Bidisperse Particles Research Articles

Designing Microfluidic-Chip Filtration with Multiple Channel Networks for the Highly Efficient Sorting of Cell Particles.

Microfluidic-chip based hydrodynamic filtration is one of the passive sorting techniques that can separate cell or particle suspensions into subpopulations of different sizes. As the branch channels and side channels play an important role in maintaining particle focusing, their rational design is necessary for highly efficient sorting. A model framework involving multiple side and multiple branch channels has been developed by extending the analytical analysis of three-dimensional laminar flow in channel networks, which was previously validated by comparison with numerical simulations. Objective parameters were identified as the number of branch channels and each length of individual branches. The presence of multiple side channels causes an increase in the average fluid velocity in main and branch channels as the branch point shifts toward the end of the main channel, which differs from the behavior observed in a single side channel. The number of branches and their individual lengths decrease distinctly in the case of branch channels consisting of narrow and wide sections, which enables the compact design of a microfluidic-chip, being operated by a lower pressure drop under the same throughput. Sorting of bidisperse particles was accomplished with an optimally designed chip to verify this framework by achieving very high recovery and purity.

Representation of aggregates from their two-dimensional images for primary particles of different sizes

This study focused on representing the three-dimensional (3D) structure of individual aggregates based on their two-dimensional (2D) images. This starts with the determination of 2D box-counting fractal dimension (Df,BC,2D), uses a previously derived empirical correlation to obtain 3D power law fractal dimension (Df,PL), and then builds the aggregate on the basis of Df,PL by an existing algorithm. Validation of this procedure can be done in forward or backward manner. Forward validation requires the existence of tomographic measurements of Df,PL. It has been conducted on aggregates of large primary particles produced to this purpose in a spray fluidized bed and analyzed by X-ray micro-computed tomography (μ-CT). For the same agglomerates backward validation has also been exercised, starting the representation from 2D projections of the 3D objects and repeating the same procedure on the represented aggregates to see, how accurately the fractal dimensions of the original objects are reproduced. When the primary particles are too small in size to be resolved by X-ray μ-CT, only 2D imaging data by electron microscopy are usually available. Such images have been taken from literature for aggregates composed of submicron particles or nanoparticles and used for aggregate representation in 3D. Subsequently, backward validation of the procedure has been conducted. Both forward validation and backward validation results indicate a high level of consistency between the fractal characteristics and morphological structures of the represented aggregates and those of the original ones. Additionally, this study shows that the method is effective for aggregates of bidisperse and polydisperse particles.

Bed strength in sheared beds of mono- and bi-disperse particles: Dependence on geometrical and mechanical properties of constituent particles

Temporary plugging zones are low-permeability fracture-scale plugs ‘assembled’ in situ by injecting polymer particles into petroleum reservoirs. We applied the rolling resistance linear model to simulate the shear strength of a rectangular packed bed, our model for a temporary plugging zone, comprising either uniform-sized particles or a binary mixture of larger bridging particles and smaller filling particles. Simulation results show that the strength of uniform beds increases with the size, the aspect ratio, the friction coefficient, and the Young’s modulus of the particles. The strength of binary packed beds first increased and then decreased as the fractional volume of the domain occupied by filling particles increased. Maximum strength was achieved when bridging particles have uniform Young’s modulus and aspect ratio but a range of friction coefficients, and their friction coefficient, Young’s modulus and aspect ratio are 21%, 17% and 18% larger than those of filling particles.

