (PSD) of soil materials by inverse modeling of suspension pressure data in a sedimentation experiment. The objective function in ISP includes externally determined sand fractions and a time series of measured suspension pressures. Practical experience with ISP has shown that the precision of the method for the clay fraction is not satisfying. In this contribution, we present a further developed method called "ISP+" to improve the accuracy. This is achieved by additionally including in the objective function the dry particle mass of a collected subsample of the suspension containing fine material, mainly clay. This regularizes the inverse problem and reduces the uncertainty of the determined PSD in the fine particle range. The application of the methodology is illustrated with five soils tested with an adapted PARIO™ system (METER Group AG, Munich, Germany). The results show a significantly improved precision of the ISP+ results in the range of silt and clay particles and very good agreement with the pipette method, which serves as the reference. The measurement time could be reduced from 8 h (ISP) to about 2 h (ISP+) without affecting the accuracy.

Preparation and characterization of halogen-free flame retardant MCA core-shell microcapsules coated with melamine or acrylic acid resin

The resin melamine cyanurate (MCA) core-shell microcapsules were prepared by surface coatingmodification of halogen-free flame retardant MCA using melamine resin and acrylic resin as wall materials. The influence of different wall materials on the coating effect of halogen-free flame retardant MCA was studied by SEM, particle size analysis, IR, and DSC and TGA methods. The results showed that the melamine resin had a high degree of polymerization and decomposed at about 160°, which had a surface modification effect on MCA and did not affect its flame retardant performance. The surface coating rate of poly(methyl methacrylate) PMMA-MCA core-shell microcapsules was about 80%. Afteradding acrylic acid (AA) as the second monomer the coating effect was significantly improved and the thermal decomposition temperature of the wall material of the microcapsule was reduced.

Superpixel Image Segmentation-Based Particle Size Distribution Analysis of Fragmented Rock

Research on the particle size of blast piles has always been an essential issue in mining engineering. Reasonable blasting parameters can reduce mining costs and reduce the workload of secondary crushing, which can significantly improve mining efficiency. The usual particle size analysis methods include the sieving method, the large particle size statistical method and other manual measurement methods. Nevertheless, these methods have the disadvantages of a high labor intensity, low efficiency and low precision. This paper analyzes UAV image information based on the single-picture photogrammetry method of computer image processing technology. A two-dimensional empirical wavelet transform (EWT) is used for image noise reduction. The nonlocal multiscale fractional differential (NMFD) enhances the texture of dark images and uses superpixel image segmentation technology so that the processed image can meet the granularity statistical study requirements of blast piles. The research results show that the accuracy of the ore particle size distribution by the method proposed in this paper is more than 90%.

Preparation, characterization and foaming performance of thermally expandable microspheres

Thermal expansion microcapsules (TEMs) are widely used in various fields due to their unique structures. In recent years, TEMs have attracted much attention and have broad market application prospects. In this study, thermally expandable microcapsules with a core–shell structure were prepared by suspension polymerization using acrylonitrile (AN), methyl methacrylate (MMA), and methyl acrylate (MA) as monomers and low-boiling alkane as the core material. Through particle size analysis, morphology test, thermal analysis and other methods, the effects of core material types, single core material and mixed core material, dispersion system on the microcapsule structure, particle size distribution, and expansion properties were compared. Moreover, the core material with a content of 35% can make the expansion ratio of the microcapsules up to 4 times. The expansion performance of the microcapsules with a mixture of isopentane and isooctane (ratio 1:1) as the core material was increased by 27% compared with that of a single core material. In addition, comparing with colloidal SO2/PVP dispersant, the expansion ratio of the microcapsules with magnesium hydroxide as the dispersant was increased by 20%. Finally, the optimized method for preparing thermally expandable microcapsules was obtained.

Quantitative Relationships Between Pore Tortuosity, Pore Topology, and Solid Particle Morphology Using a Novel Discrete Particle Size Algorithm

To sustain the continuous high-rate charge current required for fast charging of electric vehicle batteries, the ionic effective diffusion coefficient of the electrodes must be high enough to avoid the electrode being transport limited. Tortuosity factor and porosity are the two microstructure parameters that control this effective diffusion coefficient. While different methods exist to experimentally measure or calculate the tortuosity factor, no generic relationship between tortuosity and microstructure presently exists that is applicable across a large variety of electrode microstructures and porosities. Indeed, most relationships are microstructure specific. In this work, generic relationships are established using only geometrically defined metrics that can thus be used to design thick electrodes suitable for fast charging. To achieve this objective, an original, discrete particle-size algorithm is introduced and used to identify and segment particles across a set of 19 various electrode microstructures (nickel-manganese-cobalt [NMC] and graphite) obtained from X-ray computed tomography (CT) to quantify parameters such as porosity, particle elongation, sinuosity, and constriction, which influence the effective diffusion coefficient. Compared to the widely used watershed method, the new algorithm shows less over-segmentation. Particle size obtained with different numerical methods is also compared. Lastly, microstructure-tortuosity relationship and particle size and morphology analysis methods are reviewed.

Synthesis of yttrium citrate from yttrium carbonate hydroxide and citric acid

The reactions of citric acid with freshly precipitated basic carbonate under the hydrothermal conditions (at 80, 100 and 120 °C) were studied in order to obtain yttrium citrate. The obtained results of the analysis for the H and C contents, thermogravimetric studies and structure analysis by XRD indicate that yttrium citrate dihydrate was formed after the 72 h - synthesis. The particle size analysis method of static light scattering showed that 72% of the particles had a diameter of 0.1–02 μm and 28% of particles with sizes from 0.5 to 10 μm.