Particle Size Distribution Measurements Research Articles

Analytical deconvolution of smearing effect for inversion of scanning mobility particle sizer data

The scanning mobility particle sizer (SMPS) is a key instrument for aerosol studies that enables rapid measurement of particle size distribution. When SMPS data are inverted, the smearing effect needs to be considered. Previous studies used numerical methods to deconvolute the smearing effect. In this paper, to reduce the complexity of SMPS data inversion, we derive an analytical formula for de-smearing, and include our de-smearing formula into a full SMPS data inversion scheme. We also propose the voltage step change experiment to characterize the smearing effect of an SMPS. The effectiveness and robustness of our de-smearing approach were demonstrated using experimental data.

A comparative analysis of in situ measurements of high-altitude cirrus in the tropics

Abstract. We analyze cirrus cloud measurements from two dual-instrument cloud spectrometers, two hygrometers and a backscattersonde with the goal of connecting cirrus optical parameters usually accessible by remote sensing with microphysical size-resolved and bulk properties accessible in situ. Specifically, we compare the particle backscattering coefficient and depolarization ratio to the particle size distribution, effective and mean radius, surface area density, particle aspherical fraction, and ice water content. Data were acquired by instruments on board the M55 Geophysica research aircraft in July and August 2017 during the Asian Monsoon campaign based in Kathmandu, Nepal, in the framework of the StratoClim (Stratospheric and upper tropospheric processes for better climate predictions) project. Cirrus clouds have been observed over the Himalayan region between 10 km and the tropopause, situated at 17–18 km. The observed particle number densities varied between 10 and 10−4 cm−3 in the dimensional range from 1.5 to 468.5 µm in radius. Correspondingly, backscatter ratios from 1.1 up to 50 have been observed. Optical-scattering theory has been used to compare the backscattering coefficients computed from the measured particle size distribution with those directly observed by the backscattersonde. The aspect ratio of the particles, modeled as spheroids for the T-matrix approach, was left as a free parameter to match the calculations to the optical measures. The computed backscattering coefficient can be brought into good agreement with the observed one, but the match between simulated and measured depolarization ratios is insufficient. Relationships between ice particle concentration, mean and effective radius, surface area density, and ice water content with the measured backscattering coefficient are investigated for an estimate of the bulk microphysical parameters of cirrus clouds from remote sensing lidar data. The comparison between particle depolarization and aspherical fraction as measured by one of the cloud spectrometers equipped with a detector for polarization represents a novelty since it was the first time the two instruments were operated simultaneously on an aircraft. The analysis shows the difficulty of establishing an univocal link between depolarization values and the presence and amount of aspherical scatterers. This suggests the need for further investigation that could take into consideration not only the fraction of aspheric particles but also their predominant morphology.

Alteration of Hordeum vulgare and Sinapis alba germination and early growth in response to airborne low-metallic automotive brake wear debris

Road transportation significantly contributes to environmental pollution, both in terms of exhaust and non-exhaust (brake wear) emissions. As was proven, brake wear debris is released in a wide variety of sizes, shapes, and compositions. Although studies confirming the possible adverse health and environmental impact of brake wear debris were published, there is no standardized methodology for their toxicity testing, and most studies focus only on one type of brake pad and/or one test. The lack of methodology is also related to the very small amount of material released during the laboratory testing. For these reasons, this study deals with the mixture of airborne brake wear debris from several commonly used low-metallic brake pads collected following the dynamometer testing. The mixture was chosen for better simulation of the actual state in the environment and to collect a sufficient amount of particles for thorough characterization (SEM, XRPD, XRF, chromatography, and particle size distribution) and phytotoxicity testing. The particle size distribution measurement revealed a wide range of particle sizes from nanometers to hundreds of nanometers, elemental and phase analysis determined the standard elements and compounds used in the brake pad formulation. The Hordeum vulgare and Sinapis alba were chosen as representatives of monocotyledonous and dicotyledonous plants. The germination was not significantly affected by the suspension of brake wear debris; however, the root elongation was negatively influenced in both cases. Sinapis alba (IC50 = 23.13 g L−1) was more affected than Hordeum vulgare (IC50 was not found in the studied concentration range) the growth of which was even slightly stimulated in the lowest concentrations of brake wear debris. The plant biomass was also negatively affected in the case of Sinapis alba, where the IC50 values of wet and dry roots were determined to be 44.83 g L−1 and 86.86 g L−1, respectively.

