Chains Of Particles Research Articles

Analysis of dynamic levitation process of the particle chain in a nonlinear standing wave field.

This research delves into the dynamic behavior of acoustic levitation of the particle chain in a nonlinear standing wave field. Experimental acoustic levitation control tests reveal bifurcation and jump phenomena during dynamic adjustments to resonant cavity height. Employing the 10-particle chain experiments and the COMSOL simulation models, the Sine-Gordon 2D vibration model is established to study the dynamic deformation process of the particle chain. The study uncovers the nonlinear interaction of particle lateral vibrations, horizontal acoustic radiation force, and conical wave fields that generate the jumping standing wave field. Notably, the fourth particle acts as a prominent jumping critical point in the secondary standing wave field, facilitating the derivation of the particle chain's nonlinear levitation dynamics. This discovery provides us with a new method to regulate the particle chain system.

Complex Permittivity Spectra of Granular Polymer Composites with Dispersed Ag-Coated Cu Flakes

AbstractConductive particle-containing granular composites with tuneable negative permittivity are being studied to improve the performance of electromagnetic devices, such as shielding materials. In this study, we investigated the relative complex permittivity and electrical conductivity of granular composites of polyphenylene sulfide (PPS) resin and Ag-coated Cu flakes in the radio- to microwave-frequency range and compared them with those of PPS/bare Cu flake composites. Electrical conductivity measurements revealed that the PPS/Ag-coated Cu flake composites have a lower percolation threshold (φc) than the PPS/bare Cu flake composites, whereas the electrical conductivity of the PPS/Ag-coated Cu flake composites in the percolated particle state was higher at the same particle volume fraction. At particle contents above φc, a low-frequency plasmonic state of conduction electrons was achieved in the percolated particle chains in both composites, and negative permittivity spectra were obtained. The percolated PPS/Ag-coated Cu flake composites had a negative permittivity up to a higher frequency than the percolated PPS/bare Cu flake composites. Furthermore, the Drude model was used to analyze the negative permittivity spectra of the composites in the percolated particle state. The plasma frequency of the composites with percolated Ag-coated Cu flakes was higher than that of the composites with percolated bare Cu flakes. Thus, coating Ag on Cu particles improved the conductivity of the composite, leading to negative permittivity up to higher frequencies. This study contributes to the enhancement of the negative permittivity achieved by granular composites, which is useful for microwave technology applications. Graphical Abstract

Study of self-assembly between two magnetic particle chains in magnetorheological fluids

The self-assembly behavior of individual magnetic particles in magnetorheological liquids has been extensively analyzed in previous studies, but the self-assembly behavior between chains of magnetic particles has rarely been investigated. In this paper, the self-assembly mechanism between chains of magnetic particles is investigated using simulation and experimental methods. Firstly, a two-dimensional coupling simulation numerical model of particle-magnetic field-flow field is constructed by analyzing the magnetic force, fluid force and contact interaction force between magnetic particles. The accuracy of the simulation model was verified through experiments. Then the attraction and repulsion dividing line of two magnetic particle chains are analytically calculated by simulation combined with parametric scanning. And analyze the law of the influence of the number of magnetic particles between magnetic particle chains on the attraction and repulsion dividing line. Finally, the different self-assembly behaviors that occur when magnetic particle chains are in different regions of attraction and repulsion between them are experimentally verified. Thus, this study provides new insights into the self-assembly mechanism between chains of magnetic particles in magnetorheological fluids in terms of the effect of the number of magnetic particles on the attraction–repulsion dividing line.