A high-sensitivity and multi-response magnetic nanofiber-aerogel sensor with directionally aligned porous structure based on triple network for interactive human–machine interfaces

Flexible multimodal sensors with a porous structure have attracted tremendous attentions due to their low density, high specific surface area, a wide detection range and satisfied deformability. However, pores disorder and maldistribution issues of these multimodal sensors are major concerns during their sensing response, which often cause poor linearity and unstable sensing characteristics. Herein, a facile and rapid approach was proposed to fabricate a multifunctional magnetic sensor with directionally aligned porous structure based on triple network by combining electrospun nanofibers, bidisperse magnetic particles and sodium alginate/chitosan foam. The electrospun nanofibers were employed as three-dimensional skeletons for the crystallization and vertical growth of ice crystals. Benefiting from the remarkable structure orientation, the homogenized nanofiber-aerogel scaffold possesses excellent flexibility, superior deformation recoverability and biocompatibility. The assembled sensors not only exhibit a high sensitivity (0.40 T−1), rapid response/recovery time and long stability under magnetic stimuli, but also displays satisfied cross-sensitivity, quick response and reliable durability (8000 cycles) in response to external mechanical functions. Importantly, the respective input stimuli could be clearly discriminated via outputting the electrical signals of opposite or different trends. Furthermore, the sensor could be employed as wearable skins to monitor various physiological signals and realize information translation by Morse mode for individuals with disabilities. Additionally, a wearable gesture recognition system with assistance of the deep learning algorithm was testified, with high average recognition accuracy of 99 %. The simple fabrication process and prominent multifunctional characteristics of the proposed sensor endow it with an extensive application prospect in the field of interactive human–machine interfaces.

Turbulence modulation by charged inertial particles in channel flow

Large amounts of small inertial particles embedded in a turbulent flow are known to modify the turbulent statistics and structures, a phenomenon referred to as turbulence modulation. While particle electrification is ubiquitous in particle-laden turbulence and significantly alters particle behaviour, the effects of inter-particle electrostatic forces on turbulence modulation and the underlying physical mechanisms remain unclear. To fill this gap, we perform a series of point-particle direct numerical simulations of turbulent channel flows at a friction Reynolds number of approximately 540, laden with uncharged and charged bidisperse particles. The results demonstrate that, compared to flows laden with uncharged particles, the presence of inter-particle electrostatic forces leads to substantial changes in both turbulent intensities and structures. In particular, the inner-scaled mean streamwise fluid velocity is found to shift towards lower values, indicating a noticeable increase in fluid friction velocity. Turbulent intensities appear to be further suppressed through facilitating the particles to extract momentum from the fluid phase and increasing extra turbulent kinetic dissipation by particles. Importantly, the overall drag is enhanced by indirectly strengthening the contribution of particle stress, even though the contribution of the total fluid stress is decreased. On the other hand, the magnitude of the large-scale motions is weakened by simultaneously reducing turbulent production and increasing particle feedback around the scales of the large-scale motions. Meanwhile, the average streaky fluid structures in the streamwise–spanwise planes and inclined fluid structures in the streamwise–wall-normal planes become expanded and flattened, respectively.

Prediction of separation density of pulsed fluidized bed based on bidisperse particle characteristics

ABSTRACT Fluidized bed technology plays a vital role in petroleum, chemical, and coal separation. The dry separation of coarse coals with a particle size of >6 mm has been efficiently achieved using the fluidized bed. However, for fine coal with a particle size of 6–1 mm, ordinary fluidized bed technology is unable to effectively separate it. In light of this issue, the present study incorporates airflow vibration energy into conventional fluidized beds, with a specific focus on the separation process of fine coal. The investigation explores the variation pattern of separation density and delves deep into the influencing factors affecting coal preparation through bed density. A theoretical model for separation density is established based on the characteristics of bidisperse particles, which is subsequently validated and calibrated using dry separation experiments conducted on fine coal. The error is controlled within 10% while achieving a possible deviation E as low as 0.095 g/cm3.