Numerical simulation and evaluation of global ultrafine particle concentrations at the Earth's surface

Abstract. A new global dataset of annually averaged ultrafine particle (UFP) concentrations at the Earth's surface for the years 2015–2017 has been developed through numerical simulations using the ECHAM/MESSy Atmospheric Chemistry model (EMAC). We present total and size-resolved concentrations along with their interannual variability. Size distributions of emitted particles from the contributing source sectors have been derived based on literature reports. The model results of UFP concentrations are evaluated using particle size distribution and particle number concentration measurements from available datasets and the literature. While we obtain reasonable agreement between the model results and observations (logarithmic-scale correlation of r=0.76 for non-remote, polluted regions), the highest values of observed, street-level UFP concentrations are systematically underestimated, whereas in rural environments close to urban areas the model generally overestimates observed UFP concentrations. As the relatively coarse global model does not resolve concentration gradients in urban centres and industrial UFP hotspots, high-resolution data of anthropogenic emissions are used to account for such differences in each model grid box, obtaining UFP concentrations with unprecedented 0.1∘×0.1∘ horizontal resolution at the Earth's surface. This observation-guided downscaling further improves the agreement with observations, leading to an increase in the logarithmic-scale correlation between observed and simulated UFP concentrations to r=0.84 in polluted environments (and 0.95 in all regions), a decrease in the root mean squared logarithmic error (from 0.57 to 0.43), and removal of discrepancies associated with air quality and population density gradients within the model grid boxes. The model results are made publicly available for studies on public health and other impacts of atmospheric UFPs, as well as for intercomparison with other regional and global models and datasets.

Image-based simultaneous particle size distribution and concentration measurement of powder blend components with deep learning and machine vision

This work presents a system, where deep learning was used on images captured with a digital camera to simultaneously determine the API concentration and the particle size distribution (PSD) of two components of a powder blend. The blend consisted of acetylsalicylic acid (ASA) and calcium hydrogen phosphate (CHP), and the predicted API concentration was found corresponding with the HPLC measurements. The PSDs determined with the method corresponded with those measured with laser diffraction particle size analysis. This novel method provides fast and simple measurements and could be suitable for detecting segregation in the powder. By examining the powders discharged from a batch blender, the API concentrations at the top and bottom of the container could be measured, yielding information about the adequacy of the blending and improving the quality control of the manufacturing process.

Dynamic evolution investigation on crystal size and morphology of sodium sulfate based on a combination of ultrasonic and image on-line testing

Crystallization is widely used in the fine chemical processes of purification and separation, where the crystal size variation, together with the crystallization temperature, plays a crucial role. An online measurement system for the simultaneous characterization of crystal size and other morphological parameters was studied, in which an ultrasonic spectrometer and image analysis was effectively combined for the monitoring and understanding of key parameters during the entire crystallization of sodium sulfate solution. The change in crystallization temperature, crystal size, and morphology at different cooling rates and stirring rates were analyzed, which shows that the cooling rate plays a dominant role in the variation of the critical time of crystal precipitation and average crystal size. In the middle stage of the crystallization, the median diameter change obtained by the ultrasonic and image analysis is close together, with a relative deviation of less than 10%. While the aspect ratio is mainly distributed in the range of 1–1.6, the crystal size has a relatively stable growth rate. An ultrasonic spectrometer can be used to measure particle size distribution of higher concentrations compared with image analysis. The combination actually provides an effective complement to implementing straightforward testing during the relatively complete crystallization process.

Application of acoustic spectroscopy and neural networks to on-line size measurement of pharmaceutical nanocrystals.

