Search Results (37)

We present a theoretical model for the electrophoresis of a weakly charged oil drop migrating through an uncharged polymer gel medium saturated with an aqueous electrolyte solution. The surface charge of the drop arises from the specific adsorption of ions onto its interface. Unlike solid particles, liquid drops exhibit internal fluidity and interfacial dynamics, leading to distinct electrokinetic behavior. In this study, the drop motion is driven by long-range hydrodynamic effects from the surrounding gel, which are treated using the Debye–Bueche–Brinkman continuum framework. A simplified version of the Baygents–Saville theory is adopted, assuming that no ions are present inside the drop and that the surface charge distribution results from linear ion adsorption. An approximate analytical expression is derived for the electrophoretic mobility of the drop under the condition of low zeta potential. Importantly, the derived expression explicitly includes the Marangoni effect, which arises from spatial variations in interfacial tension due to non-uniform ion adsorption. This model provides a physically consistent and mathematically tractable basis for understanding the electrophoretic transport of oil drops in soft porous media such as hydrogels, with potential applications in microfluidics, separation processes, and biomimetic systems. These results also show that the theory could be applied to more complicated or biologically important soft materials. Full article

In recent times, fiber reinforced polymer composite materials have become more popular due to their remarkable features such as high specific strength, high stiffness and durability. Particularly, Carbon Fiber Reinforced Polymer (CFRP) composites are one of the most prominent materials used in the field of transportation and building engineering, replacing conventional materials due to their attractive properties as mentioned. In this work, a CFRP laminate is fabricated with carbon fiber mats and epoxy by a hand layup technique. Alumina (Al₂O₃) micro particles are used as a filler material, mixed with epoxy at different weight fractions of 0% to 4% during the fabrication of CFRP laminates. The important objective of the study is to investigate the influence of alumina micro particles on the mechanical performance of the laminates through characterization for various physical and mechanical properties. It is revealed from the results of study that the mass density of the laminates steadily increased with the quantity of alumina micro particles added and subsequently, the porosity of the laminates is reduced significantly. The SEM micrograph confirmed the constituents of the laminate and uniform distribution of Al₂O₃ micro particles with no significant agglomeration. The hardness of the CFRP laminates increased significantly for about 60% with an increase in weight % of Al₂O₃ from 0% to 4%, whereas the water gain % gradually drops from 0 to 2%, after which a substantial rise is observed for 3 to 4%. The improved interlocking due to the addition of filler material reduced the voids in the interfaces and thereby resist the absorption of water and in turn reduced the plasticity of the resin too. Tensile, flexural and inter-laminar shear strengths of the CFRP laminate were improved appreciably with the addition of alumina particles through extended grain boundary and enhanced interfacial bonding between the fibers, epoxy and alumina particles, except at 1 and 3 wt.% of Al₂O₃, which may be due to the pooling of alumina particles within the matrix. Inclusion of hard alumina particles resulted in a significant drop in impact strength due to appreciable reduction in softness of the core region of the laminates. Full article

Membrane tubes, a class of soft biological confinement for ubiquitous transport intermediates, are essential for cell trafficking and intercellular communication. However, the confinement interaction and directional migration of diffusive nanoparticles (NPs) are widely dismissed as improbable due to the surrounding environment compressive force. Here, combined with the mechanics analysis of nanoparticles (such as extracellular vesicles, EVs) to study their interaction in confinement, we perform dissipative particle dynamics (DPD) simulations to construct a model that is as large as possible to clarify the submissive behavior of NPs. Both molecular simulations and mechanical analysis revealed that the interactions between NPs are controlled by confinement deformation and the centroid distance of the NPs. When the centroid distance exceeds a threshold value, the degree of crowding variation becomes invalid for NPs motion. The above conclusions are further supported by the observed dynamics of multiple NPs under confinement. These findings provide new insights into the physical mechanism, revealing that the confinement squeeze generated by asymmetric deformation serves as the key factor governing the directional movement of the NPs. Therefore, the constraints acting on NPs differ between rigid confinement and soft confinement environments, with NPs maintaining relative stillness in rigid confinement. Full article

