System Of Spherical Particles Research Articles

Reversible Binding Interfaces Made of Microstructured Polymer Brushes.

The polymer brush architecture of the end-tethered polymer molecules is one of the most widely used efficient methods to regulate interfacial interactions in colloidal systems found in live matter and manufactured materials. Emerging applications of polymer brush structures require solutions to new tasks in the control of interfacial interactions. The rapid development of live cell manufacturing relies on scalable and efficient cell harvesting methods. Stimuli-responsive surfaces made of surface-grafted poly(N-isopropylacrylamide) (PNIPAM) can bind and detach the adherent cell upon changes in temperature and have been used for cell growth and harvesting. The applications are limited by the requirement to satisfy a range of PNIPAM coating characteristics that depend on the dimensions of the integrin complex in the cell membrane and the basal surface. The analysis of the microstructured surfaces, when adhesive and disjoining functions of the microdomains are decoupled, shows that many limitations of PNIPAM one-component coatings can be avoided by using a much broader range of structural characteristics of the microstructured interfaces composed of alternating disjoining PNIPAM domains and adhesive polymeric domains with cell-affinity functional groups. Temperature-controlled reversible adhesion to such microstructured interfaces is studied here experimentally with model systems of solid spherical particles and by employing simulations for solid and soft membranes interacting with the microstructured surfaces to mimic interactions with soft and solid disk-like particles.

Quasi-steady-state modelling and characterization of diffusion-controlled dissolution from polydisperse spheroidal particles, II: characterization

A quasi-steady-state model for accurately predicting the detailed diffusion-dominated dissolution process of polydisperse spheroidal (prolate, oblate and spherical) particle systems was presented in Part I of this study. In the present paper, the dissolution characteristics of typical polydisperse spheroidal particle systems have been extensively investigated. The effects of the distributions of particle size and shape have been studied by examining the detailed dissolution processes, such as the size reduction rates of individual particles, the increase in bulk concentration and the dissolution time of the polydisperse systems. Some important factors controlling the dissolution process, including initial particle concentration, smallest and largest particle sizes, and the smallest and largest Taylor shape parameters, have been identified.

Quasi steady-state modelling and characterization of diffusion-controlled dissolution from polydisperse spheroidal particles, I: modelling

A quasi steady-state model (QSM) for accurately predicting the detailed diffusion-dominated dissolution process of polydisperse spheroidal (prolate, oblate and spherical) particle systems with a broad range of distributions of particle size and aspect ratio has been developed. A rigorous, mathematics-based QSM of the dissolution of single spheroidal particles has been incorporated into the well-established framework of polydisperse dissolution models based on the assumption of uniform bulk concentration. Validation against experimental results shows that this model can accurately predict the increase in bulk concentration of polydisperse systems with various particle sizes and shape parameters. A series of representative instances involving the dissolution of polydisperse felodipine particles at various concentration ratios is used to demonstrate the model's effectiveness, rendering it a valuable tool for understanding and managing complex systems with diverse particle characteristics.

Visualization of Radiation Scattering Indicatrix on a Polydisperse System of Spherical Particles

The article is devoted to solving the direct problem of light scattering on an ensemble of spherical polydisperse particles. The paper presents an algorithm for computer simulation of the optical radiation scattering indicatrix by a particle system based on the theory of G. Mie. The influence of the relative complex refractive index of scattering centers and their size distribution, wavelength and polarization state of incident light on computer models of scattering indicatrix is investigated. The practical significance of the results obtained lies in the fact that computer models of scattering indicatrix are useful in the experimental study of dispersed systems by static light scattering for the optimal choice of installation parameters and experimental conditions and, more importantly, in solving the inverse problem of the static light scattering method to restore the characteristics of nanoparticles from experimental data.