Effect of isotropy and anisotropy: Toward understanding the fracture behavior of magnetoactive elastomers

Magnetoactive elastomers (MAEs) exhibit magneto-mechanical coupling and typically contain micron-sized spherical ferromagnetic particles embedded in an elastomeric matrix. Anisotropic particle arrangement in MAEs, achieved by curing the material in a magnetic field, offers tailored and enhanced magneto-mechanical coupling compared to isotropic configurations. While tunable MAE properties such as the effective modulus and vibrational response have been relatively well studied, a thorough understanding of their fracture mechanisms, particularly in MAEs with microstructural anisotropy or composites with similar structures remains almost completely unexplored. Here, we characterize the fracture mechanisms of anisotropic and isotropic unmagnetized MAEs using experiments and simulations, focusing on the effects of spherical particles in anisotropic chain-like configurations. Specifically, we experimentally measure the fracture toughness of MAEs containing different volume fractions of particles, and with particles arranged both randomly and aligned at 0°, 45°, and 90° to the loading direction. Results show that anisotropic MAEs with particle chains aligned with the load direction can improve fracture toughness by up to almost 600%, whereas isotropic MAEs increase the fracture toughness by only 420%, compared to the pure elastomer. Scanning electron microscopy of the post-fractured surface reveals toughening mechanisms at micro-scale, such as chain waviness, particle agglomeration, and particle distribution. Simulations using a finite element method-based decoupled phase field-cohesive zone model on simplified geometries qualitatively support imaging interpretations. Overall, this work explains how internal geometry, including waviness in particle chains, chain alignment, and particle agglomerations affects fracture of MAEs and generally soft composites with chain-like geometries of spherical particles. These results have engineering applications in improving fracture properties of smart soft composites relevant to soft robotics, tunable vibration absorbers, and noise attenuators.

Particle damping equivalent method based on force chain for high frequency vibration reduction: Mechanism analysis and experimental verification

A particle damping equivalent method based on force chain is newly proposed for simulating the behavior of particle damper (PD) with higher accuracy. Compared with other existing equivalent methods, this method considers the contact between particles and evaluates the particle motion state. Firstly, the particle damping equivalent method based on the theory of force chain and contact model is proposed, and the simulation process of the equivalent method is described. Then, this equivalent method is adopted to simulate the high frequency vibration of pipe installed with PD using SAP2000 software. The simulated vibration response exhibits excellent agreement with experimental results, validating the effectiveness of the proposed equivalent method. Finally, based on the calculation results, it is observed that the particle motion state of the PD in the experiment is quasi-static. This further shows that the particle chain in the damper under high frequency vibration can ignore the wave propagation behavior, which aligns with the assumption of the particle contact model.

Mie Magnetic Structural Colors from Short Chains of TiO2 Nanospheres.

We demonstrate distinctive structural colors within a small footprint by using a short chain of nanospheres. Rather than using high-index materials like Si (n ∼ 4), which ensure strong modal confinement, TiO2 is employed. TiO2 has an intermediate index (n ∼ 2), promoting stronger modal coupling between the magnetic dipoles of each particle. This approach enables selective engineering of the magnetic response and yields larger spectral changes compared to that of Si. Despite the lower refractive index, the absence of absorption in TiO2 also produces higher scattering intensities than Si. We develop a quasistatic analytical model that describes the dipolar modal coupling in a trimer and use it to reveal distinct magnetic field strengths in the outer or central particle depending on the polarization of incident light. These results suggest pathways to manipulate the magnetic field in chains of particles and create vibrant structural colors with simple configurations.

Two-Step Chirality Transfer to Twisted Assemblies: Synergistic Interplay of Chiral and Aggregation Interactions.

Chirality plays a pivotal role in both the origin of life and the self-assembly of materials. However, the governing principles behind chirality transfer in hierarchical self-assembly across multiple length scales remain elusive. Here, we propose a concise and versatile simulation strategy using the patchy particle chain model to investigate the self-assembly of rods interacting through chiral and aggregation interactions. We reveal that chiral interaction possessing an entropic nature, amplifies the fluctuations and twists in the alignment of rods, while aggregation interaction serves as a foundational platform for aggregation and assembly. When both interactions exhibit moderate absolute and relative values, their synergistic interplay facilitates the chirality transfer from rods to assemblies, resulting in the formation of chiral mesoscale ordered structures. Furthermore, we observe a two-step chirality transfer process by monitoring the formation kinetics of the twisted assemblies. This work not only provides a comprehensive insight into chirality transfer mechanisms, but also introduces a versatile mesoscale simulation framework for exploring the role of chirality in hierarchical self-assembly.

