Mixture Of Particles Research Articles

Synergistically active Fe3O4 magnetic and EDTA modified cellulose cotton fabric using chemical method and their effective pollutants removal ability from wastewater

A unique combination of cotton fabric (CF) with a mixture of EDTA and APTES Fe3O4 magnetic particles was developed and utilized for the first time as an adsorbent for removing pollutants from wastewater. Initially, Fe3O4 was synthesized using the co-precipitation method. Further, the surface of Fe3O4 was modified by introducing amino functional groups through a reaction with APTES, resulting in Fe3O4-NH2. Following this, the surface of carbon fiber (CF) was altered using ethylenediaminetetraacetic acid (EDTA) to create CF@EDTA. Through the use of EDC-HCl and NHS, Fe3O4-NH2 was attached to the surface of CF@EDTA, resulting in the final product CF@EDTA/Fe3O4. Subsequently, the prepared CF@EDTA/Fe3O4 was utilized to adsorb metal pollutants from wastewater, with a thorough analysis conducted using various characterization techniques including FTIR, SEM, EDX, XRD, VSM, and XPS to study the materials. The study specifically aimed to assess the adsorption performance of our cotton-based material towards As(III) and Cr3+ metal ions. The pH study was also performed. Results indicated that the material exhibited an adsorption capacity of approximately 714 mg/g for As(III) ions and 708 mg/g for Cr3+ ions. The Langmuir and Freundlich models, as well as pseudo-first and second-order models were also analyzed. The Langmuir and pseudo-second-order models were found to best fit the data. In terms of regeneration and reusability, the materials showed straightforward regeneration and recyclability for up to 15 cycles. The remarkable adsorption capacity, combined with the unique blend of cotton and Fe3O4 magnet, along with its recyclability, positions our material CF@EDTA/Fe3O4 as a promising contender for wastewater treatment and other significant areas in water research.

Influence of fermentation conditions by Rhizopus oryzae on the release of phenolic compounds, composition, and properties of brewer's spent grain

This study aimed to (i) assess the influence of moisture and particle size on the release of phenolic compounds from brewer's spent grain by Rhizopus oryzae fermentation, (ii) determine the release kinetics of these compounds, and (iii) characterize brewer's spent grain before (BSG) and after (BSGF) fermentation. BSG and BSGF were evaluated for chemical composition, phenolic profile, and antioxidant and technological properties. The release of methanol-soluble phenolic compounds (MSPC) was influenced by both moisture and particle size, with the highest value (300.25 mg 100 g−1) obtained at 71% moisture and a 50:50 mixture of particles measuring 0.50 and 0.30 mm. This maximum MSPC content was obtained after 48 h of fermentation, being 761% higher than that contained in BSG. Catechin was the major component of the MSPC fraction (37.08 mg 100 g−1), whereas ferulic acid (36.38 mg 100 g−1) was the predominant component of the bound phenolic fraction. BSGF showed higher ash (8%) and protein (17%) content, but lower soluble dietary fiber (10%) and lipid content (67%) than BSG. Fermentation altered the protein fractions of the residue, increasing the proportion of albumin and globulin and decreasing that of prolamin and glutelin. These changes resulted in improved technological properties (oil absorption, water solubility, and swelling volume) and antioxidant activity. It is concluded that the proposed fermentation method can contribute to expanding the utilization of BSG, thereby diversifying its applications, and adding value to the production chain.

Microstructure and properties of ZrB2-reinforced aluminum matrix composites consolidated by ECAP process