Fully coupled discrete element method for graded particles transport in pipes

Hydraulic conveying of graded particles is much more complex than that of uniform particles but is not fully understood. A fully coupled computational fluid dynamics–discrete element method model is established for the hydraulic conveying of graded particles, which integrally considers the particle–fluid and particle–particle interactions and turbulence modulation from particles. The proposed model accounts for the stochastic motion of particles by the discrete random walk method and applies the diffusion averaging algorithm to obtain particle concentration in arbitrary cells for smooth and cell-independent data fields on unfavorable cells (fluid cell size ≤ particle size). The particle–fluid drag force is applied to slurry flows through densely packed particle beds due to the consideration of porosity modification. The proposed model well performs in simulating the hydraulic conveying of dense graded particles. Dynamics in slurry mixtures of bi-disperse particles are investigated regarding different particle size compositions. The results show obvious stratification between coarse and fine particles, e.g., fine particles settling at the pipe bottom elevate the coarse particles and form a “lubrication layer” with high velocity. The torque caused by particle–particle/wall contact is greater than the torque caused by the fluid. The pipe cross section is divided into four regions according to the particle angular velocity. The effect of particle concentration on liquid motion is small because the difference in local particle concentration is relatively small, but the maximum pressure drop corresponds to a critical particle size composition.

Metal-organic framework photonic crystals with bidisperse particles-based brilliant structural colors and high optical transparency for elaborate anti-counterfeiting

Photonic crystals (PCs) have attracted great interest and wide applications in displays, printing, anti-counterfeiting, etc. However, two main challenges significantly hinder their applications: 1) the tradeoff between high optical transparency across the whole visible range and brilliant colors requiring a large refractive index contrast (Δn), and 2) the way of regulating structural colors by altering tens of different sizes. To address these issues, a new type of metal–organic framework (MOF)-based transparent photonic crystal (TPC) has been fabricated through self-assembling MOF particles into three-dimensional ordered structures which were then infiltrated by polydimethylsiloxane (PDMS). Compared to conventional PCs, these TPCs exhibit 1) both brilliant forward iridescent structural colors and high transmittance (>75 %) across the whole visible spectra range, and 2) conveniently adjustable colors based on bidisperse particles. The unique color-generating mechanism of the light diffraction by each plane lattice and the small Δn between MOF particles and PDMS are the keys to TPCs’ characteristics. Moreover, the prepared invisible anti-counterfeit labels can reversibly hide-reveal patterns with elaborate and exchangeable color contrast in a non-destructive way, showing potential applications in anti-counterfeiting, information encryption, and optical devices.

Viscosity-modulated clustering of heated bidispersed particles in a turbulent gas

Clustering of externally and evenly heated particles is enhanced by the increased viscosity of heated fluid in the vicinity of these clusters – a phenomenon known as viscous capturing (VC). Herein we study, via direct numerical simulations of decaying turbulence, the effect of temperature-driven viscosity on clustering with different particle loading densities. We employ a two-way momentum and energy coupling, and gas viscosity is modelled by a power law to understand the role of the increased drag and particle back-reaction force on the clustering intensity. For the continuum and dispersed phases, Eulerian and Lagrangian point particle schemes have been used, neglecting inter-particle collisions. We found that the enhanced viscosity-driven clustering is a strong function of particle loading density, as the increase in particle number density enables the formation of large uneven clusters before heating, which is the main condition for VC to take effect. Higher number density should result in greater turbulence modulation and negate local temperature-based viscous effects leading to VC. However, due to higher local particle number density in the clusters and interphase heat transfer, increased drag force prevails in such cases and delivers excessive clustering. By sampling conditionally the particle velocity and temperature inside the clusters, it is found that the thermodynamic and kinematic properties of the particles in the clusters are highly correlated, and this correlation increases with the particle loading density. Therefore, based on the particle number density, temperature-based viscosity can enhance considerably the clustering of heated particles and alter the effect of particles on the underlying turbulence.