The interaction of microplastics (MPs) with organic micropollutants, such as antibiotics, facilitates their transport in aquatic environments, increasing mobility and toxicological risk. The diverse polymer types, sizes, and shapes in wastewater present a challenge in understanding the fate of persistent organic micropollutants. This study examines ceftazidime adsorption on five polymer types—polyethylene terephthalate (PET), polyethylene (PE), hard and soft polystyrene (PS), hard and soft polyurethane (PU), and tyre wear particles (TWPs, including three passenger tyres and one truck tyre) in various forms (fibres, beads, foam, and fragments) and sizes (10–1000 µm). MPs underwent weathering (alkaline hydrolysis, UVC-activated H₂O₂, and Xenon lamp irradiation) to simulate environmental conditions. Their physical and chemical changes were analysed through mass loss, carbonyl index, scanning electron microscopy, and atomic force microscopy. The adsorption values (mg g⁻¹) for pristine and weathered MPs, respectively, were as follows: PET (0.664 and 1.432), PE (0.210 and 0.234), hard PS (0.17 and 0.24), soft PS (0.53 and 0.48), hard PU (0.19), soft PU (0.17), and passenger TWPs—Bridgestone (0.212), Michelin (0.273), Goodyear (0.288), and Kumho truck TWPs (0.495). The highest and lowest adsorption were observed in weathered PET (1.432 mg g⁻¹) and pristine hard PS/soft PU (0.17 mg g⁻¹), respectively. Sorption kinetics and isothermal models showed that aged MPs exhibited higher sorption due to surface cracks, fragmentation, and increased adsorption sites. These findings enhance scientific knowledge of MP–antibiotic interactions in wastewater and can underpin studies to mitigate MP pollution and their adverse effects on the environment and humans. Full article

The transport of deformable particles (TDPs) through porous media has been of considerable interest due to the multiple applications found in industrial and medical processes. The adequate design of these applications has been mainly achieved through experimental efforts, since TDPs through porous media are challenging to model because of the mechanical blockage of the pore throat due to size exclusion, deformation in order to pass through the pore throat under the driven pressure, and breakage under strong extrusion. In this work, based on the diffusivity equation and considering the TDP as a complex fluid whose viscosity and density depend on the local pressure, a simple but accurate theoretical model is proposed to describe the pressure behavior under steady- and unsteady-state flow conditions. Assuming a linear pressure dependence of the viscosity and density of the TDPs, valid for moderate pressure changes, the solution of the mathematical model yields a quantitative correlation between the pressure evolution and the parameters compressibility, viscosity coefficient, elastic modulus, particle size, and friction factor. The predictions of the model agree with experiments and allow the understanding of transport of deformable particles through a porous media. Full article

In aquatic sediments, active ventilation of burrows is an important component of sediment metabolism, transporting solutes across the sediment–water interface. Within a burrow, the temporal and spatial structure of the flow velocity can dictate the flux of solutes across the burrow walls. However, it is difficult to measure the fine-scale flow dynamics within a burrow due to the opacity of marine sediments. Here, we allowed a nereid polychaete Alitta succinea, a cosmopolitan deposit feeder found in brackish to marine soft sediments, to construct burrows in a transparent, elastic sediment analog. This allowed the measurement of the temporal velocity structure of flow in the burrow using particle tracking velocimetry. We find that the flow within the burrow of this piston-pumping polychaete is unsteady and that oscillations in flow velocity are damped with distance along the tube. We also show that the flow velocity in a tube scales with worm size. Conversely, neither the unsteadiness of flow oscillations nor the stroke frequency of the worm pump scale with worm size. Full article

The nonlinear dependence of the mean-squared displacement (MSD) on time is a common characteristic of particle transport in complex environments. Frequently, this anomalous behavior only occurs transiently before the particle reaches a terminal Fickian diffusion. This study shows that a system of hierarchically coupled Ornstein–Uhlenbeck equations is able to describe both transient subdiffusion and transient superdiffusion dynamics, as well as their sequential combinations. To validate the model, five distinct experimental, molecular dynamics simulation, and theoretical studies are successfully described by the model. The comparison includes the transport of particles in random optical fields, supercooled liquids, bedrock, soft colloidal suspensions, and phonons in solids. The model’s broad applicability makes it a convenient tool for interpreting the MSD profiles of particles exhibiting transient anomalous diffusion. Full article