In this research work, the effects of mechanical alloying and subsequent compaction by ECAP on the microstructural, physical, and mechanical properties of Al-ZrB2 metal matrix composites (MMCs) were evaluated. To prepare composite powders, a mixture of Al and ZrB2 particles was mechanically alloyed at various times of 1, 6, 12, 18 and 24 h. SEM micrographs indicate that the size of the obtained particles decreases by increasing the time of mechanical alloying up to 18 h. However, after this time, increasing the time of mechanical alloying has led to an increase in the size of the particles. By means of mechanical alloying for 18 h, the average size of fine particles reached 823 nm, while coarse particles were 8 μm. The calculation via the use of XRD examination implies that the mean crystallite size of powder decreased from about 68 nm to 31 nm and 26.8 nm, for Al and Al-5%ZrB2 samples, respectively, while lattice strain increased from 0.25% to 0.64% and from 0.3% to 0.73% after 1 h to 24 h milling of same samples, respectively. However, the rate of crystallite size reduction after 12 h of mechanical alloying is gradually reduced, and that is reached its lowest level after 18 h. After that, increasing the time of mechanical alloying has led to a saturation in the lattice strain. In continue, the resulting composite powder was heated, consolidated and turned into bulk material by warm equal channel angular pressing (ECAP) at the temperature of 250 °C. The resultant optimum composite has been characterized by EDS elemental mapping. Microhardness measurements and shear punch tests were performed to evaluate the mechanical properties of the unreinforced and composite samples after the ECAP process. The Al-ZrB2 MMC bulk samples subjected to ECAP, with a ZrB2 amount of 5 wt%, had a relative density, hardness, and ultimate shear strength of 99.3%, 170 HV, and 151 MPa, respectively, using powders which have been mechanically alloyed up to 24 h.

Effect of concentration of CuO on radiation shielding characteristics of Epoxy-resin materials

In this work, a new composite based on epoxy resin impeded with both micro and nano size of copper oxide (CuO) for photon shielding application were investigated. Four Epoxy-CuO composites were prepared including pure Epoxy resin material, EP-10%CuOm (90% Epoxy +10% CuO-MPs), EP-30%CuOm (70% Epoxy +30% CuO-MPs) and EP-50%CuOm (50% Epoxy +10% CuO-MPs). The same composites were prepared with CuO-nanoparticles (EP-10%CuOn, EP-30%CuOn and EP-50%CuOn) as well as three other composites with micro and nano together (EP-10%CuOm + n, EP-30%CuOm + n and EP-50%CuOm + n). The linear attenuation coefficient (LAC) was found via the narrow beam technique employing HPGe (high pure Ge) detector at different abroad energies from 0.060 to 1.333 MeV. Comparison of the experimental values with those of micro composites obtained from XCOM software revealed a good agreement. Additional attenuator parameters (half and tenth value layers, mean free path, and transmission factor) have been calculated. The results approved that the composites with varying weight percent of mixture of nano and micro particles of CuO have higher attenuation preference than composites with nano and micro particles, separately at all discussed energies. It was observed that the attenuation preference of EP-50%CuO > EP-30%CuO > EP-10%CuO > Pure Epoxy, in addition to, the LAC of EP-50%CuOm + n > EP-50%CuOn > EP-50%CuOm.

Anisotropic remixing of a phase separated binary colloidal system with particles of different sizes in an external modulation.

We explore the phase behavior of a binary colloidal system under external spatially periodic modulation. We perform Monte Carlo simulations on a binary mixture of big and small repulsive Lennard-Jones particles with a diameter ratio of 2:1. We characterize structure by isotropic and anisotropic pair correlation functions, cluster size distribution, bond angle distribution, order parameter, and specific heat. We observe the demixing of the species in the absence of external modulation. However, the mixing of the species gets enhanced with increasing potential strength along with the alignment of the particles transverse to the modulation. The de-mixing order parameter shows discontinuity with increasing modulation strength, characterizing a first order phase transition. The peak in specific heat increases linearly with the size of the system. We also look into the dynamical behavior of the system via computing Mean Square Displacement (MSD) along both parallel and perpendicular directions to the modulation. We observe a decrease in the diffusion coefficient for both types of particles as we increase the strength of the modulation.

