Neighboring Particles Research Articles

Construction of fractional granular model and bright, dark, lump, breather types soliton solutions using Hirota bilinear method

The present article designs the granular metamaterials considering the granular structures of discrete particles which are different from elastic metamaterials consisting of continuous media. In granular metamaterials, the wave propagates through contact with neighboring particles. To identify the propagating properties of wave quantities in the rough granular medium the fractional granular equation is formulated directly in a pre-compressed spherical chain adopting Hertz law and long wave approximation theory. Using phase and group velocities, Caputo fractional derivatives are used to illustrate normal and anomalous dispersion wave dependence. To demonstrate in depth the dynamical behavior of the wave profile, various types of complex solutions like multi-shock, multi-solitons, lump, and breather solutions of the one-dimensional time fractional granular equations are explored employing Hirota’s bilinear approach. Finally, the more complicated hybrid solutions such as kink with the lump, soliton with the lump, etc. are exhibited from numerical understanding. The numerical graphs and figures demonstrate the crucial role of the order of derivative (roughness parameter) in the formation of different types of soliton solutions.

Nb3Al paste for superconducting connections

We achieved a superconducting transition temperature of 9 K in a superconducting paste prepared using Nb3Al particles. The paste was synthesized by a simple traditional method often used to prepare Ag paste. Subsequently, the paste was screen printed on a solid substrate and thermally cured under optimum conditions to form a single-phase film with a thickness of 150 µm. The single-phase nature of the Nb3Al film was confirmed by X-ray diffraction, and the close contact of each Nb3Al particle with its neighboring particles was confirmed by cross-sectional scanning electron microscopy. The resistivity of this thick Nb3Al film is zero at temperatures lower than 9 K, indicating that this film is superconducting at cryogenic temperatures. Furthermore, NbTi-thin-film-pad/Nb3Al/NbTi-thin-film-pad connections were fabricated by vapor-phase growth and screen printing. The temperature dependence of the connection resistivity showed two superconducting transitions: a gradual decrease in resistivity from 13 K to 9 K, attributed to Nb3Al, and a sharp decrease at 6.2 K, attributed to the superconducting transition of the NbTi thin film. These results indicated that the Nb3Al superconducting paste is a candidate for achieving superconducting-thin-film-based device-to-device integration technology comprising three elements, namely superconducting wires, a superconducting crossover, and a superconducting contact.

A novel Eulerian SPH shallow water model for 2D overland flow simulations

A 2D Eulerian meshless shallow water model based on smoothed particle hydrodynamics (SPH) is proposed to study overland flow. Rain on a dry bed to generate a runoff flow is one common hydraulic phenomenon. However, it is difficult for existing Lagrangian SPH shallow water models to present the flow because no computational particle exists on a dry bed. To overcome this difficulty, the Eulerian form of the 2D shallow water equations is used to describe flow behavior in the proposed model. An HLLC approximate Riemann solver is applied to calculate fluxes between two neighboring particles to smear out the instabilities caused by the discretization of the nonlinear convective term and the discontinuity of wet-dry beds. Additionally, we use a surface reconstruction method (SRM) to ensure that the proposed model has well-balanced and positivity-preserving properties. Bed friction and infiltration effects are also analytically considered. Eight case studies involving various overland flows with wet-dry transitions, rainfall, infiltration, bed friction and complex topography are adopted to test the proposed model capacity. The first-order convergence rate is obtained in the convergence analysis. Against the exact and measured results, in the analytical case studies, the relative root-mean-square errors of depth and velocity are approximately 0.02% to 0.3% and 1.3% to 1.7%, respectively. In the experimental case studies, the relative root-mean-square errors of depth and discharge (velocity) are approximately 3.8% and 1.2% to 6.1%, respectively. The good agreement demonstrates between the results shows the reliability of the proposed 2D Eulerian SPH shallow water model for real-world overland flows.