Hydrodynamics of polydisperse gas-solid flows: Kinetic theory and multifluid simulation

Polydisperse gas-solid flows, which is notoriously difficult to model due to the complex gas-particle and particle-particle interactions, are widely encountered in industry. In this article, a refined kinetic theory for polydisperse flow is developed, which features single-parameter Chapman-Enskog expansion (the Knudsen number) and exact calculation of the integrations related to pair distribution function of particle velocity without any mathematical approximations. The Navier-Stokes order constitutive relations for multifluid modeling of polydisperse gas-solid flow are then obtained analytically, including the solid stress tensor, the solid-solid drag force, the granular heat flux and the energy dissipation rate. Finally, the model is preliminarily validated by comparing to the discrete element simulation data of one-dimensional granular shear flow and by showing that the hydrodynamic characteristics of gas-solid flows in a bubbling fluidized bed containing bidisperse particles can be successfully predicted.

Fabric-based jamming phase diagram for frictional granular materials.

A jamming phase diagram maps the phase states of granular materials to their intensive properties such as shear stress and density (or packing fraction). We investigate how different phases in a jamming phase diagram of granular materials are related to their fabric structure via three-dimensional discrete element method simulations. Constant-volume quasi-static simple shear tests ensuring uniform shear strain field are conducted on bi-disperse spherical frictional particles. Specimens with different initial solid fractions are sheared until reaching steady state at a large shear strain (200%). The jamming threshold in terms of stress, non-rattler fraction, and coordination numbers (Z's) of different contact networks is discussed. The evolution of fabric anisotropy (F) of each contact network during shearing is also examined. By plotting the fabric data in the F-Z space, a unique critical fabric surface (CFS) becomes apparent across all specimens, irrespective of their initial phase states. Through the correlation of this CFS with fabric signals corresponding to jamming transitions, we introduce a novel jamming phase diagram in the fabric F-Z space, offering a convenient approach to distinguish the various phases of granular materials solely through the direct observation of geometrical arrangements of particles. This jamming phase diagram underscores the importance of the microstructure underlying the conventional jamming phenomenon and introduces a novel standpoint for interpreting the phase transitions of granular materials that have been exposed to processes such as compaction, shearing, and other complex loading histories.

Compression of an Assembly of Bi-Dispersed Particles

Compression of an Assembly of Bi-Dispersed Particles

Discovery of asymmetric distribution of fine particles in fluidization using signal deflection reconstruction measurement

Bubbles in fluidization contribute to efficient gas–solid interaction and excellent transfer behavior. The fines addition effectively improves fluidization quality by prioritizing bubble control. Our study delves into the dynamic behavior of these added fines through cold-flow fluidization experiments, employing coarse glass particle (Geldart Group B, 186 μm in diameter) with varying contents of fines (Geldart Group A, 60 μm in diameter). To overcome the challenge of measuring the solid volume fractions of individual components in this bi-disperse system, a novel measurement technology, coupled with an optical fiber probe and signal deflection reconstruction method, is established. This technology could sensitively capture the preferential entry of fines into bubbles, leading to an asymmetric distribution of fines between bubbles and emulsion phase. Furthermore, our proposed flux mode, considering both the capability to maintain mono-disperse phase segregation and the competitive occupation of bi-disperse particles through bubble interface, effectively describes the observed asymmetry.

Wet classification behavior of bidisperse colloidal particles through nanofibrous membrane

Membrane separation has emerged as a prominent method for the removal of undesirable particles from wastewater in the field of water treatment. However, classification of particles with varying sizes by membrane is still poorly understood, warranting further exploration. This study is to investigate the wet classification behaviors of polydisperse particles using a nanofibrous membrane that features a complex three-dimensional network structure and high porosity. The experimental results demonstrate that the nanofibrous membrane is effective in retaining larger particles, while its high porosity facilitates the smooth passage of smaller particles. To clarify the classification mechanism, we analyzed the filtration model and employed SEM images taken at different stages of the process to investigate the retention behavior of larger particles. The filtration of larger particles through microfiltration membrane exhibited a cake filtration model. The blockage of large particles on the membrane surface formed a cake layer, significantly reducing the filtration rate. Conversely, the nanofibrous membrane exhibited continuous intermediate blocking filtration at pH 11, resulting in effective retention of larger particles inside the membrane rather than solely on membrane surface. This enabled better utilization of the pore space within the nanofibrous membrane, thus highlighting it as a potential area for future research.