Molecular-Induced Steric Shape Separation of Nano Geometries

The separation of specific-shaped nanoparticles from particle mixtures is important for the construction of particle domains with shape-specific characteristics. On the other hand, shape-based particle separation techniques have not received as much attention as size-based techniques. The shape separation effect of molecule-coated nanoparticles is primarily dependent on short-range steric interaction. The surfactant’s geometrical arrangement determines the position of the nanoparticle’s various crystallographic facets; this also determines how the various shapes are organized throughout the nanoparticle self-assembly process. In addition to smooth surfaces with a fixed droplet contact line and a stable environment, the self-assembled shape separation effect has been observed on surfaces with wettability stripe patterns and fluctuating environments where the droplet contact line behaves stick–slip-like during the evaporation process. The shape separation of spheres and rods is strongly influenced by steric interactions. Since shape-dependent transport properties exist in such nano-crystalline domains, it is important to understand the shape separation effect.

A Reverse Nonequilibrium Molecular Dynamics Algorithm for Coupled Mass and Heat Transport in Mixtures.

We present a new method for introducing stable nonequilibrium concentration gradients in molecular dynamics simulations of mixtures. This method extends earlier reverse nonequilibrium molecular dynamics (RNEMD) methods, which use kinetic energy scaling moves to create temperature or velocity gradients. In the new scaled particle flux (SPF-RNEMD) algorithm, energies and forces are computed simultaneously for a molecule existing in two nonadjacent regions of a simulation box, and the system evolves under a linear combination of these interactions. A continuously increasing particle scaling variable is responsible for the migration of the molecule between the regions as the simulation progresses, allowing for simulations under an applied particle flux. To test the method, we investigate diffusivity in mixtures of identical but distinguishable particles and in a simple mixture of multiple Lennard-Jones particles. The resulting concentration gradients provide Fick diffusion constants for mixtures. We also discuss using the new method to obtain coupled transport properties using simultaneous particle and thermal fluxes to compute the temperature dependence of the diffusion coefficient and activation energies for diffusion from a single simulation. Lastly, we demonstrate the use of this new method in interfacial systems by computing the diffusive permeability of a molecular fluid moving through a nanoporous graphene membrane.

Phase separation dynamics in a symmetric binary mixture of ultrasoft particles.

Phase separation plays a key role in determining the self-assembly of biological and soft-matter systems. In biological systems, liquid-liquid phase separation inside a cell leads to the formation of various macromolecular aggregates. The interaction among these aggregates is soft, i.e., they can significantly overlap at a small energy cost. From a computer simulation point of view, these complex macromolecular aggregates are generally modeled by soft particles. The effective interaction between two particles is defined via the generalized exponential model of index n, with n = 4. Here, using molecular dynamics simulations, we study the phase separation dynamics of a size-symmetric binary mixture of ultrasoft particles. We find that when the mixture is quenched to a temperature below the critical temperature, the two components spontaneously start to separate. Domains of the two components form, and the equal-time order parameter reveals that the domain sizes grow with time in a power-law manner with an exponent of 1/3, which is consistent with the Lifshitz-Slyozov law for conserved systems. Furthermore, the static structure factor shows a power-law decay with an exponent of 4, consistent with the Porod law.

Imbalance of APOB Lipoproteins and Large HDL in Type 1 Diabetes Drives Atherosclerosis.

Individuals with type 1 diabetes (T1D) generally have normal or even higher HDL (high-density lipoprotein)-cholesterol levels than people without diabetes yet are at increased risk for atherosclerotic cardiovascular disease (CVD). Human HDL is a complex mixture of particles that can vary in cholesterol content by >2-fold. To investigate if specific HDL subspecies contribute to the increased atherosclerosis associated with T1D, we created mouse models of T1D that exhibit human-like HDL subspecies. We also measured HDL subspecies and their association with incident CVD in a cohort of people with T1D. We generated LDL receptor-deficient (Ldlr-/-) mouse models of T1D expressing human APOA1 (apolipoprotein A1). Ldlr-/-APOA1Tg mice exhibited the main human HDL subspecies. We also generated Ldlr-/-APOA1Tg T1D mice expressing CETP (cholesteryl ester transfer protein), which had lower concentrations of large HDL subspecies versus mice not expressing CETP. HDL particle concentrations and sizes and proteins involved in lipoprotein metabolism were measured by calibrated differential ion mobility analysis and targeted mass spectrometry in the mouse models of T1D and in a cohort of individuals with T1D. Endothelial transcytosis was analyzed by total internal reflection fluorescence microscopy. Diabetic Ldlr-/-APOA1Tg mice were severely hyperglycemic and hyperlipidemic and had markedly elevated plasma APOB levels versus nondiabetic littermates but were protected from the proatherogenic effects of diabetes. Diabetic Ldlr-/-APOA1Tg mice expressing CETP lost the atheroprotective effect and had increased lesion necrotic core areas and APOB accumulation, despite having lower plasma APOB levels. The detrimental effects of low concentrations of larger HDL particles in diabetic mice expressing CETP were not explained by reduced cholesterol efflux. Instead, large HDL was more effective than small HDL in preventing endothelial transcytosis of LDL mediated by scavenger receptor class B type 1. Finally, in humans with T1D, increased concentrations of larger HDL particles relative to APOB100 negatively predicted incident CVD independently of HDL-cholesterol levels. Our results suggest that the balance between APOB lipoproteins and the larger HDL subspecies contributes to atherosclerosis progression and incident CVD in the setting of T1D and that larger HDLs exert atheroprotective effects on endothelial cells rather than by promoting macrophage cholesterol efflux.