Modeling Thermoelasticity of HCP single crystals using a nonlocal discrete approach

This paper presents full-field modeling Thermoelasticity of hexagonal close-packed (HCP) single crystals using reformulations of conventional continuum theories based on a novel nonlocal lattice particle method (LPM). In LPM, grain domain is modeled as an assembly of regularly packed material particles according to the atomic lattice. The interaction between material particles is nonlocal, e.g., for mechanical problems, a material particle interacts with neighboring material particles up to certain distance via bonds and the interaction between two material particles depends on the deformation states of not only the two material particles but also all their neighbors. To determine the nonlocal interaction between material particles, a top-down approach based on the classical continuum theories is developed. Equivalency assumptions of energy, heat transfer rate and thermal strain between LPM and its continuum counterpart are made to consistently determine the material particle interaction for mechanical, thermal, and thermal–mechanical coupling problems, respectively. To capture the crystallographic orientation, a lattice rotation scheme that is equivalent to the coordinate transformation used in the classical continuum theories is adopted. Numerical studies regarding validity of the proposed nonlocal discrete reformulation and accuracy of the model prediction are conducted for all three types of analysis. Good agreements are observed between the results from the developed reformulations and the conventional continuum theories.

Modeling of heating and cooling behaviors of laminated glass facades exposed to fire with three-dimensional flexibilities

To develop a precise and efficient computer model for predicting the heating and cooling behaviors of laminated glass facades exposed to fire, there is an urgent need to reduce the huge computational requirements associated with simulating heat transfer in layered structures that feature a down-flowing water film. We overcome this challenge by proposing an efficient three-dimensional finite difference method (3DFDM) which has high numerical stability when solving heat transfer equations with water film and air convection. To capture the moving particles of the water film, we developed a unique computational algorithm for particle labeling, which has two significant advantages: (1) it eliminates the time-consuming process of searching for neighboring particles in conventional meshfree methods, and (2) it ensures that every main particle interacts only with limited neighboring particles without utilizing any weights, thus significantly reducing the computational effort. We validated our 3DFDM through experiments in heating and cooling scenarios and compared its thermal results with those obtained from commercial packages to demonstrate its high efficiency and accuracy. Furthermore, we examined the feasibility of our model in evaluating the effects of thickness of the interlayer and water film release time on the cooling behavior of laminated glass during a fire.

Novel soft magnetic composite with insulating layers formed in situ from hydrothermal carbon nanospheres and boric acid

This work addresses a method for obtaining a novel double-layered soft magnetic composite (SMC) by using carbon nanospheres and boric acid as precursors for a post-compaction formation of the insulating coatings on the surface of iron particles. Through the material’s heat treatment, the hydrothermal carbon nanospheres release oxygen groups that react with the metallic iron surface, generating a thin iron oxide layer. Additionally, the boric acid decomposes into glassy boron oxide (B2O3), which spreads over the iron oxide coating, hence improving the electrical insulation among the neighbor particles. The selected compounds and production method allowed for a synergetic mechanism that led to a reduction of 42% on the dynamic losses of the double-layered SMC when compared to the single-layered ones. Furthermore, the effects of the mean size and the concentration of carbon nanospheres on the magnetic behavior of the double-layered SMC showed that an optimization of the system can be achieved when using smaller carbon nanospheres providing the concentration used is high enough to guarantee the covering of the iron particles.

Investigations on a high order SPH scheme using WENO reconstruction

Theoretically, a 2nd order convergence can be reached with the Smoothed Particle Hydrodynamics (SPH) method. However, depending on the spatial disorder of particles, the order of convergence observed in practice can be lower than one. In this paper, a methodology is proposed for the reconstruction of high order numerical fluxes in Riemann-SPH formulations for weakly-compressible flows, so as to increase the global order of convergence of the scheme. This methodology is based on the use of one-dimensional Weighted Essentially Non-Oscillatory (WENO) reconstructions applied at each pair of interacting particles, and each 1D WENO stencil is completed using Moving-Least-Squares (MLS) reconstructions. It is shown that a 6th order convergence can be reached with the proposed SPH-WENO scheme. The gain in accuracy and convergence properties of this scheme is shown and discussed through its application to various one-dimensional and two-dimensional test cases. In particular, the influence of the number of neighbor particles and of the spatial particle disorder is studied. Finally, it is shown that the proposed high-order SPH scheme provides a better accuracy to CPU time ratio than usual Riemann-SPH schemes. The treatment of boundary conditions on rigid walls with the proposed scheme is also discussed.