Acoustic spectroscopy and neural networks (NNs) are applied to on-line real-time measurement of particle size distribution (PSD) during wet milling of pharmaceutical nanocrystals. A method for modeling the relationship between acoustic attenuation spectra and PSD is proposed that is based on NNs and principal component analysis (PCA). PCA reduces the dimensions of both the spectra and the PSD; then, a neural network model of 2 × 2 × 2 (input, hidden, output layer nodes) with only eight connection weights is built. Compared with previous instrument models that could require as many as 14 physical properties, the current approach does not need any prior knowledge of the system's properties. In addition, the time taken to complete a PSD measurement is reduced from minutes to seconds and it always generates a single solution, rather than possible multiple PSD solutions as in early methods. Application to hydrotalcite nanomilling found good agreement between the on-line measurements and off-line analysis.

Size distribution of migrating particles and droplets under gravity in concentrated dispersions measured with static multiple light scattering

HypothesisLight scattering techniques can provide a non-intrusive measurement of particle and droplet size distribution but are limited to relatively diluted liquid dispersions. Measurement of particle velocity distributions (PVD) and particle/droplet size distributions (PSD) in diluted to highly concentrated solid suspensions and emulsions can be performed by coupling the static multiple light scattering technique (SMLS) to mathematical models describing the vertical motion under gravity of polydisperse particles and droplets. ExperimentsMeasurement of the PSD using SMLS was performed on silica particles dispersed in water with monomodal, bimodal and trimodal PSDs ranging from 570 nm and 7.90 µm. Quasi-monodisperse certified latex particles with 815 nm mean diameter dispersed in water and non-controlled emulsions of hexadecane-water emulsions at volume fractions ranging from 0.005 % to 20 % were also characterized with SMLS. These measurements were compared to certified size distributions, and to laser diffraction and dynamic light scattering measurements. FindingsRobust, highly resolutive and concentration-dependent measurement of the PVD and PSD of solid particles and droplets was achieved for diluted to highly concentrated liquid dispersions. As interactions between particles or droplets are dependent on the dispersed phase concentration, accurate characterization of as-formulated industrial liquid dispersions can be performed with SMLS.

Effects of ferrocene addition on soot formation characteristics in laminar premixed burner-stabilized stagnation ethylene flames

The influence of ferrocene addition (∼60 ppm on a molar basis) on soot formation in laminar premixed burner-stabilized stagnation ethylene flames (with an equivalence ratio of 2.0) is investigated both experimentally and computationally. The results show that ferrocene addition has a very small effect on both flame temperature and concentrations of small soot precursors from kinetic modeling, but apparently promotes soot inception and particle size growth from particle size distribution measurements, and decreases soot maturity from elemental analysis. Transmission electron microscope (TEM) images and energy dispersive spectrometry (EDS) results show that distinct iron cores are present in large soot aggregates, consistent with the kinetic modeling results that iron predominates over iron oxide in ferrocene-doped flames. Iron in the incipient soot may be too dispersed or form too small cores to be observed by TEM; and as the soot particles coagulate, iron in the soot coalesces into large cores. Since iron is not exposed on the soot surface, and the concentrations of soot precursors are also not significantly increased by ferrocene, ferrocene promotes soot size growth mainly through enhanced coagulation rather than surface growth.

Natural gamma-ray spectrometry as a rapid sensing method for detecting variations in soil shrinking and cracking behaviour: An application case study