Impact of heteroaggregation between microplastics and algae on particle vertical transport

Understanding the impacts of microplastics (MPs) on aqueous environments requires understanding their transport dynamics and how their presence affects other natural processes and cycles. In this context, one aspect to consider is how MPs interact with freshwater snow (FWS), a mixture of algae and natural particles. FWS is one of the primary drivers of the flux of organic matter from the water surface to the bottom sediment, where zooplankton, diurnal migration, fish faecal pellets settling and turbulent mixing can also play prominent roles. Understanding how MPs and FWS heteroaggregation affects their respective settling velocities is important to assess not only MPs fate and transport but also their ecological impacts by altering FWS deposition and thereby nutrient cycling. In this present study, we obtained a mechanistic understanding of the processes controlling MPs settling dynamics and heteroaggregation with FWS and the subsequent impacts on the settling rates of both MPs and ballasted FWS. Here we used a plexiglass column equipped with a stereoscopic camera system to track the settling velocities of (1) MPs of various compositions, densities and morphologies, (2) FWS flocs and (3) MP–FWS agglomerates. For each experimental set, thousands of particles were tracked over a series of image sequences. We found that agglomerates with high-density MPs settled at least twofold faster than FWS alone, implying a much smaller residence time in the water column, except for cases with MP fibres or low-density plastics. These findings will help to refine MP fate models and, while contingent on MPs number, may impact biogeochemical cycles by changing the flux of nutrients contained in FWS to the sediment.

Friction Stir Welding: A Comprehensive Review of Non-Metallic Particle Reinforcement in Joints

Friction Stir Welding (FSW), a solid-state joining technique, has demonstrated superior efficiency in welding metal-matrix-reinforced composite joints. FSW has garnered significant attention in recent years as a viable technique for joining similar and dissimilar materials, particularly those reinforced with non-metallic particles. By utilizing diverse mixture of reinforcement particles and base matrices, FSW outperforms traditional fusion joining methods in terms of effectiveness and reliability. Despite significant progress, challenges persist in achieving a homogeneous distribution of Non-metallic particles in the weld zone, which directly impacts macrostructural and microstructural characteristics. Moreover, the mechanical properties of these welds are intricately linked to process parameters, influencing grain enhancement and reinforcement particle distribution. This review critically evaluates these aspects, providing insights into the current understanding and highlighting areas for future research.