An improved YOLOv8-CGA-ASF-DBB method for multi-class wear debris recognition of online visual ferrograph image

Abstract The analysis of wear based on On-Line Visual Ferrograph (OLVF) provides crucial insights for the analysis of wear faults in mechanical equipment.However, online ferrograph analysis has been greatly limited by the low imaging quality and recognition accuracy of particle chains and high hubbles when analyzing lubricant oils in practical applications. To address this issue,this paper proposes an enhanced OLVF wear image detection model based on YOLOv8 and applies it to the multi-class intelligent recognition of ferrograph images .The Cascade Group Attention(CGA) module is introduced enhance the diversity of features and improve computational efficiency. The fusion of attention scale sequence is introduced to achieve precise and rapid recognition of small targets. This Diverse Branch Block(DBB) module is introduced efficiently extracts features without compromising reasoning speed during training. For verification , a test of the bridge transmission box was conducted based on OLVF, and 992 ferrograph images were collected. Experimental results reveal that the improved algorithm achieves an accuracy of 94.53% on the dataset of bridge transmission box ferrograph wear debris images collected through OLVF. This represents a 5.2% increase in recognition accuracy compared to the original algorithm, while maintaining a processing time of only 0.69ms per image. These findings provide compelling evidence for the significant enhancements in both recognition accuracy and processing speed achieved by the improved algorithm, thereby establishing its considerable value for engineering applications.

MultiMatch: geometry-informed colocalization in multi-color super-resolution microscopy

With recent advances in multi-color super-resolution light microscopy, it is possible to simultaneously visualize multiple subunits within biological structures at nanometer resolution. To optimally evaluate and interpret spatial proximity of stainings on such an image, colocalization analysis tools have to be able to integrate prior knowledge on the local geometry of the recorded biological complex. We present MultiMatch to analyze the abundance and location of chain-like particle arrangements in multi-color microscopy based on multi-marginal optimal unbalanced transport methodology. Our object-based colocalization model statistically addresses the effect of incomplete labeling efficiencies enabling inference on existent, but not fully observable particle chains. We showcase that MultiMatch is able to consistently recover existing chain structures in three-color STED images of DNA origami nanorulers and outperforms geometry-uninformed triplet colocalization methods in this task. MultiMatch generalizes to an arbitrary number of color channels and is provided as a user-friendly Python package comprising colocalization visualizations.

High purity H2 resource from methanol steam reforming at low-temperature by spinel CuGa2O4 catalyst for fuel cell

Methanol steam reforming (MSR) is an effective way to provide high purity hydrogen for PEMFCs, however the main challenge is the toxic effect of CO. In this study, CuGa2O4 spinel catalyst was applied first for MSR at low temperature. The properties of catalysts were characterized by various techniques, the MSR catalytic performance was also studied in deeply. The surface of the catalyst is composed of particle chains that are interconnected, forming high-volume pores that increase the specific surface area. The catalyst also has a rich porous structure, exposing more active sites. Furthermore, the presence of oxygen vacancies facilitates the adsorption of reactive oxygen species, reducing CO generation. A possible pathway for methanol dehydrogenation has been determined using DFT calculations. The relatively low overall energy barrier on the catalyst surface facilitates methanol activation. Among the steps, formaldehyde dehydrogenation is the rate-determining step in the methanol dehydrogenation process. The CuGa2O4 catalyst exhibits good gas selectivity, with a hydrogen selectivity of 98 % and CO selectivity of 0. and no deactivation occurred within 50 h, demonstrating outstanding durability. These features allow it to serve as an efficient catalyst for MSR online hydrogen production and direct supply to PEMFCs.