Molecular cluster analysis using local order parameters selected by machine learning.

Accurately extracting local molecular structures is essential for understanding the mechanisms of phase and structural transitions. A promising method to characterize the local molecular structure is defining the value of the local order parameter (LOP) for each particle. This work develops the Molecular Assembly structure Learning package for Identifying Order parameters (MALIO), a machine learning package that can propose an optimal (set of) LOP(s) quickly and automatically for a huge number of LOP species and various methods of selecting neighboring particles for the calculation. We applied this package to distinguish between the nematic and smectic phases of uniaxial liquid crystal molecules, and selected candidate LOPs that could be used to precisely observe the nematic-smectic phase transition. The LOP candidates were used to observe the nucleation and subsequent percolation transition, and the effect of the choice of LOP species and neighboring particles on the statistics of local molecular structures (clusters) was examined. The procedure revealed the time evolution of the number of clusters and the dependence of the percolation curve on the number of neighboring particles for each LOP species. The LOP species with the lowest dependence on the number of neighboring particles was the best-performing LOP species in the MALIO screening strategy. These results not only show that machine learning can powerfully screen a huge number of LOP species and suggest only a few promising candidates, but also indicate that MALIO can select the best LOP species.

Modeling the viscoelastic relaxation dynamics of soft particles via molecular dynamics simulation-informed multi-dimensional transition-state theory.

Viscoelastic soft colloidal particles have been widely explored in mechanical, chemical, pharmaceutical and other engineering applications due to their unique combination of viscosity and elasticity. The characteristic viscoelastic relaxation time shows an Arrhenius-type (or super-Arrhenius due to temperature-dependent transition attempts) thermally-activated behavior, but a holistic explanation from the relevant transition-state theory remains elusive. In this paper, the viscoelastic relaxation times of Lennard-Jones soft colloidal particle systems, including a single particle type system and a binary particle mixture based on the Kob-Andersen model, are determined using molecular dynamics (MD) simulations as the benchmark. First, the particle systems show a non-Maxwellian behavior after comparing the MD-predicted viscoelastic relaxation time and dynamic moduli (storage and loss modulus) to the classic Maxwell viscoelastic model and the recent particle local connectivity theory. Surprisingly, neither the Maxwell relaxation time τMaxwell (obtained from the static shear viscosity η and the high-frequency shear modulus G∞) nor the particle local connectivity lifetime τLC can capture the super-Arrhenius temperature-dependent behavior in the MD-predicted relaxation time τMD. Then, the particle dissociation and association transition kinetics, fractal dimensions of the particle systems, and neighbor particle structure (obtained from the radial distribution functions) are shown to collectively determine the viscoelastic relaxation time. These factors are embedded into a new multi-dimensional transition kinetics model to directly estimate the viscoelastic relaxation time τModel, which is found to agree with the MD-predicted τMD remarkably well. This work highlights the microscopic origin of viscoelastic relaxation dynamics of soft colloidal particles, and theoretically connects rheological dynamics and transition kinetics in soft matters.

