Properties Of Individual Particles Research Articles

Solid organic-coated ammonium sulfate particles at high relative humidity in the summertime Arctic atmosphere

SignificancePhysical and chemical properties of individual atmospheric particles determine their climate impacts. Hygroscopic inorganic salt particles mixed with trace amounts of organic material are predicted to be liquid under typical tropospheric conditions in the summertime Arctic. Yet, we unexpectedly observed a significant concentration of solid particles composed of ammonium sulfate with an organic coating under conditions of high relative humidity and low temperature. These particle properties are consistent with marine biogenic-derived new particle formation and growth, with particle collision hypothesized to result in the solid phase. This particle source is predicted to have increasing relevance in the context of declining Arctic sea ice and increasing open water, with impacts on clouds, and therefore climate.

Effects of Particle Shape on the Shear Wave Velocity and Shear Modulus of 3D Printed Sand Analogs

Isolating the effects of individual particle properties (e.g. shape, size, mineralogy, surface roughness) on the mechanical behavior of naturally occurring coarse-grained soils is a significant challenge in experimental studies. This challenge can be addressed by recent advances in 3D printing technology which enable generation of artificial sand-sized particles with independent control over particle size and shape. In this study, bender element tests are conducted to examine the isolated effects of particle shape on the shear wave velocity and shear modulus of 3D printed sand analogs. The experimental results show that the shear wave velocity and shear modulus of the 3D printed sand specimens exhibit a relationship with mean effective stress that is in agreement to that reported for natural sands. The specimens composed of 3D printed sands with greater particle roundness and sphericity exhibit greater shear wave velocity and shear modulus for a given void ratio, relative density, and mean effective stress. The changes in shear wave velocity can be captured in terms of differences in individual particle shape parameters such as roundness and sphericity as well as combined particle shape parameters such as regularity. Regression analysis is used to develop relationships between shear wave velocity and particle shape parameters and void ratio, which are shown to be in agreement with previously-published relationships and to reliably predict the shear wave velocity of natural sands. The results presented herein highlight the usefulness of testing 3D printed soils to identify functional trends and dependencies between soil response parameters and intrinsic properties. However, this requires verification of the results against published trends and assessment of the possible effects of the differences in constituent material between the 3D printed and the natural soils.

Percolation-based simulation to predict caking kinetics of polydisperse amorphous powders

Caking in amorphous powders compromises their quality during storage. Individual particles absorb water vapor, which changes their viscosity and promotes the formation of sinter bridges. Lumps of particles grow and eventually span the whole powder, affecting the mechanical properties and quality of the powder. Previous studies of the caking dynamics largely neglect the role of spatial heterogeneities in the particle-size distribution. We perform particle-based simulations and show that, if caking is mapped into a percolation transition, the role of spatial heterogeneities is well captured by the corresponding percolation threshold. Since this threshold only depends on the geometry of the granular assembly, we can separate the contribution of the spatial heterogeneities and of the individual particle properties. This enables a rational approach for interpreting and mitigating caking propensity of commercial products consisting of particle species with different particle size distributions. We corroborate the numerical and analytical predictions with experiments.

Lightweight Cement-Based Composites Incorporating Hollow Glass Microspheres: Fresh and Hardened State Properties

This research aims to develop a lightweight cementitious composite with satisfied mechanical and good thermal insulating properties. Two different types of hollow glass microspheres were used as lightweight aggregates and were substituted with fine aggregate by 10, 20 and 40% by volume. The rheological, physical, mechanical and microstructural properties of the resulting HGM-incorporated composites are investigated. The results showed that physical and mechanical properties of individual HGM particles plays a dominant role on the properties of lightweight cement mortars. HGM addition provided reductions up to 20% in the density and 45% in the thermal conductivity values of mortars compared to the reference. The optimum HGM ratio is suggested as 20%, which provides benefits such as reduced density and improved thermal insulation capability without causing significant reduction in compressive strength. It was concluded that HGMs can be used in the lightweight cementitious mortar production which have great potential in building applications to reduce the heating energy consumption.