Tagged particle behavior in a harmonic chain of direction-reversing active Brownian particles

Abstract We study the tagged particle dynamics in a harmonic chain of direction-reversing active Brownian particles, with the spring constant k, rotation diffusion coefficient D R , and directional reversal rate γ. We exactly compute the tagged particle position variance for quenched and annealed initial orientations of the particles. For well-separated time-scales, k − 1 , D R − 1 and γ −1, the strength of the spring constant k relative to D R and γ gives rise to different coupling limits, and for each coupling limit there are short, intermediate, and long-time regimes. In the thermodynamic limit, we show that, to the leading order, the tagged particle variance exhibits an algebraic growth t ν , where the value of the exponent ν depends on the specific regime. For a quenched initial orientation, the exponent ν crosses over from 3 to 1 / 2 , via intermediate values 5 / 2 or 1, depending on the specific coupling limits. However, for the annealed initial orientation, ν crosses over from 2 to 1 / 2 via an intermediate value 3 / 2 or 1 for the strong coupling limit and the weak coupling limit, respectively. An additional time-scale t N = N 2 / k emerges for a system with a finite number of oscillators N. We show that the behavior of the tagged particle variance across tN can be expressed in terms of a crossover scaling function, which we find exactly. Moreover, we study the velocity autocorrelation. Finally, we characterize the stationary state behavior of the separation between two consecutive particles by calculating the corresponding spatio-temporal correlation function.

A novel “S” chain structure mechanism model of magneto-rheological elastomer

Mechanism models based on chain-like structures are often used to characterize the morphology of magneto-rheological elastomer (MRE) and provide theoretical guidance for MRE preparation. However, widely used shear and tension mechanism models based on oblique straight chain or bent-chain structures have the limitation of insufficient accuracy in characterization, mainly because the internal particle chains of anisotropic MRE are not simple oblique straight or bent from scanning electron microscope (SEM) results. Therefore, the particle chain formation and particle interaction mechanism within MRE are revealed firstly. The theoretical results shows that particles tend to form S-like chain structures due to complex attraction and extrusion. On this basis, a novel “S” chain mechanism model is proposed, which is confirmed to have higher accuracy than the ideal shear model and tension model by comparing with the experimental results. The main reason is that the “S” chain mechanism model has realized the unification of shear, compressive, or tension mode, and integrates the fully coupled magnetic field, distribution parameters and interface stretching. The “S” chain mechanism model also takes into account the radius and volume fraction of the particles in MRE preparation, which makes it a more accurate guide to subsequent preparation.

The Determining Influence of the Phase Composition on the Mechanical Properties of Titanium-Iron Alloys after High-Pressure Torsion.

Three titanium alloys with 0.5, 6, and 9 wt.% iron were investigated, and the samples were pre-annealed in three different regions of the Ti-Fe phase diagram, namely β, α+β, and α+FeTi. After annealing, five samples of different phases and structural compositions were studied. They were then subjected to the high-pressure torsion (HPT). The microstructure of the samples before and after HPT treatment was studied using transmission and scanning electron microscopy. The microstructure of the samples obtained during heat treatment before HPT treatment had a fundamental effect on the microstructure after HPT. Grain boundary layers and chains of particles formed during the annealing process made it difficult to mix the material during HPT, which led to the formation of areas with non-uniform mixing of components. Thus, the grain boundary layers of the α-phase formed in the Ti-6wt % Fe alloy after annealing at 670 °C significantly decreased the mixing of the components during HPT. Despite the fact that the microstructure and phase composition of Ti-6wt % Fe alloys pre-annealed in three different regions of the Ti-Fe phase diagram had significant differences, after HPT treatment, the phase compositions of the studied samples were quite similar. Moreover, the measured micro- and nanohardness as well as the Young's modulus of Ti-6wt % Fe alloy had similar values. It was shown that the microhardness of the studied samples increased with the iron content. The values of nanohardness and Young's modulus correlated well with the fractions of β- and ω-phases in the studied alloys.