Kinetic modeling of fluid-induced interactions in compressible, rarefied gas flows for aerodynamically interacting particles

In the study of gas-particulate multiphase systems, the flow of high-speed gas through a distribution of solid particulates is of utmost importance. While these aerodynamically interacting systems have been extensively studied for low-speed gas flows in the gas continuum regime, less attention has been given to high-speed systems where non-continuum effects are significant due to the high flow gradients. To address this, the flow of rarefied gas through an aerodynamically interacting monodisperse spherical particle system is studied using the Direct Simulation Monte Carlo (DSMC) gas-kinetic approach. Since the method provides the best resolution of shocks at supersonic Mach numbers it is used to classify the weak separated shocks and strong collective shocks in these systems based on particle spacing in a two-particulate system at different orientation angles. The study used the two-particle system to help analyze more complex particle distributions of volume fractions, 1%, 5%, and 15%, exposed to gas flows in the slip and transitional gas regime for a free-stream Mach number range of 0.2<Ma∞<2.0. We observe that the weak separated shocks in the 1% distribution allow a higher degree of gas penetration and shock-particle interactions or “hypersonic-surfing”, exposing a major fraction of the particulates to higher force magnitudes. In contrast, the strong collective shock in the 5% and 15% distributions only generates high particulate forces on the flow-facing particles. Finally, a simple stochastic model is proposed for use in large-scale Eulerian–Lagrangian simulations that captures the non-monotonic behavior of average drag and force variability generated by the complicated gas particulate interactions in the compressible gas regime.

Application of Bonded-Block Models to Rock Failure Analysis

Discrete element models are being increasingly applied to model rock failure processes. Bonded-particle models, based on circular or spherical particle systems, have been successfully used for two decades. More recently, bonded-block models, using polygonal or polyhedral elements, have proven to be a powerful alternative. This paper describes the basis of the application of these models in the numerical simulation of failure in rock materials. The critical governing parameters are identified, and their influence is discussed. The model calibration procedure based on the analysis of laboratory tests is discussed. An application example of an underground excavation problem is presented using a simple bonded-block model employing rigid blocks and a bilinear softening contact model. The results show the capability of this approach to reproduce observed failure modes involving block fractures.

Spatial Structure Characteristics of Underground Reservoir Water Storage Space in Coal Mines Considering Shape Characteristics of Crushed Rock

In order to investigate the impact of a crushed rock shape on the storage coefficient of underground reservoirs in coal mines, statistical analysis of the shape characteristics of crushed rocks was conducted, which was followed by numerical packing tests using the rigid block model. These tests aimed to investigate the spatial structure characteristics of underground reservoir water storage space in coal mines under the influence of different shapes of crushed rock. The results demonstrated the following: (1) Crushed rock exhibits a lognormal distribution in its shape characteristic parameters at different scales with a predominant discoid shape. The shape coefficient M can be utilized as a comprehensive indicator to characterize the shape characteristics of crushed rock. (2) The average storage coefficient of crushed rock increases exponentially as the shape coefficient M increases. There is a 50.1% increase in the storage coefficient from M = 1 to 3.5. (3) The spatial structure of the water storage space exhibits self-similarity, and both the void fractal dimension and the void boundary fractal dimension increase with an increase in the shape coefficient M. (4) When comparing the non-spherical particle system with the spherical particle system, it is observed that the spherical particle system has smaller water storage space, lower connectivity among voids, and more irregular void space. In the non-spherical particle system, the water storage space becomes larger as the shape of crushed rock becomes more irregular, resulting in more irregular void space. However, there is no significant effect on void connectivity.

Retrieving mean volumetric properties of multiphase flows from 2D images: A new approach combining deep learning algorithms and 3D modelling

Measuring the morphological properties of complex multiphase systems is a crucial problem in many areas of science and industry and is particularly difficult in dense environments with limited optical access. This paper presents a new approach capable of extracting three-dimensional (3D) information from spherical particle systems based solely on two-dimensional (2D) projections of the system. Synthetic images of the system are generated using a stochastic geometrical model from a simulated 3D particle system with the same geometrical features as the studied system, which is projected into 2D images labeled with the appropriate 3D information. These images are then fed to a convolutional neural network (CNN) for training before being tested on synthetic and experimental images. Validation results show that this technique successfully predicts the mean features of the studied systems, even for dense environments with overlapping particles, with high computational efficiency.