Ultrasonic attenuation model of mixed particle three-phase system based on Monte Carlo method

From the perspective of calculating ultrasonic absorption and scattering properties of individual solid particle and droplet, the ultrasonic wave is treated as discrete phonons. And by tracking their motion process and event statistics, a new prediction model of ultrasonic attenuation of spherical mixed particles in gaseous medium is established with Monte Carlo method. Considering the difference in physical properties between solid particles and liquid particles, the ultrasonic absorption characteristics of the two kinds of particles are obviously different, and when dimensionless particle size <i>kR</i> ≤ 1, the backscattering of particles is uniform and dominant, then the ultrasonic scattering pressures gradually transit from the dominant position of backscattering to the trend of forward enhancement with the increase of dimensionless particle size. The numerical simulation results for the system with a single particle type are compared with those from various standard models such as classical ECAH model and McC model, showing that they are in good agreement. Similarly, the results are then compared with experimental results, which accord with each other in general. After calculating and verifying the ultrasonic attenuation of aluminum particles and submicron droplets respectively in air, the method is extended to the three-phase monodisperse and polydisperse mixed particle system composed of aluminum particles and liquid droplets. In the three-phase system of gas-liquid-solid mixed particles, the particle type has a significant influence on ultrasonic attenuation, and the attenuation contribution of different particles against mixing ratio does not follow the linear gradient with the increase of volume concentration. For a polydisperse system, the ultrasonic attenuation spectrum is greatly affected by the average particle size, but it is insensitive to the width of particle size distribution. The numerical results also show that both the particle type and particle distribution size should be carefully take into account in the polydisperse system. Moreover, the MCM model can be further extended to non-spherical particles and combined with mathematical inversion to form the theoretical basis for the measurement of mixed particle system.

Impact of dry intrusion events on the composition and mixing state of particles during the winter Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA)

Abstract. Long-range transport of continental emissions has a far-reaching influence over remote regions, resulting in substantial change in the size, morphology, and composition of the local aerosol population and cloud condensation nuclei (CCN) budget. Here, we investigate the physicochemical properties of atmospheric particles collected on board a research aircraft flown over the Azores during the winter 2018 Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA) campaign. Particles were collected within the marine boundary layer (MBL) and free troposphere (FT) after long-range atmospheric transport episodes facilitated by dry intrusion (DI) events. Chemical and physical properties of individual particles were investigated using complementary capabilities of computer-controlled scanning electron microscopy and X-ray spectromicroscopy to probe particle external and internal mixing state characteristics. Furthermore, real-time measurements of aerosol size distribution, cloud condensation nuclei (CCN) concentration, and back-trajectory calculations were utilized to help bring into context the findings from offline spectromicroscopy analysis. While carbonaceous particles were found to be the dominant particle type in the region, changes in the percent contribution of organics across the particle population (i.e., external mixing) shifted from 68 % to 43 % in the MBL and from 92 % to 46 % in FT samples during DI events. This change in carbonaceous contribution is counterbalanced by the increase in inorganics from 32 % to 57 % in the MBL and 8 % to 55 % in FT. The quantification of the organic volume fraction (OVF) of individual particles derived from X-ray spectromicroscopy, which relates to the multi-component internal composition of individual particles, showed a factor of 2.06 ± 0.16 and 1.11 ± 0.04 increase in the MBL and FT, respectively, among DI samples. We show that supplying particle OVF into the κ-Köhler equation can be used as a good approximation of field-measured in situ CCN concentrations. We also report changes in the κ values in the MBL from κMBL, non-DI=0.48 to κMBL, DI=0.41, while changes in the FT result in κFT, non-DI=0.36 to κFT, DI=0.33, which is consistent with enhancements in OVF followed by the DI episodes. Our observations suggest that entrainment of particles from long-range continental sources alters the mixing state population and CCN properties of aerosol in the region. The work presented here provides field observation data that can inform atmospheric models that simulate sources and particle composition in the eastern North Atlantic.