Artificial intelligence-motivated in-situ imaging for visualization investigation of submicron particles deposition in electric-flow coupled fields

This study delves into the intricate deposition dynamics of submicron particles within electric-flow coupled fields, underscoring the unique challenges posed by their minuscule size, aggregation tendencies, and biological reactivity. Employing an operando investigation system that synergizes microfluidic technology with advanced micro-visualization techniques within a lab-on-a-chip framework, it enables a meticulous examination of the dynamic deposition phenomena. The incorporation of object detection and deep learning methodologies in image processing streamlines the automatic identification and swift extraction of crucial data, effectively tackling the complexities associated with capturing and mitigating these hazardous particles. Combined with the analysis of the growth behavior of particle chain under different applied voltage, it established that a linear relationship exists between the applied voltage and θ.And there is a negative correlation between the average particle chain length and electric field strength at the collection electrode surface (4.2E5 V·m–1 to 1.6E6 V·m–1). The morphology of the deposited particle agglomerate at different electric field strength is proposed: dendritic agglomerate, long chain agglomerate and short chain agglomerate.

Hydrodynamic mechanism for dynamical structure formation of a system of rotating particles

Based on the hydrodynamic mechanism, which takes into account the interaction of all particles, a numerical simulation of the formation of a dynamical structure in a viscous fluid was carried out. This structure is a result of the collective dynamics of rotating particles in the fluid. It is supposed that the particles have a magnetic moment and are driven into rotation by an external variable uniform magnetic field. The results of numerical modeling of collective dynamics are presented for three initial structures that can be formed by interacting dipole particles in the absence of an external magnetic field. Such equilibrium structures are a straight chain, a closed chain, and a periodic structure in the form of a flat system of particle chains. The rotation of particles sets the surrounding fluid in motion, whose flow creates hydrodynamic forces and moments that move the particles. The collective dynamics of a system of rotating particles leads to the formation of a new dynamical structure from the original one, and this new structure has its own characteristic features for each case considered. A qualitative comparison of the results of the dynamics for a particles’ system set in motion due to the action of an external moment or an external force is carried out. The proposed hydrodynamic mechanism for the formation of a dynamical structure as a result of the collective dynamics of a rotating particles’ system can be used to control structure formation in a liquid-particle system.

Experimental study and mechanism analysis on the effect of pre-curing time on the microstructure and mechanical properties of magnetorheological elastomers under compression

The effects of the pre-curing time before exposing the carbonyl iron particles (CIPs) filled liquid polydimethylsiloxane (PDMS) mixture to a preparatory magnetic field on the magnetorheological (MR) effects of the magnetorheological elastomers (MREs) were experimentally and theoretically investigated. The anisotropic MRE samples with different pre-curing time were firstly fabricated and their compressive MR effects were tested. The results showed that the longer pre-curing time induces the shorter and more irregular particle chains formed in the MREs, and the sample pre-cured for 20 min showed the maximum MR effect. Then based on the rheological characterization, a rheological model was proposed to predict the rheological property evolution of CIPs/PDMS mixture with respect to the pre-curing time, and a modified three-dimensional (3D) particle dynamics (PD) model was developed to simulate the particle structure evolution in the MRE mixtures under a preparatory magnetic field. The simulation results showed that short chains were first formed owing to the magnetic attraction between the adjacent particles. Then these short chains approached each other to form long chains and even thick chain-like clusters. The later process can be restrained by increasing the pre-curing time, thus more short and incompact particle chains are formed in the MREs. Lastly, simplified microstructure models representing the wavy chains were used to explore the effect of particle arrangement on the MR effect of the MREs under compression. It is found that the wavy chains with incompactly packed particles are beneficial for improving the MR effect owing to the strong transverse magnetic attraction between the neighboring particles. This work demonstrates that PD simulation is an efficiency method to predict the particle arrangement evolution in the MRE mixture, and the possibility to tailoring the microstructures of the MREs by adjusting the viscosity of MRE mixtures to improve their MR effects, while keeping a high zero-field modulus simultaneously.