Separating micrometer-sized particles utilizing a dusty plasma ratchet

Directional transport-dominated particle separation presents major challenges in many technological applications. The Feynman ratchet can convert the random perturbation into directional transport of particles, offering innovative separation schemes. Here, we propose the design of a dusty plasma ratchet system to accomplish the separation of micrometer-sized particles. The dust particles are charged and suspended at specific heights within the saw channel, depending on their sizes. Bi-dispersed dust particles can flow along the saw channel in opposite directions, resulting in a perfect purity of particle separation. We discuss the underlying mechanism of particle separation, wherein dust particles of different sizes are suspended at distinctive heights and experience electric ratchet potentials with opposite orientations, leading to their contrary flows. Our results demonstrate a feasible and highly efficient method for separating micrometer-sized particles.

Pinning and Depinning Dynamics of an Evaporating Sessile Droplet Containing Mono- and Bidispersed Colloidal Particles on a Nonheated/Heated Hydrophobic Substrate

The present study is primarily focused on the coupled effects of substrate heating, colloidal dispersion, and particle size variation on the contact line (CL) pinning-depinning dynamics of evaporating droplets containing mono- (3/4.5 μm) and bidispersed (3 and 4.5 μm) polystyrene colloidal particles on poly(dimethylsiloxane) (PDMS) substrates. Experimental techniques such as high-speed visualization, optical microscopy, infrared thermography, and scanning electron microscopy are implemented to discover the plausible causes dictating the underlying physics. In the case of the nonheated substrate, there exists a significant delay in the CL depinning for the evaporating droplets containing bidispersed particles, as opposed to the monodispersed cases. A first-order model is illustrated for the determination of the net horizontal force acting on the particles near the CL. Interestingly, the model's findings revealed that due to the difference of particle size in the case of the bidispersed suspension, the interparticle contact force gets modified, thus enhancing the CL pinning. For the heated substrate cases, droplets with monodispersed particles (3 μm) exhibit a substantial delay in the CL depinning, whereas a nearly complete pinning of the CL is witnessed for the case of bidispersed colloidal suspension droplets. It is mainly due to the augmentation of particle deposition near the CL because of the circulatory thermal Marangoni and outward capillary flows. Thus, the mobility of the CL is inhibited, which is further reinforced by the presence of different-sized particles. Eventually, a ring-like deposition is observed, as opposed to an inner deposit commonly observed from the evaporation of colloidal droplets on hydrophobic substrates.

Modeling particle collisions in moderately dense curtain impacted by an incident shock wave

The interactions between an incident shock and a moderately dense particle curtain are simulated with the Eulerian–Lagrangian method. A customized solver based on OpenFOAM is extended with an improved drag model and collision model and then validated against two benchmark experiments. The results show that the collision model has a limited impact on curtain morphology compared with the improved drag model. In this work, parametric studies are performed considering different particle sizes, volume fractions, and curtain thicknesses. Smaller particle sizes and larger volume fractions lead to stronger reflected shock and weaker transmitted shock. Attention is paid to the particle collision effects on the curtain evolution behaviors. According to our results, for the mono-dispersed particle curtain, the collision effects on curtain front behaviors are small, even when the initial particle volume fraction is as high as 20%. This is due to the positive velocity gradient across the curtain after the shock wave passage, leading to the faster motion of downstream particles than the upstream ones, and hence, no collision occurs. For the bi-dispersed particle curtain, the collision effects become important in the mixing region of different-size particles. Collisions decelerate small particles while accelerating large ones and cause velocity scattering. Moreover, increasing the bi-dispersed curtain thickness leads to multiple collision force peaks, which is the result of the delayed separation of different particle groups. Our results indicate that the collision model may be unnecessary to predict curtain fronts in mono-dispersed particles, but in bi-dispersed particles, the collision effects are important and, therefore, must be modeled.