Soils which develop desiccation cracks after drying are unsuitable for the making of earthenware. The present work was carried out to demonstrate the use of Natural Gamma-ray Spectrometry (NGS) as a rapid sensing method to detect the variation of cracking behaviour and types of clay dominant in soil using samples collected from the study region. Natural gamma-ray intensities due to potassium (K) and equivalent thorium (eTh) radioisotopes present in soil were recorded using an NGS device. Circular soil cakes of set diameter were sun-dried to find shrinking and cracking variations. Other tests included measurement of particle size distribution, Atterberg indices, basic soil physico-chemical properties, exchangeable cation contents using ICP-OES and XRD identification of clays. 6 soil varieties were identified from the distribution of data points in the binary plots of gamma-ray potassium (GR-K) and thorium (GR-eTh) counts per sec (C/s). Variation of GR-K was observed to be wider (2.14 C/s to 2.54 C/s) than GR-eTh (0.44 C/s to 0.63 C/s). The measured GR-K counts reflect changes in illite content. The soils displayed 3 categories of shrinking and cracking behaviour. The soil variety which displayed maximum mild shrinkage without fine desiccation cracks on the set surface area has the highest GR-K counts. The soil shrinking and cracking variations were not clearly defined by the classification based on the texture and plasticity chart, though the latter indicated dominant smectites. A strong linear relationship between GR-K and exchangeable K (R2 = 0.84) indicates K+ contribution mainly from illite and dominance of other clay types in outliers. Higher levels of polyvalent cations known for binding clay aggregates were observed in the non-cracking soils. Concomitant higher GR-K levels indicate that shrinking soils lacking fine desiccation cracks are associated with fluvial sediments of the recent past with parental mica. This research concludes that NGS-based portable devices can be used for rapid sensing of soils to detect variation in shrinking and cracking behaviour and dominant clay type and thus can be used for identification of soil suitable for earthenware making.

Advanced Particle Size Analysis in High-Solid-Content Polymer Dispersions Using Photon Density Wave Spectroscopy.

High-solid-content polystyrene and polyvinyl acetate dispersions of polymer particles with a 50 nm to 500 nm mean particle diameter and 12-55% (w/w) solid content have been produced via emulsion polymerization and characterized regarding their optical and physical properties. Both systems have been analyzed with common particle-size-measuring techniques like dynamic light scattering (DLS) and static light scattering (SLS) and compared to inline particle size distribution (PSD) measurements via photon density wave (PDW) spectroscopy in undiluted samples. It is shown that particle size measurements of undiluted polystyrene dispersions are in good agreement between analysis methods. However, for polyvinyl acetate particles, size determination is challenging due to bound water in the produced polymer. For the first time, water-swelling factors were determined via an iterative approach of PDW spectroscopy error (Χ2) minimization. It is shown that water-swollen particles can be analyzed in high-solid-content solutions and their physical properties can be assumed to determine the refractive index, density, and volume fraction in dispersion. It was found that assumed water swelling improved the reduced scattering coefficient fit by PDW spectroscopy by up to ten times and particle size determination was refined and enabled. Particle size analysis of the water-swollen particles agreed well with offline-based state-of-the-art techniques.

Modelling Outer Ash Deposition Rates in Second Generation Atmospheric Pressure Oxy-Fuel Combustion Systems

ABSTRACT The particle size distribution (PSD) measurements of coarse fly-ash particles (diameter, dp >10 µm) near the depositing surface are often not available, creating challenges in formulating mechanistic models for ash deposition. This void may be partially alleviated if measurements of deposition rate and PSD of the ash deposits are available. This is demonstrated using well-resolved Computational Fluid Dynamic simulations in conjunction with a particle viscosity and particle kinetic energy based capture criterion to model the outer ash deposition processes for three different fuels (two types of coal and Rice Husk) during their combustion in AIR and O2/CO2 (70/30 vol %, OXY70; 50/50 vol %, OXY50) oxidizer compositions. First, deposition rate predictions for monodisperse fly-ash particles (10 µm < dp < 150 µm) encompassing the aforementioned scenarios were carried out. The PSD of the fly-ash particles were then inferred by mass-weighted averaging the monodisperse fly-ash diameters to match the measured deposition rates as well as the deposit ash PSD. While the methodology proved to be promising in the coal-firing scenarios, the deposit ash PSD predictions for Rice Husk were smaller than their corresponding measurements and may be attributed to irregular particle sizes or necessary modifications to surface capture characteristics.