Microspectroscopy on Thin Films of Colloidal Mixture Gradients for Data‐Driven Optimization of Optical Properties

AbstractThin films comprising mixtures of different colloids provide a simple approach to materials with tunable optical properties. However, the prediction of UV–vis spectra for different compositions in colloidal crystals and glasses is difficult. The degree of disorder, for example, determines whether the optical response is dominated by incoherent scattering, coherent scattering, or Bragg diffraction. Both the volume ratio, as well as the morphology of the individual constituents, influence the properties of the ensemble, which necessitates extensive screening procedures. Here, a method for expediting such a screening approach by means of gradient colloidal crystals and glasses is shown. Continuous composition gradients, combined with local microspectroscopy, allow for the characterization of the entire composition range with high reproducibility, thereby reducing the experimental effort. This is shown for a system of spherical polymer particles with different radii. An optimum of the scattering efficiency in the visible wavelength range is shown close to the order/disorder transition at the edge of the composition range. The high‐throughput screening method presented here can generate large data sets that may contribute to machine‐learning‐enabled optimization of self‐assembled optical materials.

Numerical study of blockage and arching behavior of particle with different shapes in packed bed

Blockage has a significant impact on the flow and heat transfer characteristics of particles in discharging process and can affect the system security seriously. In this study, the discrete element method (DEM) was adopted to analyze the discharge flow of pebbles, ellipsoids, and cubes. The mechanism of blockage formation is the mechanical interaction between particles. With the increase of axial force, the frequency of the blockage increases. High probability of blockage formation arises when the local axial velocity difference dvzl is less than 0.075, while a large local difference in axial velocity (dvzl≥ 0.075) can efficiently avoid blockage. With the increase of the bottom cone angle α of the geometric of the packed bed, blockage during particle flow can be avoided. When α increased to 60°, the particles of Rd less than 0.248 can be discharged smoothly. In addition, the coefficient of friction μ between particles, the ratio of particle diameter to discharge orifice diameter Rd and the aspect ratio Ra of non-spherical particles are all factors influencing the formation of blockages. The critical conditions for particle blockage formation were proposed. For actual working condition of engineering, the application of Rd less than 0.24 and μ less than 0.4 can effectively avoid blockage formation and ensure relatively safe operation for spherical particle systems. For ellipsoidal particles, low aspect ratio (Ra≤4) can effectively avoid blockage.

Voronoi tessellation-based algorithm for determining rigorously defined classical and generalized geometric pore size distributions.

The geometric pore size distribution (PSD) P(r) as function of pore radius r is an important characteristic of porous structures, including particle-based systems, because it allows us to analyze adsorption behavior, the strength of materials, etc. Multiple definitions and corresponding algorithms, particularly in the context of computational approaches, exist that aim at calculating a PSD, often without mentioning the employed definition and therefore leading to qualitatively very different and apparently incompatible results. Here, we analyze the differences between the PSDs introduced by Torquato etal. and the more widely accepted one provided by Gelb and Gubbins, here denoted as T-PSD and G-PSD, respectively, and provide rigorous mathematical definitions that allow us to quantify the qualitative differences. We then extend G-PSD to incorporate the ideas of coating, which is significant for nanoparticle-based systems, and of finite probe particles, which is crucial to micro and mesoporous particles. We derive how the extended and classical versions are interrelated and how to calculate them properly. We next analyze various numerical approaches used to calculate classical G-PSDs and may be used to calculate the generalized G-PSD. To this end, we propose a simple yet sufficiently complicated benchmark for which we calculate the different PSDs analytically. This approach allows us to completely rule out a recently proposed algorithm based on radical Voronoi tessellation. Instead, we find and prove that the output of a grid-free classical Voronoi tessellation, namely, the properties of its triangulated faces, can be used to formulate an algorithm, which is capable of calculating the generalized G-PSD for a system of monodisperse spherical particles (or points) to any precision, using analytical expressions. The Voronoi-based algorithm developed and provided here has optimal scaling behavior and outperforms grid-based approaches.