Coupling between turbulence and solar-like oscillations: A combined Lagrangian PDF/SPH approach

Context. The development of space-borne missions such as CoRoT and Kepler now provides us with numerous and precise asteroseismic measurements that allow us to put better constraints on our theoretical knowledge of the physics of stellar interiors. In order to utilise the full potential of these measurements, however, we need a better theoretical understanding of the coupling between stellar oscillations and turbulent convection. Aims. The aim of this series of papers is to build a new formalism specifically tailored to study the impact of turbulence on the global modes of oscillation in solar-like stars. In building this formalism, we circumvent some fundamental limitations inherent to the more traditional approaches, in particular the need for separate equations for turbulence and oscillations, and the reduction of the turbulent cascade to a unique length and timescale. In this first paper we derive a linear wave equation that directly and consistently contains the turbulence as an input to the model, and therefore naturally contains the information on the coupling between the turbulence and the modes through the stochasticity of the equations. Methods. We use a Lagrangian stochastic model of turbulence based on probability density function methods to describe the evolution of the properties of individual fluid particles through stochastic differential equations. We then transcribe these stochastic differential equations from a Lagrangian frame to a Eulerian frame more adapted to the analysis of stellar oscillations. We combine this method with smoothed particle hydrodynamics, where all the mean fields appearing in the Lagrangian stochastic model are estimated directly from the set of fluid particles themselves, through the use of a weighting kernel function allowing to filter the particles present in any given vicinity. The resulting stochastic differential equations on Eulerian variables are then linearised. As a first step the gas is considered to follow a polytropic relation, and the turbulence is assumed anelastic. Results. We obtain a stochastic linear wave equation governing the time evolution of the relevant wave variables, while at the same time containing the effect of turbulence. The wave equation generalises the classical, unperturbed propagation of acoustic waves in a stratified medium (which reduces to the exact deterministic wave equation in the absence of turbulence) to a form that, by construction, accounts for the impact of turbulence on the mode in a consistent way. The effect of turbulence consists of a non-homogeneous forcing term, responsible for the stochastic driving of the mode, and a stochastic perturbation to the homogeneous part of the wave equation, responsible for both the damping of the mode and the modal surface effects. Conclusions. The stochastic wave equation obtained here represents our baseline framework to properly infer properties of turbulence-oscillation coupling, and can therefore be used to constrain the properties of the turbulence itself with the help of asteroseismic observations. This will be the subject of the rest of the papers in this series.

Measurements of scattering and absorption properties of submillimeter bauxite and silica particles

Submillimeter solid particles have been considered as thermal storage media for concentrated solar power applications. Knowledge of the scattering and absorption properties of individual particles is crucial for modeling the radiative heat transfer of the particle bed. In this work, a laser scatterometer is used to measure the single-particle scattering properties at a wavelength of 635 nm by using two configurations: (1) a falling particle curtain and (2) a taped particle layer. Because a one-particle nominal thickness is formed with area fractions of 5−55% depending on the configuration, multiple scattering is minimized and hence the single scattering phase function, averaged over all illuminated particles, is directly measured. Bauxite-based ceramic particles that are strongly absorbing in the solar spectrum and silica particles that are nonabsorbing in the visible and near-infrared are investigated. The directional-hemispherical reflectance and transmittance of the taped particles are also measured to deduce the forward and backward scattering efficiency factors and the absorption efficiency factors. Only weak wavelength dependence is observed in the measured region from 380 nm to 1020 nm. The scattering phase functions of all bauxite-based particles with varying sizes and compositions are very similar and can be fitted to a Henyey−Greenstein phase function with an asymmetry factor g = −0.20. For the silica particles, forward scattering dominates and g = 0.45 yields the best fit. A Monte Carlo method is developed to model the particle scattering characteristics, and reasonable agreements between the modeling and experimental results are observed by introducing a specularity parameter.

Accounting Carbonaceous Counterfeits in Graphene Materials Using the Thermogravimetric Analysis (TGA) Approach.