Semi-supervised urban haze pollution prediction based on multi-source heterogeneous data

Particulate matter (PM) is defined by the Texas Commission on Environmental Quality (TCEQ) as “a mixture of solid particles and liquid droplets found in the air”. These particles vary widely in size. Those particles that are less than 2.5 μm in aerodynamic diameter are known as Particulate Matter 2.5 or PM2.5. Urban haze pollution represented by PM2.5 is becoming serious, so air pollution monitoring is very important. However, due to high cost, the number of air monitoring stations is limited. Our work focuses on integrating multi-source heterogeneous data of Nanchang, China, which includes Taxi track, human mobility, Road networks, Points of Interest (POIs), Meteorology (e.g., temperature, dew point, humidity, wind speed, wind direction, atmospheric pressure, weather activity, weather conditions) and PM2.5 forecast data of air monitoring stations. This research presents an innovative approach to air quality prediction by integrating the above data sets from various sources and utilizing diverse architectures in Nanchang City, China. So for that, semi-supervised learning techniques will be used, namely collaborative training algorithm Co-Training (Co-T), who further adjusting algorithm Tri-Training (Tri-T). The objective is to accurately estimate haze pollution by integrating and using these multi-source heterogeneous data. We achieved this for the first time by employing a semi-supervised co-training strategy to accurately estimate pollution levels after applying the U-air system to environmental data. In particular, the algorithm of U-Air system is reproduced on these highly diverse heterogeneous data of Nanchang City, and the semi-supervised learning Co-T and Tri-T are used to conduct more detailed urban haze pollution prediction. Compared with Co-T, which train time classifier (TC) and subspace classifier (SC) respectively from the separated spatio-temporal perspective, the Tri-T is more accurate with a and faster because of its testing accuracy up to 85.62 %. The forecast results also present the potential of the city multi-source heterogeneous data and the effectiveness of the semi-supervised learning. We hope that this synthesis will motivate atmospheric environmental officials, scientists, and environmentalists in China to explore machine learning technology for controlling the discharge of pollutants and environmental management.

Diagnostyka stanu technologicznego gazociągów na podstawie składu transportowanych mieszanin gazowych

The efficiency of natural gas transportation hinges largely on the quality of technological processes involved. Imperfect separation process can lead to the liquid particles remaining in the gas and entering the transport systems, causing various technological issues with gas pipelines (clogging, hydrate formation, corrosion wear, etc.). The presence of mechanical particles in gas mixtures accelerates the degradation of metallic components of the transport system due to erosion. Additionally, the multiphase nature of gases contributes to complications during transportation, altering the quality indicators when different gas qualities are mixed. Consequently, the composition of gas mixtures, their mechanical particles, moisture, and other indicators, deviate non-linearly from their initial values. The technological condition of the main gas pipelines significantly impacts their discharge capacity and hydraulic characteristics. Failure to clean natural gas to current standards and requirements at production stations can result in condensation of water and hydrocarbon vapours in pipelines, leading to the accumulation of the liquid phase in the cavities of the pipeline and the formation of blockages due to hydrate compounds formation, the reduction of the cross-section of the gas pipeline or its complete blockage. Sediment accumulation on the inner surfaces of gas pipelines installed in complex geographical conditions adversely affects transportation system, increasing maintenance, energy, and transportation costs. Utilizing gas composition as an auxiliary tool (indicator) for diagnosing various technological processes and predicting transport parameters has been investigated in numerous research works in the oil and gas production industry.

Experimental Study on Surface Segregation Law of Three-Dimensional Accumulation Body of Sand and Stone Particles by Binary Mechanism

Sand and stone materials are one of the important raw materials for infrastructure construction. In recent years, natural sand resources have decreased rapidly. In order to protect rivers and DAMS and ecological balance, local governments have increased the control power of natural sand mining, and replacing natural sand with mechanically broken parent rock formation mechanism sand has become an inevitable trend of the industry development. During the crushing process of parent rock, sand particles of different particle size range are produced, and particle segregation occurs in the process of stacking in the yard, which brings great trouble to the calculation of particle grading and material sample detection, and hinders the large-scale application of machine-made sand. In this paper, three-dimensional stacking tests of irregular particles were carried out to identify the particle distribution on the surface of the stack by digital image technology, analyze the relationship between particle size composition of particle mixture and the particle distribution of the accumulation body, and study the distribution law and segregation characteristics of the accumulation body. The experimental results show that the mixture with different coarse particle content will produce the corresponding distribution on the surface of the accumulation body after the accumulation. On the surface of the accretion body, the content of coarse particles is vertically distributed along the height of the accretion body. The content of coarse particles in the lower part of the accretion body is greater than that in the upper part of the accretion body. The overall segregation coefficient on the surface of the pile decreases with the increase of coarse particle content, and the variation is the largest in the lower part of the pile surface with the initial coarse particle content. Based on the test results in this paper, it provides a basis for formulating the sampling and inspection method of machine-made sand, ensuring the quality of machine-made sand and improving the utilization rate of machine-made sand.