Experimental study of free drainage of mixed cubic and spherical particles in a monolayer granular system

The granular system of varied shapes is important in industrial production. Once the particles are deformed and crushed into parts, the characteristics of free discharge will become complicated and different from the spheres greatly. In this work, to further study the free-discharging characteristics of the mixed granular system for cubic and spherical particles, an unloading experiment of the mixed granular system is designed, with relevant experimental platforms. The algorithm for the particle recognition used in the particle tracking velocimetry (PTV) system mixed with cubic and spherical particles is applied. The effect of non-spherical particle fractions on the flow rate of discharge, residence time, and translational and rotational movement for non-spherical particles are analyzed based on PTV and the method of marked particles. It was found that a larger percentage of cubic particles has the effect of impeding particles' movement, especially in the near-wall region. The rotational movement of cubic particles becomes more intense and evident in the region below the middle of the silo. Number of contacted cubic particles during the discharge for cases when R cp0 = 10% and 15% (a), and some images during the discharge (b)(c)(d). • The discharge process of the mixed cubic and spherical particle system is analyzed. • A recognition and PTV algorithm for a mixed particle system is proposed. • Larger components of cubic particles impede the movement of the whole system. • Appropriate addition of cubic particles can locally promote the central discharge. • The rotational movement of a non-spherical particle is revealed by marked particles.

Effect of Particle Form and Surface Friction on Macroscopic Shear Flow Friction in Particle Flow System

The damage caused by landslide disasters is very significant. Among them, landslides after forest fires have been widely concerned by scholars in recent years due to their particular physical and chemical properties. This large-scale shear flow of particulate matter has similarities to fluid systems. However, due to the discontinuity of the particle system, its flow process has significant random characteristics. To investigate the random properties of particle systems, this study conducted a series of ring shear tests on four particle systems. The effects of the particle shape, normal stress, and shear velocity on the systems’ shear rheological features were investigated using experimental data. The particle form has an important effect on the macroscopic properties of the system. In a spherical particle system, the macroscopic friction fluctuation is determined by the friction of the particle surface and the system’s normal stress. The shear velocity has a minor effect on this characteristic. Three elements simultaneously influence the macroscopic friction fluctuation of a breccia particle system: the particle surface friction, system normal stress, and shear velocity. The origins of macroscopic frictional fluctuations in particle systems with various shapes are fundamentally distinct. This study contributes to a better understanding of the causes of particle system fluctuations, and establishes the theoretical foundation for the future development of disaster prevention technology.

Simulation of sound propagation and calculation of its velocity in spherical and superellipsoidal particle systems

Discrete element method is used to simulate sound propagation in spherical and superellipsoidal particle systems and calculate the sound velocities under different boundary and stress conditions. Compressional and shear wave velocities at different axial and confining pressures for a conventional triaxial compressed spherical particle system under cylindrical boundary condition are calculated through time-of-flight method and analyzed using stiffness, effective medium theory (EMT), and granular solid hydrodynamics (GSH) theory. Results obtained through the time-of-flight method for a system under fixed boundary condition are consistent with the existing experimental results. The system stiffness calculated by branch vector and contact force can explain the variation of sound velocity with axial stress and confining pressure. For compressional velocities, the simulation results of spherical particle system at different axial stresses under isotropic compression in radial direction are consistent with the theoretical results provided by EMT and GSH theories. Compared with compressional velocities, shear velocities predicted by EMT are bigger than experiments, and shear modulus of theories improving upon EMT gives velocities in accordance with experiment. Moreover, the sound velocities of spherical and superellipsoidal particle systems are calculated under the same boundary and normal stress conditions to investigate the influence of particle shape on the sound velocity. The difference between compressional wave velocities in spherical and superellipsoidal particle systems is evident and is qualitatively explained from the perspective of anisotropy of contact force distribution in the system. The proposed methods of sound propagation simulation and sound velocity calculation can be used to investigate the elastic wave propagation in particle system, and can obtain the microscopic quantities that are difficult to obtain experimentally and theoretically. They can provide references for the study of EMT and GSH theories and further discuss the influence of shape-induced anisotropy on sound velocity.