A Modified Particle Swarm Optimization Algorithm for Power Sharing and Transient Response Improvement of a Grid-Tied Solar PV Based A.C. Microgrid

The increasing penetration of Distributed Generators (D.G.) into the existing power system has brought some real challenges regarding the transient response of electrical systems. The injection of D.G.s and abrupt load changes may cause massive power, current, and voltage overshoots/undershoots, which consequently affects the equilibrium of the existing power system and deteriorate the performance of the connected electrical appliances. A robust and intelligent control strategy is of utmost importance to cope with these issues and enhance the penetration level of D.G.s into the existing power system. This paper presents a Modified Particle Swarm Optimization (MPSO) algorithm-based intelligent controller for attaining a desired power-sharing ratio between the M.G. and the main grid with an optimal transient response in a grid-tied Microgrid (M.G.) system. The proposed MPSO algorithm includes an additional parameter named best neighbor particles (rbest) in the velocity updating equation to convey additional information to every individual particle about all its neighbor particles, consequently leading to the increased exploration capability of the algorithm. The MPSO algorithm optimizes P.I. parameters for transient and steady-state response improvement of the studied M.G. system. The main dynamic response evaluation parameters are the overshoot and settling time for active and reactive power during the D.G. connection and load change. Furthermore, the performance of the proposed controller is compared with the PI-PSO-based MG controller, which validates the effectiveness of the proposed M.G. control scheme in maintaining the required active and reactive power under different operating conditions with minimum possible overshoot and settling time.

Light scattering by media consisting of Maxwell 3-foci concave particles in the geometrical optics approximation

We study light scattering by non-spherical Maxwell particles and media consisting of them using computer simulations. The particle shapes are defined by a generalization of the concept 3-foci ellipses introduced by J. C. Maxwell. We modify them for the 3-D case by replacing the distances between the foci and current points on the ellipsoid surface by their logarithms. This makes it possible to describe 3-D ellipsoids that have partially concave surfaces. We carry out simulations within the framework of geometrical optics based on reflection and refraction of 108 rays and calculate phase curves of the nonzero elements of the Mueller matrix. This enables us to clarify the origin of the characteristics of the phase curves, i.e., which scattering order is responsible for the curve features. It is shown that equality M12 = M21 and M34 = –M43 that are valid for isolated particles are broken by the interactions with neighboring particles. It is also shown that the opposition effect of such particulate surfaces is mainly formed by components having one or more internal reflections within particles.

Particle Merging-and-Splitting.

Robustly handling collisions between individual particles in a large particle-based simulation has been a challenging problem. We introduce particle merging-and-splitting, a simple scheme for robustly handling collisions between particles that prevents inter-penetrations of separate objects without introducing numerical instabilities. This scheme merges colliding particles at the beginning of the time-step and then splits them at the end of the time-step. Thus, collisions last for the duration of a time-step, allowing neighboring particles of the colliding particles to influence each other. We show that our merging-and-splitting method is effective in robustly handling collisions and avoiding penetrations in particle-based simulations. We also show how our merging-and-splitting approach can be used for coupling different simulation systems using different and otherwise incompatible integrators. We present simulation tests involving complex solid-fluid interactions, including solid fractures generated by fluid interactions.

Deep learning for drag force modelling in dilute, poly-dispersed particle-laden flows with irregular-shaped particles

This study applies machine learning-based approaches to develop a drag force model for irregular-shaped particles in incompressible flows. The particle-laden flows are studied through an in-house particle-resolved direct numerical simulation (PR-DNS) at low-intermediate Reynolds numbers (Re). We utilize the PR-DNS to obtain drag force coefficients and flow fields of single particles. A variational auto-encoder model is used to obtain latent vectors to represent the geometrical features of the particles, and artificial neural networks (ANN) are developed to predict drag force coefficients and flow fields of the single particles. This study applies a pairwise interaction extended point-particle (PIEP) model to obtain the coefficients assuming the flow fields of neighboring particles can be linearly superposed. The PIEP method shows significant improvement on prediction for a few neighbored particles. In addition, the results reveal R2 scores of 0.56-0.62 and errors of 9.1-10.0 % for the dilute, polydispersed systems with a volume fraction of 0.5 %.