We present a detailed analysis based on both experimental and 3D modelling approaches of the unique silicon nitride precipitation sequence observed in ferritic Fe-Si alloys upon nitriding. At 570 °C, Si₃N₄ silicon nitride was shown to form as an amorphous phase into α-Fe ferrite matrix, which is morphologically unstable over time. Precipitates nucleated with a spheroidal shape, then developed a cuboidal shape for intermediate sizes and octapod-like morphology for a longer time. Using transmission electron microscopy, we show that the transition between spheroid and cuboid morphology depended on particle size and resulted from competition between interfacial energy and elastic strain energy. The resulting morphology was then shown to be a cuboid shape whose faces were always parallel to the {100} planes of the α-Fe; the <100> directions of the matrix corresponded to the elastically soft directions. There was a critical size of around 45 nm for which the transition between the cuboid shape and the octapod-like morphology took place. This was characterised by a transformation of quasi-flat facets into concave ones and the development of lobes in the <111> directions of the bcc crystal. To better assess the kinetic effects of diffusion fields and internal stresses on the morphological instability observed, an original 3D model that explicitly coupled phase transformations and mechanical fields was developed and applied. The latter, validated on the basis of model cases, was shown to be able to describe the time-evolution of both chemical and mechanical fields and their interactions in diffusive mass transport. Using a model system, it was shown that the concentration field around the precipitates and the internal stresses played opposing roles in the cuboid to octapod-like morphological instability. This work gives some clarification regarding the morphological evolution of amorphous Si₃N₄ precipitates, an important point for controlling the mechanical properties of nitrogen steels. Full article

Abundant industrial experiences have shown that directional air drilling technology is effective for gas drainage when drilling broken and soft coal seams. In this paper, the Eulerian–Eulerian model was used to simulate the gas–solid two-phase flow behavior of compressed air transporting coal dust in broken soft coal seams. The relationship between the degree of coal dust deposition, annular air pressure law, transportation of coal dust, aforementioned factors of rotational speed, particle size, and air volume could be determined. The results indicate that the particle size plays a significant role in the transport capacity of coal dust. Smaller particle sizes and a higher airflow result in a lower deposition degree of coal dust. When the particle size of coal dust is 1.69 mm and the airflow is 300 m³/h, in the case of coal dust generation at a rate of 0.24 m³/h, the deflection angle of the coal dust collection zone is increased by 130% as the rotational speed of the drill rod is increased from 0 to 120 rpm. Similarly, the deflection angle of the coal dust collection zone is increased by 12.8% in a 500 m³/h airflow under the same condition. Additionally, fine particle-sized coal dust is transported in a spiral line. The coal dust with larger particle sizes tends to be in the middle and lower parts of the hole and move along a specific trajectory. Industrial experiences of medium-air-pressure drilling confirm that a rotary drilling speed between 80 and 120 rpm, with a minimum air volume of 400 m³/h and preferably 500 m³/h, can promote a smooth hole drilling effect and enhance the construction safety in the gas drainage process. Full article

Mucus, composed significantly of glycosylated mucins, is a soft and rheologically complex material that lines respiratory, reproductive, and gastrointestinal tracts in mammals. Mucus may present as a gel, as a highly viscous fluid, or as a viscoelastic fluid. Mucus acts as a barrier to the transport of harmful microbes and inhaled atmospheric pollutants to underlying cellular tissue. Studies on mucin gels have provided critical insights into the chemistry of the gels, their swelling kinetics, and the diffusion and permeability of molecular constituents such as water. The transport and dispersion of micron and sub-micron particles in mucin gels and solutions, however, differs from the motion of small molecules since the much larger tracers may interact with microstructure of the mucin network. Here, using brightfield and fluorescence microscopy, high-speed particle tracking, and passive microrheology, we study the thermally driven stochastic movement of 0.5–5.0 μm tracer particles in 10% mucin solutions at neutral pH, and in 10% mucin mixed with industrially relevant dust; specifically, unmodified limestone rock dust, modified limestone, and crystalline silica. Particle trajectories are used to calculate mean square displacements and the displacement probability distributions; these are then used to assess tracer diffusion and transport. Complex moduli are concomitantly extracted using established microrheology techniques. We find that under the conditions analyzed, the reconstituted mucin behaves as a weak viscoelastic fluid rather than as a viscoelastic gel. For small- to moderately sized tracers with a diameter of lessthan 2 $\mathsf{\mu }$m, we find that effective diffusion coefficients follow the classical Stokes–Einstein relationship. Tracer diffusivity in dust-laden mucin is surprisingly larger than in bare mucin. Probability distributions of mean squared displacements suggest that heterogeneity, transient trapping, and electrostatic interactions impact dispersion and overall transport, especially for larger tracers. Our results motivate further exploration of physiochemical and rheological mechanisms mediating particle transport in mucin solutions and gels. Full article