Effect of morphological properties on the particle size distribution measurements and modelling of porous and nonspherical aerosol behaviour

Estimating the time evolution of the suspended aerosol concentration in nuclear reactor containment is critical in assessing the environmental source term during severe accident conditions. Morphological properties of porous and non-spherical aerosol particles are necessary to convert the measured equivalent size distributions to actual size distributions and modelling the aerosol processes. Towards this, the dynamics of liquid PAO (Poly Alpha Olefin) and metal aerosol (non-radioactive fission product equivalent SrO2; and structural steel) are studied individually in a 1 m3 closed chamber. The effect of initial particle size distributions (PSDs) based on different equivalent diameters and the morphological properties on realistic modeling of experimental results is analysed. Electrical Low-Pressure Impactor (ELPI) and Scanning Mobility Particle Sizer (SMPS) are used to measure concentration decay and size growth. The aerosol dynamics model is validated with PAO aerosol data and applied to metal aerosol. Modelled dynamics using both the aerodynamic and effective density (ρe) corrected mobility equivalent PSDs of ELPI (APSD and MEPSD) agree with the measured values within 10% deviation for PAO aerosol, which are spherical with ρe (0.82 g cm−3) slightly differed from 1 g cm−3. Modelled dynamics using APSD significantly deviate around 77.5–137% for the porous and non-spherical/fractal metal aerosols, irrespective of the morphological properties explicitly used to model the aerosol processes with marginal effect. As ρe of SrO2 and steel aerosols (3.16 and 3.34 g cm−3) are >1 g cm−3, aerodynamic distribution underestimates the coagulation phenomenon, the primary aerosol dynamics process to a larger extent. The mobility equivalent size distributions of ELPI model the aerosol dynamics within 6–23% deviation, as supported by SMPS measurements. This study can be extended to ascertain the input parameters required for improved estimations of sodium combustion aerosol dynamics, which has added complexity of hygroscopic growth and time-varying chemical speciation.

Development of a two-column particle sizer (TC-PS) for simultaneous measurements of particle concentration and size distribution

Development of a two-column particle sizer (TC-PS) for simultaneous measurements of particle concentration and size distribution

Measuring particle size distribution of ground coffee using computer vision

Measuring particle size distribution of ground coffee using computer vision

Direct extraction of biphasic organosolv lignin for producing aromatic aldehydes via alkaline oxidation

Lignin can be a sustainable source of aromatic compounds, whereas the utilization is limited because of its complex three-dimensional structure. Organosolv method is promising for the valorization of lignin because of its mild conditions as compared with industrial pulping processes. Aromatic aldehydes, widely used in various industries, are obtained by catalytic oxidation of lignin. Organosolv treatment of various types of lignocellulose in water/1-butanol solvent was conducted using a batch type reactor. During the solvent removal from 1-butanol phase containing organosolv lignin, the concentrated lignin was denatured, which was evaluated by measuring particle size distribution and thermal decomposition behavior of the lignin. The recovery procedure of lignin was improved, and the extraction of organosolv lignin from 1-butanol phase to alkaline solution was developed. The improved extraction method definitely showed a higher yield of aromatic compounds regardless of the type of lignocellulose, yielding 14 C-mol% of aromatic aldehydes after alkaline oxidation of willow-derived lignin. After the alkaline oxidation reaction, a simple solvent fractionation was applied for refining the oxidized products. The solvent fractionation of the oxidized products was achieved using ethyl acetate and n-heptane. n-Heptane-soluble fraction selectively contained the lighter fraction with maintaining the content of aromatic compounds.

Measurement of Fly Ash Particle Size Distribution Using Lensless Digital In-Line Holography

Abstract We propose the use of a lensless digital in-line holography setup for the measurement of particle size distribution (PSD) of fly ash obtained from wet electrostatic precipitators of different power plants. The fly ash samples were prepared by spreading the ash nonuniformly over a glass slide. A number of holograms corresponding to distinct regions of the glass slide were recorded and reconstructed. The particle sizes in each reconstructed image were estimated using a circular Hough transform–based edge detection algorithm. PSDs in the range of 10 to 90 μm were obtained. A numerical scheme to extend the measurement range below 10 μm is discussed. The performance of the proposed method is compared with the laser particle-size analyzer and conventional hydrometer. The experimental results indicate that the performance of the proposed method is similar to the hydrometer, with lower experimental and time complexity.