Magnetic relaxation of a system of interacting magnetic nanoparticles at finite temperature

We investigate the magnetic relaxation of a system of interacting single-domain magnetic nanoparticles, where the uniaxial energy density depends on temperature. Particles of different sizes are placed in random positions along a linear chain. For each value of temperature, the stochastic Landau–Lifshitz–Gilbert equation is numerically integrated. Applying an appropriate scaling function we determine the magnetic relaxation as a function of time and temperature as well as the energy barrier distribution of the system as a function of the mean distance between neighbor particles. We show that the typical energy barrier is not a monotonic function of the dipolar coupling. It decreases with the separation between particles until it reaches a minimum. For weaker dipolar interactions, the antiferromagnetic part could be responsible for enhancing the local uniaxial energy barriers. The decrease of the energy barrier for small values of the dipolar coupling was seen experimentally for the magnetoferritin nanoparticle.

Regioisomeric Giant Triblock Molecules: Role of the Linker.

In this study, polyhedral oligomeric silsesquioxane (POSS) based giant triblock molecules with precisely defined regio-configuration are modularly prepared through highly efficient coupling reactions. The length of the linker connecting neighboring nanoparticles is elaborately designed to regulate the geometric constraints. The triblock molecules adopt a folded packing during phase separation, and the regio-configuration imparts direct influence on the self-assembly behaviors. The ortho-isomers form periodic structures with a larger domain size, larger interfacial curvature, and enhanced phase stability. The regio-effect is closely related to the length and symmetry of the linker. As the linker extends, the neighboring particles gradually decouple, and the regio-effect diminishes. The symmetry of the linker shows an even more profound impact. This work quantitatively scrutinized the role of the linker, opening an avenue for engineering the assembled structures with molecular precision.

Discretization Corrected Particle Strength Exchange for Steady State Linear Elasticity

Discretization corrected particle strength exchange (DC PSE) is a particle based spatial differential operator designed to solve meshless continuum mechanics problems. DC PSE is a spatial gradient operator that can discretize a computational domain with randomly distributed particles, provided that each particle has enough neighboring particles. In contrast, conventional methods such as the standard finite difference method require the computational domain to be discretized into a Cartesian grid. In linear elasticity simulations, especially steady state cases, this domain is mostly discretized using mesh-based methods such as finite element. However, while particle methods such as smoothed particle hydrodynamics (SPH) have been widely applied to solve dynamic elasticity problems, they have rarely been used in steady state simulations. In this study, a DC PSE operator was used to solve steady linear elasticity problems in a two-dimensional domain. The result of the DC PSE numerical simulation was compared to numerical results, empirical formula results, and results from conventional commercial finite element software, respectively.

Improved model of lattice gas in the adsorption of carbon monoxide and oxygen

The adsorption and subsequent oxidation of carbon monoxide (CO) on a platinum (Pt) surface has been studied using computational methods. The Monte Carlo method is used to this end through the lattice model. This study focuses on the improvement of this first theoretical model (ZGB) proposed for the oxidation of CO. In this work, four different models are revised in detail with the objective of establishing a comparison between the obtained results on the oxidation of CO on the Pt with an orientation (111) surface. The variance between the models lies on the nature of the sticking coefficient of the CO and oxygen (O2) molecules on Pt (111). This adsorption depends on the initial concentration of CO in the gas phase and the number of vacant sites on the platinum surface. The results obtained in these simulations show that the first model, the ZGB model, differs considerably from the other models, and thus the results with the second and third model have a better adjustment to the adsorption of the CO and O2 molecules, since they take into account the gas concentration, the sticking coefficient and the interaction with the neighboring particles. In this sense, the oxidation reaction occurs in a wider theoretical range around 0.5 mole fraction of CO and 0.2 mole fraction of O atomic, and the poisoning of the platinum catalytic surface can be inhibited if the concentration of carbon monoxide is included as a control parameter.