Flow pattern monitoring of gas–liquid–solid mixed flow has great significance to enhance the quality and efficiency of material mixing, and the material transport mechanism and dynamic control strategy are faced with significant challenges. To solve these problems, a computational fluid mechanics and discrete element method (CFD-DEM) coupling modeling and solving approach based on soft sphere and porous models is presented to explore material transport mechanisms. The user-defined function (UDF) is adopted to perform data communication, and the porosity of the porous model is calculated to achieve the bidirectional calculation of Eulerian fluid and Lagrange particle phases. Material transport processes of gas–liquid–solid mixed flows are discussed to explore material transport mechanisms of particle flow and the flow pattern evolution laws under the inflation control are obtained. The results show that the particles are not evenly distributed under the synergistic action of impeller rotation and inflation. The particles in the upper and lower impeller have similar characteristics along the radial direction, and there is an aggregation phenomenon in the impeller center. A certain degree of inflation enhances the macroscopic mixing process of turbulent vortices, promotes the particle suspension effect inside the container, and improves the material transport efficiency inside the mixing space. Relevant research results can provide theoretical references for the material transport mechanism, flow pattern tracking models, and energy transfer and can also provide technical support for chemical process separation, food processing, battery homogenate mixing, and other production processes. Full article

Heavy metal toxicity generally refers to the negative impact on the environment, humans, and other living organisms caused by exposure to heavy metals (HMs). Heavy metal poisoning is the accumulation of HMs in the soft tissues of organisms in a toxic amount. HMs bind to certain cells and prevent organs from functioning. Symptoms of HM poisoning can be life-threatening and not only cause irreversible damage to humans and other organisms; but also significantly reduce agricultural yield. Symptoms and physical examination findings associated with HM poisoning vary depending on the metal accumulated. Many HMs, such as zinc, copper, chromium, iron, and manganese, are present at extremely low levels but are essential for the functioning of plants. However, if these metals accumulate in the plants in sufficient concentrations to cause poisoning, serious damage can occur. Rice is consumed around the world as a staple food and incidents of HM pollution often occur in rice-growing areas. In many rice-producing countries, cadmium (Cd), arsenic (As), and lead (Pb) have been recognized as commonly widespread HMs contaminating rice fields worldwide. In addition to mining and irrigation activities, the use of fertilizers and pesticides has also contributed significantly to HM contamination of rice-growing soils around the world. A number of QTLs associated with HM stress signals from various intermediary molecules have been reported to activate various transcription factors (TFs). Some antioxidant enzymes have been studied which contribute to the scavenging of reactive oxygen species, ultimately leading to stress tolerance in rice. Genome engineering and advanced editing techniques have been successfully applied to rice to improve metal tolerance and reduce HM accumulation in grains. In this review article, recent developments and progress in the molecular science for the induction of HM stress tolerance, including reduced metal uptake, compartmentalized transportation, gene-regulated signaling, and reduced accumulation or diversion of HM particles to plant parts other than grains, are discussed in detail, with particular emphasis on rice. Full article