Counterfeits in the supply chain of high-value advanced materials such as graphene and their derivatives have become a concerning problem with a potential negative impact on this growing and emerging industry. Recent studies have revealed alarming facts that a large percentage of manufactured graphene materials on market are not graphene, raising considerable concerns for the end users. The common and recommended methods for the characterization of graphene materials, such as transmission electron microscopy (TEM), atomic force microscopy (AFM), and Raman spectroscopy based on spot analysis and probing properties of individual graphene particles, are limited to provide the determination of the properties of "bulk" graphene powders at a large scale and the identification of non-graphene components or purposely included additives. These limitations are creating counterfeit opportunities by adding low-cost black carbonaceous materials into manufactured graphene powders. To address this problem, it is critical to have reliable characterization methods, which can probe the specific properties of graphene powders at bulk scale, confirm their typical graphene signature, and detect the presence of unwanted additional compounds, where the thermogravimetric analysis (TGA) method is one of the most promising methods to perform this challenging task. This paper presents the evaluation of the TGA method and its ability to detect low-cost carbon additives such as graphite, carbon black, biochar, and activated carbon as potential counterfeiting materials to graphene materials and their derivatives such as graphene oxide (GO) and reduced GO. The superior performance of the TGA method is demonstrated here, showing its excellent capability to successfully detect these additives when mixed with graphene materials, which is not possible by two other comparative methods (Raman spectroscopy and powder X-ray diffraction (XRD)), which are used as the common characterization methods for graphene materials.

Radiative properties of alumina/aluminum particles and influence on radiative heat transfer in solid rocket motor

The thermal radiation of micron-sized condensed phase particles plays a dominant role during the heat transfer process in aluminized Solid Rocket Motors (SRMs). Open research mainly focuses on the radiative properties of alumina particles while the study considering the presence of aluminum is lacking. In addition, the thermal radiation inside the SRM with consideration of the participating particles is seldom studied. In this work, the multiscale method of predicting the thermal environment inside SRMs is established from the particle radiation at microscale to the two-phase flow and heat transfer at macroscale. The effective gray radiative properties of individual particles (alumina, aluminum, and hybrid alumina/aluminum) and particles cloud are investigated with the Mie theory and approximate method. Then a numerical method for predicting the thermal environment inside SRMs with considering particle radiation is established and applied in a subscale motor. The convective and radiative heat flux distributions along inner wall of motor are obtained, and it is found that the heat transfer in the combustion chamber is dominated by thermal radiation and the radiative heat flux is essentially a constant of 5.6–6.8 MW/m2. The convective heat transfer plays a dominant role in the nozzle and the heat flux reaches the maximum value of 11.2 MW/m2 near the throat. As the combustion efficiency of aluminum drops, the radiative heat flux remains unchanged in most regions and increases slightly along the diverging section wall of the nozzle.

Flow-Through Quantification of Microplastics Using Impedance Spectroscopy.

Understanding the sources, impacts, and fate of microplastics in the environment is critical for assessing the potential risks of these anthropogenic particles. However, our ability to quantify and identify microplastics in aquatic ecosystems is limited by the lack of rapid techniques that do not require visual sorting or preprocessing. Here, we demonstrate the use of impedance spectroscopy for high-throughput flow-through microplastic quantification, with the goal of rapid measurement of microplastic concentration and size. Impedance spectroscopy characterizes the electrical properties of individual particles directly in the flow of water, allowing for simultaneous sizing and material identification. To demonstrate the technique, spike and recovery experiments were conducted in tap water with 212-1000 μm polyethylene beads in six size ranges and a variety of similarly sized biological materials. Microplastics were reliably detected, sized, and differentiated from biological materials via their electrical properties at an average flow rate of 103 ± 8 mL/min. The recovery rate was ≥90% for microplastics in the 300-1000 μm size range, and the false positive rate for the misidentification of the biological material as plastic was 1%. Impedance spectroscopy allowed for the identification of microplastics directly in water without visual sorting or filtration, demonstrating its use for flow-through sensing.