Influence of Nanofluid Flooding on Oil Displacement in Porous Media

Hydrocarbon displacement at the pore scale is mainly controlled by the wetness properties of the porous media. Consequently, several techniques including nanofluid flooding were implemented to manipulate the wetting behavior of the pore space in oil reservoirs. This study thus focuses on monitoring the displacement of oil from artificial glass porous media, as a representative for sandstone reservoirs, before and after nanofluid flooding. Experiments were conducted at various temperatures (25 – 50° C), nanoparticles concentrations (0.001 – 0.05 wt% SiO2 NPs), salinity (0.1 – 2 wt% NaCl), and flooding time. Images were taken via a high-resolution microscopic camera and analyzed to investigate the displacement of the oil at different conditions. In addition, contact angle measurements on quartz surfaces were also conducted at similar conditions to understand the flow behavior in the porous media. Further, zeta potential and particle size distribution measurements were conducted to examine the stability of the injected nanofluids. Results revealed that the injection of nanofluids into oil-wet pore space can significantly enhance the recovery rate of hydrocarbon by altering the wettability of the porous media. However, salinity, particularly at high nanoparticles concentration (≥ 0.005) can dramatically reduce the efficiency of nanofluid. Further, increased aging time can improve the ability of nanofluid to alter the wettability of the surface, and thus more oil can be displaced. Thus, nanofluid can efficiently enhance oil recovery if correctly formulated.

Computational Modeling of Magnesium Hydroxide Precipitation and Kinetics Parameters Identification.

Magnesium is a critical raw material and its recovery as Mg(OH)2 from saltwork brines can be realized via precipitation. The effective design, optimization, and scale-up of such a process require the development of a computational model accounting for the effect of fluid dynamics, homogeneous and heterogeneous nucleation, molecular growth, and aggregation. The unknown kinetics parameters are inferred and validated in this work by using experimental data produced with a T2mm-mixer and a T3mm-mixer, guaranteeing fast and efficient mixing. The flow field in the T-mixers is fully characterized by using the k-ε turbulence model implemented in the computational fluid dynamics (CFD) code OpenFOAM. The model is based on a simplified plug flow reactor model, instructed by detailed CFD simulations. It incorporates Bromley's activity coefficient correction and a micro-mixing model for the calculation of the supersaturation ratio. The population balance equation is solved by exploiting the quadrature method of moments, and mass balances are used for updating the reactive ions concentrations, accounting for the precipitated solid. To avoid unphysical results, global constrained optimization is used for kinetics parameters identification, exploiting experimentally measured particle size distribution (PSD). The inferred kinetics set is validated by comparing PSDs at different operative conditions both in the T2mm-mixer and the T3mm-mixer. The developed computational model, including the kinetics parameters estimated for the first time in this work, will be used for the design of a prototype for the industrial precipitation of Mg(OH)2 from saltwork brines in an industrial environment.

Polarized imaging dynamic light scattering for simultaneous measurement of nanoparticle size and morphology

The performance of nanoparticles is often affected by particle size and morphology. Currently, electron microscopy or atomic force microscopy is typically utilized to determine the size and morphology of nanoparticles. However, there are issues such as difficult sample preparation, long processing times, and challenges in quantitative characterization. Therefore, it is of great significance to develop a fast, accurate, and statistical method to measure the size and morphology of nanoparticles. In this study, a new method, called polarized imaging dynamic light scattering (PIDLS), is proposed. The nanoparticles are irradiated with a vertical linearly polarized laser beam, and a polarization camera collected the dynamic light scattering images of particles at four different polarization directions (0°, 45°, 90°, and 135°) at a scattering angle of 90°. The average particle size and distribution are obtained using the imaging dynamic light scattering method at 0° polarization direction, and the morphology of the particles is obtained based on the depolarization patterns of the scattered light. The optical sphericity Ф is defined based on the degree of linear polarization (DoLP). It is also implemented for the quantitative evaluation of the sphericity of the nanoparticles, including spherical, octahedral, nanoplate, nanorod, and linear ones. Together with the Poincaré sphere parameter ψ, the morphology of the nanoparticles can be roughly identified. In addition, PIDLS enables the measurement of particle size and morphology distributions simultaneously for evaluating the uniformity of particles. The effectiveness of PIDLS is verified by the measurement of five kinds of industrial titanium dioxide as well.