Two important phenomena of the solar wind–magnetosphere–ionosphere coupling are auroral particle precipitation and the formation of ions flowing upward from the ionosphere. They have opposite transport directions of energy and substance. Based on the observations of particle precipitation and ion drift from the DMSP F13 satellite in January and July 2005, the ionospheric ion upflows in dayside auroral oval (0600–1800 MLT) can be divided into five types according to the velocity of ion upflows and the spectrum characteristics of auroral particle precipitation, and the distribution for different types of ion upflows is studied. The results show that the ion upflows mainly occur in the geomagnetic latitude (MLAT) range of 70–80°.The main magnetospheric source region of ion upflows (type A and D) caused by the accelerated electron (mainly the soft electron) corresponds to Low Latitude Boundary Layer (LLBL) and Cusp, and ion upflows of type B and C (related to the process of ambipolar diffusion caused by electron acceleration) mainly occur in LLBL and Boundary Plasma Sheet (BPS), while ion upflows of type E without electron acceleration mainly occur in the central plasma sheet (CPS).The dawn–dusk asymmetry is obvious in the winter season, with the ion upflows mainly occurring on the dawn/dusk side ionosphere. However, the ion upflows in summer mainly occur at the magnetic noon, with a symmetric distribution centered at the magnetic noon. The occurrence of ion upflow in winter is significantly higher than that in summer, and it is significantly enhanced during the period of moderate geomagnetic activity. The upward region expands to the lower latitude when the geomagnetic activity is enhanced. The effect of interplanetary magnetic field (IMF) components has also been studied in this paper. When IMF Bx is negative, the upflow occurrence increases in the region of 1500–1800 MLT and 0600–0900 MLT, with the MLAT range below 70°. The direction of IMF By may lead to the high-incidence area reverse at the prenoon or postnoon region. The occurrence of ion upflows with the MLAT range below 75° increases significantly when IMF is southward. Type A ion upflow has the highest velocity of ion upflows, followed by type E, and type D has the lowest. The average velocity of ion upflows in winter is significantly higher than that in summer. Full article

Non-uniform temperature distributions in air-conditioned areas can reduce the energy efficiency of air conditioners and cause uncomfortable thermal sensations for occupants. Furthermore, it is impractical to use physical sensors to measure the local temperature at every position. This study developed a soft-sensing model that integrates the fundamentals of thermodynamics and transport phenomena to predict the temperature at the target position in space. Water experiments were conducted to simulate indoor conditions in an air-conditioning cooling mode. The transient temperatures of various positions were measured for model training and validation. The velocity vectors of water flow were acquired using the particle image velocimetry method. Correlation analysis of various positions was conducted to select the input variable. The soft-sensing model was developed using the multiple linear regression method. The model for the top layer was modified by the correction of dead time. The experimental results showed the temperature inhomogeneity between different layers. The temperature at each target position under two initial temperatures and two flow rates was accurately predicted with a mean absolute error within 0.69 K. Moreover, the temperature under different flow rates can be predicted with one model. Therefore, this soft-sensing model has the potential to be integrated into air-conditioning systems. Full article

The technology known as cemented paste backfill (CPB) has gained considerable popularity worldwide. Yield stress (YS) is a significant factor considered in the assessment of CPB’s flowability or transportability. The minimal shear stress necessary to start the flow is known as Yield stress (YS), and it serves as an excellent measure of the strength of the particle-particle interaction. The traditional evaluation and measurement of YS performed by experimental tests are time-consuming and costly, which induces delays in construction projects. Moreover, the YS of CPB depends on numerous factors such as cement/tailing ratio, solid content and oxide content of tailing. Therefore, in order to simplify YS estimation and evaluation, the Artificial Intelligence (AI) approaches including eight Machine Learning techniques such as the Extreme Gradient Boosting algorithm, Gradient Boosting algorithm, Random Forest algorithm, Decision Trees, K-Nearest Neighbor, Support Vector Machine, Multivariate Adaptive Regression Splines and Gaussian Process are used to build the soft-computing model in predicting the YS of CPB. The performance of these models is evaluated by three metrics coefficient of determination (R²), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The 3 best models were found to predict the Yield Stress of CPB (Gradient Boosting (GB), Extreme Gradient Boosting (XGB) and Random Forest (RF), respectively) with the 3 metrics of the three models, respectively, GB {R² = 0.9811, RMSE = 0.1327 MPa, MAE = 0.0896 MPa}, XGB {R² = 0.9034, RMSE = 0.3004 MPa, MAE = 0.1696 MPa} and RF {R² = 0.8534, RMSE = 0.3700 MPa, MAE = 0.1786 MPa}, for the testing dataset. Based on the best performance model including GB, XG and RF, the other AI techniques such as SHapley Additive exPlanations (SHAP), Permutation Importance, and Individual Conditional Expectation (ICE) are also used for evaluating the factor effect on the YS of CPB. The results of this investigation can help the engineers to accelerate the mixed design of CPB. Full article