A Bayesian Approach for Coincidence Resolution in Microfluidic Impedance Cytometry

Cell counting and characterization is fundamental for medicine, science and technology. Coulter-type microfluidic devices are effective and automated systems for cell/particle analysis, based on the electrical sensing zone principle. However, their throughput and accuracy are limited by coincidences (i.e., two or more particles passing through the sensing zone nearly simultaneously), which reduce the observed number of particles and may lead to errors in the measured particle properties. In this work, a novel approach for coincidence resolution in microfluidic impedance cytometry is proposed. The approach relies on: (i) a microchannel comprising two electrical sensing zones and (ii) a model of the signals generated by coinciding particles. Maximum a posteriori probability (MAP) estimation is used to identify the model parameters and therefore characterize individual particle properties. Quantitative performance assessment on synthetic data streams shows a counting sensitivity of 97% and a positive predictive value of 99% at concentrations of 2×106 particles/ml. An application to red blood cell analysis shows accurate particle characterization up to a throughput of about 2500particles/s. An original formula providing the expected number of coinciding particles is derived, and good agreement is found between experimental results and theoretical predictions. The proposed cytometer enables the decomposition of signals generated by coinciding particles into individual particle contributions, by using a Bayesian approach. This system can be profitably used in applications where accurate counting and characterization of cell/particle suspensions over a broad range of concentrations is required.

Impact of in-cloud aqueous processes on the chemical compositions and morphology of individual atmospheric aerosols

Abstract. The composition, morphology, and mixing structure of individual cloud residues (RES) and interstitial particles (INT) at a mountaintop site were investigated. Eight types of particles were identified, including sulfate-rich (S-rich), S-organic matter (OM), aged soot, aged mineral dust, aged fly ash, aged metal, refractory, and aged refractory mixture. A shift of dominant particle types from S-rich (29 %) and aged soot (27 %) in the INT to aged refractory mixture (23 %) and S-OM (22 %) in the RES is observed. In particular, particles with organic shells are enriched in the RES (27 %) relative to the INT (12 %). Our results highlight that the formation of more oxidized organic matter in the cloud contributes to the existence of organic shells after cloud processing. The fractal dimension (Df), a morphologic parameter to represent the branching degree of particles, for soot particles in the RES (1.82 ± 0.12) is lower than that in the INT (2.11 ± 0.09), which indicates that in-cloud processes may result in less compact soot. This research emphasizes the role of in-cloud processes in the chemistry and microphysical properties of individual particles. Given that organic coatings may determine the particle hygroscopicity, activation ability, and heterogeneous chemical reactivity, the increase of OM-shelled particles upon in-cloud processes should have considerable implications.

Hydrochemical interactions in dilute phoretic suspensions: From individual particle properties to collective organization

Janus phoretic colloids (JPs) self-propel as a result of self-generated chemical gradients and exhibit spontaneous nontrivial dynamics within phoretic suspensions, on length scales much larger than the microscopic swimmer size. Such collective dynamics arise from the competition of (i) the self-propulsion velocity of the particles, (ii) the attractive/repulsive chemically-mediated interactions between particles and (iii) the flow disturbance they introduce in the surrounding medium. These three ingredients are directly determined by the shape and physico-chemical properties of the colloids' surface. Owing to such link, we adapt a recent and popular kinetic model for dilute suspensions of chemically-active JPs where the particles' far-field hydrodynamic and chemical signatures are intrinsically linked and explicitly determined by the design properties. Using linear stability analysis, we show that self-propulsion can induce a wave-selective mechanism for certain particles' configurations consistent with experimental observations. Numerical simulations of the complete kinetic model are further performed to analyze the relative importance of chemical and hydrodynamic interactions in the nonlinear dynamics. Our results show that regular patterns in the particle density are promoted by chemical signaling but prevented by the strong fluid flows generated collectively by the polarized particles, regardless of their chemotactic or antichemotactic nature (i.e. for both puller and pusher swimmers).