Influence of Graphene/h-BN and SiC/h-BN reinforcing particles on microstructural, mechanical and tribological characteristics of Al7075-based hybrid nanocomposites

Aluminium (Al) based Metal Matrix Composites (MMCs) replaced conventional alloys in numerous sectors like the automotive to aerospace industries. In this investigation, Al7075/Silicon carbide (1 wt%)/Hexagonal-boron nitride (0.5 wt%) and Al7075/Graphene (1 wt%)/Hexagonal-boron nitride (0.5 wt%) hybrid metal matrix nanocomposites (HMMNCs) prepared using an ultrasonic-assisted melt-stirring squeeze casting process. To attain the homogenous mixing of hard ceramic/nanoparticles, reduce the aggregation effect and improve wettability of the reinforcing nanoparticles in the molten slurry. Reinforcement particles mixture (Silicon carbide (1 wt%)/Hexagonal-boron nitride (0.5 wt%) and Graphene (1 wt%)/Hexagonal-boron nitride (0.5 wt%)) have been ball-milled for the duration of 1 to 6 h (hrs). To analyze the morphology of the 1–6 h ball-milled hybrid reinforcing particles mixture was analyzed via scanning electron microscope (SEM). Moreover, microstructural investigation of the Al-based HMMNCs was performed using optical microscopy (OM), field-emission scanning electron microscopy (FE-SEM) and scanning electron microscope (SEM). Also, the dispersal of hybrid reinforcing particles mixture in Al7075-based HMMNCs was examined via SEM-equipped with x-ray mapping analysis. The fabricated Al7075-based HMMNCs are tested for their tensile strength, microhardness and tribological behavior by employing universal testing machines, Vickers microhardness tester and ball-on-disc instruments. Tribological characteristics of the Al7075-based HMMNCs were observed via ball-on-disc tribometer apparatus with load (10, 15 and 20 N), time (15 min) and speed (300, 600 and 900 rpm). While investigating, it is perceived that that the wear, tensile strength, hardness and microstructure characteristics of the Al7075/Silicon carbide/Hexagonal-boron nitride and Al7075/Graphene/Hexagonal-boron nitride HMMNCs were superior over the Al7075 alloy. It is found that Vickers and Rockwell hardness of the Al7075/SiC/h-BN HMMNCs were superior by 36.87% and 16.29%, respectively, over the Al7075 specimen. Whereas, UTS of the Al7075/Graphene/h-BN HMMNCs were superior by 38.19% over the Al7075 alloy.

Li/La and Cu modified ZnO semiconductor: Highly boosted of dielectric and sunlight-treatment of thiamethoxam and brilliant green contaminants

Solving the global environmental problem which related to the dissolved organic pollutants into water systems is an essential issue for human-health and aquatic life. This study represents the simple synthesis of new Li/La and Cu modified ZnO compositions as active photocatalysts and proper dielectric materials for electrical energy storage devices. The synthesized powders have one phase nature with hexagonal lattice indexed to ZnO structure. The field emission scanning electron microscopy (FESEM) clearly showed that (Li, La) modified ZnO powder consist of a mixture of particles having open hexagonal tube and spherical shapes. The FESEM picture of (Li, Cu, La) modified ZnO powder revealed lumps like cabbage shape mainly composed of pieces like sheets or papers. The purity and elemental composition were also verified by energy dispersive spectroscopy (EDS) analysis. The addition of (Li, La) and (Li, Cu, La) ions to ZnO semiconductor extremely improved the dielectric constant which is a benefit for application in solid state energy storage systems. (Li, Cu, La) modified ZnO sample is a suitable catalyst for removal of organic waste owing to its high response to visible light spectrum with measured band gap energy of 2.76 eV. The synergistic effect of Li+, Cu2+ and La3+ dopants induced high visible light photodegradation activities against thiamethoxam pesticide and brilliant green dye with measured efficiencies of 92 and 96 % after reaction time of 50 min, respectively. The high stability and mineralization properties of (Li, Cu, La) modified ZnO catalyst leads to the conclusion that this composition has a potential use in wastewater treatment.