Insight into multi-level fluidization characteristics of a spout-fluid bed under different gas-solid actions: From monodisperse particles to bidisperse particles

In this study, the effects of gas flow and particle parameters on monodisperse and bidisperse particles were systematically modelled with CFD-DEM from multi-level characteristics: fluidity, periodicity and mixing. With increasing spouting gas velocity, the mixing rate increased and overall flow state changed from spout-fluid to the spout. By comparison, the increase of auxiliary gas velocity showed the opposite variation trend. For bidisperse particles, with increasing light and small particle ratios, the dominant particles of fluidization characteristics changed from coarse and heavy to light and small particles, whose variation regularities were similar to those of single particle size and density. Furthermore, the particle fluidity improved continuously and local particle concentration differences increased. Ultimately, the particle segregation mechanism was proposed by summarizing variation regularities of fluidization characteristics under different gas-solid actions. Besides, compared to particle density, the difference in particle size caused greater stratification, which would reduce the local mass transfer efficiency. • The spout-fluid bed is deeply analyzed from fluidity, periodicity and mixing. • The particle motion behaviors under different gas-solid actions are investigated. • The segregation mechanism between mono-and bidisperse particles is summarized. • The increase of light and small particles contributes to the fluidization quality.

High-performance dual-sensitive flexible sensors based on conductive alginate sponge electrode/polyvinylidene fluoride microporous composite film

This work reported a novel dual-sensitive flexible sandwich sensor based on conductive natural biopolymers sponge electrode and polyvinylidene fluoride (PVDF) film with superiorities of high sensitivity, long lifespan and low density. The unique natural biopolymers sponge electrode, consisting of bidisperse magnetic particles and sodium alginate/chitosan (SA/CHI) with physically-crosslinked double-network structure, showed a high response capability to external magnetic fields. Besides, by combining the advantages of SA/CHI sponge electrode (high elasticity and flexibility) and PVDF film (exceptional stiffness and piezoelectricity), the SA/CHI/PVDF composite film also exhibited preferable mechanical strength and strain-dependent electrical property, which can simultaneously satisfy the requirements of high sensitivity detection to external magnetic fields and strains. Specifically, the relative resistance variation of SA/CHI/PVDF-1.00 sensor reached as high as 60.4% under a cycling loading of 240 mT magnetic field. Meanwhile, their electrical responses could also display a significant variation and relatively stable recoverability under periodic stretching, bending or compressing excitations. Afterwards, a potential working mechanism and equivalent circuit model were provided to study the magnetic/mechanic sensitivity of SA/CHI/PVDF sensors. Furthermore, a 4 × 4 SA/CHI/PVDF sensor array was developed to perceive and distinguish both magnetic field and compressive force, which indicated its favorable potential in wearable electronics and soft robotics.

Critical comparison of polydisperse kinetic theories using bidisperse DEM data

Kinetic theories have been developed to describe the hydrodynamics of polydisperse granular flows under different theoretical assumptions. In this study, six species theories are assessed using the DEM data obtained from simple shear flow containing bidisperse particles with low and moderate solid volume fraction (Galvin, 2007). It was shown that (i) only the theories of Iddir and Arastoopour (2005) and Zhao and Wang (2021) can qualitatively capture all of the effects of various parameters on the granular temperature ratio and the normal and shear stresses; (ii) the granular temperature ratio can be predicted accurately either by Iddir and Arastoopour (2005) or Zhao and Wang (2021), depending on the input parameters; and (iii) the predictions of normal and shear stresses by Iddir and Arastoopour (2005) are superior in matching the DEM data for most tested cases. Present study not only discusses the fundamental differences between different species kinetic theories, but also offers a critical assessment of their suitability in modeling simple shear flow.