On the measurements of individual particle properties via compression and crushing

Abstract An experimental study is presented to measure the elastic, yielding, and crushing properties of individual particles under compression using substrates made of aluminum alloy, stainless steel, and sapphire. Carefully selected, highly spherical individual Ottawa sand particles of 0.75–1.1 mm in nominal diameter were compressed between two smooth substrates, and the load–deformation curves were analyzed by Hertz elastic contact theory to derive their reduced modulus and Young's modulus as well as yielding and crushing strengths, which vary significantly with the type of substrate materials. Further analysis of the yielding and plastic deformation at the particle-substrate contact shows that the yield strength or hardness of the substrate materials dominates the local contact behavior and hence affects the measured apparent yielding and crushing strengths. The two softer substrates (aluminum alloy and stainless steel) actually lead to underestimated apparent shear yield strengths of quartz particles by 60.4% and 54.2%, respectively, which are actually the yielding of substrates, while the true particle yielding occurs in the sapphire-particle contact. Moreover, the two softer substrates cause much overestimated crushing strengths of the quartz particles by 50.4% and 36.4%, respectively. Selection of inappropriate substrate materials and inappropriate interpretation of the particle-substrate contact can lead to significant errors in the measured yielding and crushing strengths. It is recommended that single particle compression testing uses substrates with yield strength greater than that of the tested particles and result interpretation also considers the elastic and yielding behaviors of the substrates.

Automated Segmentation and Morphological Analyses of Stockpile Aggregate Images using Deep Convolutional Neural Networks

Particle size and morphological/shape properties ensure the reliable and sustainable use of all aggregate skeleton materials placed as constructed layers in transportation applications. The composition and packing of these aggregate assemblies rely heavily on particle size and morphological properties, which affect layer strength, modulus, and deformation response under vehicular loading and therefore facilitate the quality assurance/quality control (QA/QC) process. Aggregate imaging systems developed to date for size and shape characterization, however, have primarily focused on measurement of separated or slightly contacting aggregate particles. Development of efficient computer vision algorithms is urgently needed for image-based evaluations of densely stacked (or stockpile) aggregates, which requires image segmentation of a stockpile for the size and morphological properties of individual particles. This paper presents an innovative approach for automated segmentation and morphological analyses of stockpile aggregate images based on deep learning techniques. A task-specific stockpile aggregate image dataset is established from images collected from various quarries in Illinois. Individual particles from the stockpile images are manually labeled on each image associated with particle locations and regions. A state-of-the-art object detection and segmentation framework called Mask R-CNN is then used to train the image segmentation kernel, which enables user-independent segmentation of stockpile aggregate images. The segmentation results show good agreement with ground-truth labeling and improve the efficiency of size and morphological analyses conducted on densely stacked and overlapping particle images. Based on the presented approach, stockpile aggregate image analysis promises to become an efficient and innovative application for field-scale and in-place evaluations of aggregate materials.

Modeling the mechanical behavior of coarse-grained soil using additive manufactured particle analogs

Systematic investigation of the effects of individual particle properties, such as shape, size, surface roughness, and constituent materials stiffness, on the behavior of coarse-grained soils requires careful control over the other particle properties. Achieving this control is a pervasive challenge in investigations with naturally occurring soils. The rapid advance of modern additive manufacturing (AM) technology provides the ability to create analog particles with independent control over particle size and shape. This work evaluates the feasibility of the stereolithography (SLA) and polyjet technologies to generate analog particles that can model the mechanical behavior of coarse-grained soils. AM is used to generate equal-sized spheres and analog sand particles from 3D X-ray CT scans of natural rounded and angular sand particles. The uniaxial inter-particle compression, oedometer compression, and shear wave transmission behaviors of the AM particles are investigated and compared to those of glass and steel spheres and natural rounded and angular sand particles. The results indicate that AM can successfully reproduce the shape of natural coarse sand particles. The deformation of micro-asperities was found to influence the contact response of the polyjet AM particles, thus affecting their inter-particle uniaxial compression and oedometer compression response. The contact response of the SLA AM particles was closer to that of glass spheres. Both AM particle types exhibit a dependency of shear wave velocity and shear modulus on mean effective stress that is consistent with that of natural sands.