Segregation and mixing of binary mixtures of spherical particles in a bubbling fluidized bed

Abstract This work reports a CFD-DEM study on the segregation and mixing of binary mixtures of particles in a bubbling fluidized bed. A simplified mixing index was applied to determine the instantaneous mixing state in the bed, with which the effects of superficial gas velocity and initial packing state on the fluidization behavior were further discussed. For the well-mixed initial conditions, the mixing index decreases with fluidization time until a dynamic equilibrium between segregation and mixing is achieved. In contrast, the mixing index first increases and then decreases with fluidization time for completely-segregated initial conditions. However, the final equilibrium between segregation and mixing will not be affected by initial packing states for a given superficial gas velocity. Moreover, the bubbling behavior shows a marked impact on segregation and mixing, i.e., mixing is enhanced during the formation and grow-up of bubbles, while segregation is strengthened during the eruption of bubbles. This makes it possible to improve the fluidization of binary mixtures of particles based on the bubbling behaviors in the fluidized bed.

Colloid phase separation dynamics driven by chiral turbulent flows

Hydrodynamic interactions significantly influence phase-ordering kinetics in complex fluids. While passive fluid phase separation is well studied, the impact of active components remains relatively unexplored. We examine pure- and quasi-two-dimensional mixtures of attractive colloids and self-rotating particles in a solvent. Varying rotor rotational speed and area fraction yield diverse dynamic patterns such as percolated networks and round droplets composed of passive colloids alone. At intermediate rotation speeds, inertial chiral flows, accompanied by the inverse energy cascade, lead to self-similar power-law coarsening with a growth exponent of 1/2. The flows spontaneously organize within fluid domains, exhibiting turbulent and chiral characteristics. Surprisingly, these turbulent flows can sustain hexatic order hydrodynamically stabilized by the Magnus force under certain conditions. Conversely, at higher speeds, nonlinear hydrodynamic interactions impede phase separation. Our findings illuminate the intriguing dynamic interplay between phase separation and chiral turbulence, effectively bridging the realms of phase ordering and turbulent physics. Published by the American Physical Society 2024

Biomass Burning Aerosol Observations and Transport over Northern and Central Argentina: A Case Study

Biomass Burning Aerosol Observations and Transport over Northern and Central Argentina: A Case Study

Diesel Engine Exhaust Exposure in Relation to Lung Cancer in Long-Haul Truck Drivers: An Eight-Step Concept Analysis.

Long-haul truck drivers (LHTDs) face a number of occupational hazards. One such hazard is exposure to diesel engine exhaust (DEE). However, this concept has yet to be analyzed. To address this gap, a concept analysis was conducted to explore the effects of DEE in relation to lung cancer. Walker and Avant's eight-step concept analysis method was utilized: concept selection, analysis purpose, concept uses, defining attributes, model case, borderline case, antecedents and consequences, and empirical referents. PubMed, Scopus, and CINAHL databases were searched for relevant literature. Diesel engine exhaust was identified as a mixture of gases and particulates that are considered carcinogenic. Defining attributes of DEE for truckers include respiratory effects such as decreased peak flow and increased airway resistance leading to symptoms such as a phlegm-producing cough, eye and throat irritation, exacerbation of asthma symptoms, and allergic responses. The identified level of DEE exposure associated with these attributes is 75 μg EC/m3 for 1 to 2 hours daily or a long-term exposure of 10 μg EC/m3. The conceptual definition of DEE in truckers was illustrated by the attributes, antecedents, consequences, model case, and empirical referents. Lung cancer was identified as a significant consequence of occupational DEE exposure for LHTDs. This analysis highlights the need for future research to develop interventions that will safeguard truckers from the adverse health effects of DEE exposure.