Discrete element modeling of 3D irregular concave particles: Transport properties of particle-reinforced composites considering particles and soft interphase effects

Particles of complex morphologies and their surrounding soft interphase are main constituents that play a significant role in the transport properties of particle-reinforced composites (PRCs). It has been a crucial but unresolved issue how to derive the volume fraction of soft interphase around three-dimensional (3D) irregular concave particles, as well as it remains to be virgin to explore the effective transport properties of three-phase PRCs composed of homogeneous matrix, 3D irregular concave particles of a relatively high packing density and their surrounding soft interphase. To this end, this work initially develops a discrete element modeling (DEM) of 3D irregular concave particles with monodispersity in size to generate random dense packing structures, where an innovative mathematical-controllable parameterized method is proposed to devise diverse irregular concave particle shapes. The proposed particle design method is not only universal and controllable to generate a given particle shape, but also can be directly linked with an experimental measurement using digital scanning. In addition, an efficient two-step numerical strategy is presented to check the inter-particle contact detection and collision. Then, the volume fraction of soft interphase around monodisperse concave particles is numerically derived for the first time by using the Monte Carlo random point sampling simulation. The Monte Carlo simulation has good accuracy to obtain the soft interphase volume fraction, which is confirmed by comparing with the theoretical formulae for spherical particle systems. Next, a dual-probability-Brownian motion (DP-BM) scheme along with the level set algorithm is extended to investigate the effective transport properties like thermal conductivity of three-phase PRCs. Comparison against the finite element method (FEM), the proposed DP-BM scheme is more user-friendly and efficient to estimate the effective transport properties of PRCs within an accuracy level. The proposed DP-BM scheme can overcome the two intrinsic limitations of the classical effective medium approximations that one limitation is the ellipsoidal inclusion shape and another is a relative dilute level of inclusion volume fraction. Moreover, the effects of the concave particle shape and packing density, and the interphase dimension on the volume fraction of soft interphase and the effective normalized transport properties of PRCs are evaluated. The results elucidate rigorous component-structure–property relations, which can provide sound guidance for durability evaluation and material design of PRCs.

Traction chain networks: Insights beyond force chain networks for non-spherical particle systems

Force chain networks are generally applied in granular materials to gain insight into inter-particle granular contact. For conservative spherical particle systems, i.e. frictionless and undamped, force chains are information complete due to symmetries resulting from isotropy and constant curvature of a sphere. In fact, for conservative spherical particle systems, given the geometry and material, the force chain network uniquely defines the contact state that includes elastic forces, penetration distance, overlap volume, contact areas and contact pressures in a particle system. This is, however, not the case for conservative non-spherical particle systems. The reason is that a force chain network is not sufficient to uniquely define the contact state in a conservative non-spherical particle system. Additional information is required to define the contact state of non-spherical granular systems. Traction chain networks are proposed to complement force chain networks for the improved quantification of the state of contact of a granular system.