Measuring water repellency of individual particles: The new “micro-Wilhelmy Plate Method” and its applicability to soil

Water repellency (hydrophobicity) of granular materials such as soil is usually assessed on bulk samples or arrays of grains, with their wettability being influenced by the often-variable properties of individual particles. Numerous methods exist to assess the wetting behaviour of granular bulk materials, whereas methods for determining the wettability of individual grains are scarce. Here we introduce a new technique, based on the Wilhelmy plate method and termed “micro-Wilhelmy plate method” (mWPM) that allows quantification of the water repellency of an individual particle.We developed two complementary variants of the methods, which involve the rupture of a water lamella after a particle has been brought into contact with water and then withdrawn from it. They were applied to individual wettable or water repellent spherical glass of diameter 120 and 270 µm and polymer particles (270 µm), as well as those of both wettable and natural water repellent particles (of similar size i.e. 120 to 270 µm) from sandy soils of the UK and the Netherlands. Spherical glass and polymer particles were examined in their native condition and following treatment with a hydrophobic (silicone-based water proofing) agent. In one method the break point of lamella was determined gravimetrically (g-mWPM, using an electronic 5-digit balance) and in the other it was determined optically (o-mWPM) from a video sequence obtained from a contact angle goniometer as the distance between the particle and the water surface at the point of lamella rupture. The latter required the use of image analysis and computation to estimate the potential energy of the water lamella.Both methods provided meaningful assessments of particle wettability. Man-made particles showed limited variability, whereas those drawn from naturally wettable or water repellent soils exhibited substantial variability, indicating that wettable soils contain water repellent particles and vice versa. Both methods introduced here offer a relatively quick examination of the wettability of individual particles. The o-mWPM is a particularly simple method only requiring a video camera, stepper-motor driven sample holder and a low magnification optical system. Additionally, it offers the possibility to investigate particle shape.

Interpreting rheology and electrical conductivity: It all boils down to which particle size

Hypothesis: The electrical charges that develop on the surface of the ceramic particles upon contact with water, due to the interaction with ions in solution, result in a liquid-solid interface, which utterly modifies the properties of individual particles and the way they interact with each other to form a structure. This work explores a new approach to the relationships between structure and stability of suspensions. Experiments: For this purpose, suspensions with a constant 0.35 volume fraction of α-alumina particles, neither spherical nor smooth, and controlled ionic strength (0–90 mM KCl) were prepared and characterized in terms of flow behaviour, electrical conductivity and particle’s electrokinetic mobility. Findings: Electrical conductivity (132 µS/cm < conductivity < 5730 µS/cm) and rheology measurements (10−2 Pa s < viscosity < 104 Pa s) were found to complement each other to produce a more accurate picture of the suspension’s structure. Deviations of experimental data from well-accepted behavioural models were elucidated when the surface area equivalent particle size was used. With the electrical double layer thickness obtained from electrical conductivity measurements, this enabled the interpretation of the relationship between the suspension’s viscosity and the particles electrical conductivity, which provides a criterion for the stability of concentrated colloidal suspensions.

Shape Dependence of Falling Snow Crystals’ Microphysical Properties Using an Updated Shape Classification

We present ground-based in situ snow measurements in Kiruna, Sweden, using the ground-based in situ instrument Dual Ice Crystal Imager (D-ICI). D-ICI records dual high-resolution images from above and from the side of falling natural snow crystals and other hydrometeors with particle sizes ranging from 50 μ m to 4 mm. The images are from multiple snowfall seasons during the winters of 2014/2015 to 2018/2019, which span from the beginning of November to the middle of May. From our images, the microphysical properties of individual particles, such as particle size, cross-sectional area, area ratio, aspect ratio, and shape, can be determined. We present an updated classification scheme, which comprises a total of 135 unique shapes, including 34 new snow crystal shapes. This is useful for other studies that are using previous shape classification schemes, in particular the widely used Magono–Lee classification. To facilitate the study of the shape dependence of the microphysical properties, we further sort these individual particle shapes into 15 different shape groups. Relationships between the microphysical properties are determined for each of these shape groups.