Vacancy formation in a 1D chain of dust particles in a DC discharge

The paper presents the first experimental observation of an atypical phenomena during self-organization of dust particles into a one-dimensional chain structure levitated vertically in the plasma of a DC glow discharge. Using a laser, the third (middle) dust particle was removed from the chain of five particles so that the positions of the remaining particles did not significantly change, and a vacancy occurred in the place of the removed particle. This state of the chain turned out to be very stable, which is confirmed by the observation of the subsequent exchange of places of the fourth and the fifth particles of the chain upon the action of the laser on the forth particle. After the exchange process, vertical positions of all particles (first, second, fourth and fifth) in the chain remained almost the same as before the exchange, and the vacancy at the position of the third particle was preserved. The experimental data and the video record of the observed phenomena as well as the estimates of the plasma parameters are presented. An assumption has been made about the mechanism of the discovered phenomena that at present discharge conditions both the vacancy formation and the dust particles positions exchange are possible due to a strong ion wakes which are formed behind the upstream dust particles of the chain.

Parameters of dust particle chains levitated vertically in a gas discharge plasma

The structural parameters of the dust particle chains suspended vertically in the electric field of a gas discharge are studied here. The investigations are performed by a numerical multi-block model based on a mean field approximation. The model describes the movement of ions and dust particles under the action of an external electric field, the electric field (Coulomb) of each charged dust particle, and the field of bulk plasma charge (ions and electrons) that screens the charges of dust particles. The gravity and the ion drag forces acting on the dust particles are also taken into account. Self-consistent chain parameters are calculated and compared for different number (1, 3, 5, and 7) and two different diameters (3.4 and 8.94 mcm) of dust particles in the chains. It is shown that an “ion wake” is formed behind the dust structures, and it grows with the number of dust particles and their size. With an increase in the number of dust particles in the chain, the charge of the first (top) dust particle increases. In the case of small dust particles, with an addition of new particles into the chain, the centers of the chains almost remain at the position of a single particle in the vertical direction. The chains of big dust particles move as a whole down in the direction of gravity with an increase in the number of particles.

Model reduction for an internally damped n-particle chain in a potential well under polyharmonic excitation

The study focuses on the model reduction of an internally damped chain of particles confined within a weakening potential well subjected to polyharmonic excitation to investigate the chain’s escape dynamics. The chain features strong linear coupling between particles and nonnegligible viscous damping forces arising from their relative motion. The potential well is modeled to have no energy dissipation, which means that damping arises solely from the internal interactions among particles and not from their motion through a resisting medium. Polyharmonic excitation frequencies are chosen to excite both the center of mass of the chain and at least one of the internally resonant frequencies, which are significantly higher than the linearized angular eigenfrequency of the center of mass within the well. The relative motion of the particles quickly reaches a steady state because of the non-small internal damping, allowing for the derivation of an efficient force field for the center of mass. Eliminating fast dynamics reduces the system’s degrees of freedom to one, employing a probabilistic approach based on the relative motion’s probability density function. The reduced 1 DoF model is appropriate for further investigation using various methods established in the literature.

Molecular heat transport across a time-periodic temperature gradient.

The time-periodic modulation of a temperature gradient can alter the heat transport properties of a physical system. Oscillating thermal gradients give rise to behaviors such as modified thermal conductivity and controllable time-delayed energy storage that are not present in a system with static temperatures. Here, we examine how the heat transport properties of a molecular lattice model are affected by an oscillating temperature gradient. We use analytical analysis and molecular dynamics simulations to investigate the vibrational heat flow in a molecular lattice system consisting of a chain of particles connected to two heat baths at different temperatures, where the temperature difference between baths is oscillating in time. We derive expressions for heat currents in this system using a stochastic energetics framework and a nonequilibrium Green's function approach that is modified to treat the nonstationary average energy fluxes. We find that emergent energy storage, energy release, and thermal conductance mechanisms induced by the temperature oscillations can be controlled by varying the frequency, waveform, and amplitude of the oscillating gradient. The developed theoretical approach provides a general framework to describe how vibrational heat transmission through a molecular lattice is affected by temperature gradient oscillations.