The effects of multiparticle interactions on the aggregation of asphaltenes

In this paper, we analyze aggregation in a systems of spherical primary particles in a liquid solvent with implicitly modeled polymer molecules that are not grafted to the particle surface, but rather are adsorbed by one end; the sorption is too strong for a chain to desorb and diffuse into the solution, but weak enough so that the polymer heads can move along the surface. The potential between the particles includes short-range core attraction and a longer range steric repulsion between the polymer chains. Upon contact, the particles form a permanent bond; the contact area becomes unavailable to the polymers which redistribute along the surface and strengthen the steric repulsion. Thus, the particle-particle interaction depends on the number of bonds each particle has already made. We call this type of multiparticle interactions "neighbor-dependent potentials" and analyze their behavior with Brownian Dynamics simulations, comparing it to that of particles with reversible pairwise potentials. The neighbor-dependent systems agglomerated into stable fractal structures with the dimensions between 1.7 and 2.0 (seemingly diffusion or reaction limited, depending on the parameters) and showed almost no tendency to restructuring of fractal aggregates into droplets, while pairwise interactions with similar parameters showed restructuring into droplets undergoing concurrently to the cluster–cluster aggregation. The neighbor-dependent systems also showed a different, more ramified cluster structure with multiple internal loops. The main limitation of the modeling approach is related to the arbitrary criteria of the bond formation and call for a fully ergodic Monte Carlo modeling of systems with neighbor-dependent interactions.

Modified Equations for Water Flow through Packed Bed for different types of packing systems

Semi-empirical equations for water flow through packed bed have been estimated, for different types of packing systems (mono size spherical particle system, mono size non spherical particle system, binary sized spherical particle system, ternary sized spherical particle system, quaternary sized spherical particle system, quinary sized spherical particle) depending on Buckingham π theorem. The working range of the modified equation is within the fixed region of the fluid flow diagram, i.e., the modified equation can be used for fluid flow up to the fluidization point. The results of all calculations for the modified equations have been compared with many documented experimental literatures. This comparison gave a very good agreement, and has been represented in curves. The results from Ergun equation using similar conditions have been represented in the curves for the sake of comparison.

Direct observation of crystal nucleation and growth in a quasi-two-dimensional nonvibrating granular system.

We study a quasi-two-dimensional macroscopic system of magnetic spherical particles settled on a shallow concave dish under a temporally oscillating magnetic field. The system reaches a stationary state where the energy losses from collisions and friction with the concave dish surface are compensated by the continuous energy input coming from the oscillating magnetic field. Random particle motions show some similarities with the motions of atoms and molecules in a glass or a crystal-forming fluid. Because of the curvature of the surface, particles experience an additional force toward the center of the concave dish. When decreasing the magnetic field, the effective temperature is decreased and diffusive particle motion slows. For slow cooling rates we observe crystallization, where the particles organize into a hexagonal lattice. We study the birth of the crystalline nucleus and the subsequent growth of the crystal. Our observations support nonclassical theories of crystal formation. Initially a dense amorphous aggregate of particles forms, and then in a second stage this aggregate rearranges internally to form the crystalline nucleus. As the aggregate grows, the crystal grows in its interior. After a certain size, all the aggregated particles are part of the crystal and after that crystal growth follows the classical theory for crystal growth.

Lees-Edwards boundary conditions for the multi-sphere discrete element method

A consistent implementation of Lees-Edwards boundary conditions is proposed for the Multi-Sphere Discrete Element Method, which can mitigate various unphysical effects at the bulk and micro-structural levels. These effects include non-linear velocity profiles and inhomogeneous particle distributions, which result in significant errors with respect to pressure and granular temperature. In order to allow for a fair assessment of different implementations, a novel compound sphere particle shape is devised for comparison to reliable benchmark data generated from systems of spherical particles. The Multi-Sphere Discrete Element Method is utilised to examine two implementations of these conditions. The commonly used Naive approach results in the aforementioned unphysical effects, which are numerical artefacts causing deviations from the benchmark results of up to one order of magnitude. Meanwhile, the proposed consistent implementation fulfils the fundamental requirements of Lees-Edwards boundary conditions and produces data which are in excellent agreement with the benchmark results, as well as the available literature. Comparing the aforementioned implementations, general principles are developed for implementing Lees-Edwards boundary conditions for the Multi-Sphere Discrete Element Method.