(Invited) Tracking Metal Electrodeposition Dynamics from Nucleation and Growth of a Single Atom to a Crystalline Nanoparticle

In electrodeposition the key challenge is to obtain better control over nanostructure morphology. Currently, a lack of understanding exists concerning the initial stages of nucleation and growth, which ultimately impact the physicochemical properties of the resulting entities. Using identical location scanning transmission electron microscopy (STEM), with boron-doped diamond (BDD) serving as both an electron-transparent TEM substrate and electrode, we follow this process, from the formation of an individual metal atom through to a crystalline metal nanoparticle, under potential pulsed conditions. In doing so, we reveal the importance of electrochemically driven atom transport, atom cluster formation, cluster progression to a nanoparticle, and the mechanism by which neighboring particles interact during growth. Such information will help formulate improved nucleation and growth models and promote wider uptake of electrodeposited structures in a wide range of societally important applications. This type of measurement is possible in the TEM because the BDD possesses inherent stability, has an extremely high thermal conductivity, is electron beam transparent, is free from contamination, and is robust enough for multiple deposition and imaging cycles. Moreover, the platform can be operated under conditions such that we have confidence that the dynamic atom events we image are truly due to electrochemically driven deposition and no other factors, such as electron-beam-induced movement. Figure 1

An Interactively Corrected Smoothed Particle Hydrodynamics (IC‐SPH) for Simulating Solute Transport in a Nonuniform Velocity Field

AbstractThe Smoothed Particle Hydrodynamics (SPH) method is a Lagrangian approach that has been widely used to eliminate numerical dispersion for solving advection‐dispersion equation (ADE) of groundwater solute transport under advection‐dominated situations. It has been found that accuracy of SPH results is severely deteriorated, when particles are irregularly distributed in a model domain with heterogeneous hydraulic conductivity. To resolve this problem, we developed a new approach called Interactively Corrected SPH (IC‐SPH), which is an improved version of the Corrected SPH (C‐SPH) method. IC‐SPH uses an interactively corrected kernel gradient to construct concentration gradients used to solve ADE. This correction is made for each particle by using not only the particle's neighbor particles within the particle's support domain but also the particles within each neighbor particle's support domain. We evaluated IC‐SPH performance in two numerical studies. One considers diffusive transport with an analytical solution, and the other considers advection‐dispersion transport in a heterogeneous field of hydraulic conductivity. For each numerical study, several numerical experiments were conducted using multiple sets of irregularly distributed particles with different levels of particle irregularity. The numerical experiments indicate that, while IC‐SPH is more computationally expensive than SPH and C‐SPH, IC‐SPH produces more accurate ADE solutions, and converges faster to the analytical solution. IC‐SPH is mathematically general, and can be applied to a wide range of problems that require solving ADE.

Solution to the two-body Smoluchowski equation with shear flow for charge-stabilized colloids at low to moderate Péclet numbers

We developed an analytical theoretical method to determine the microscopical structure of weakly to moderately sheared colloidal suspensions in dilute conditions. The microstructure is described by the static structure factor, obtained by solving the stationary two-body Smoluchowski advection-diffusion equation. The singularly perturbed PDE problem is solved by performing an angular averaging over the extensional and compressing sectors and by the rigorous application of boundary-layer theory (intermediate asymptotics). This allows us to expand the solution to a higher order in P\'eclet with respect to previous methods. The scheme is independent of the type of interaction potential. We apply it to the example of charge-stabilized colloidal particles interacting via the repulsive Yukawa potential and study the distortion of the structure factor. It is predicted that the distortion is larger at small wavevectors $k$ and its dependence on $Pe$ is a simple power law. At increasing $Pe$, the main peak of the structure factor displays a broadening and shift towards lower $k$ in the extensional sectors, which indicates shear-induced spreading out of particle correlations and neighbor particles locally being dragged away from the reference one. In the compressing sectors, instead, a narrowing and shift towards high $k$ is predicted, reflecting shear-induced ordering near contact and concomitant depletion in the medium-range. An overall narrowing of the peak is also predicted for the structure factor averaged over the whole solid angle. Calculations are also performed for hard spheres, showing good overall agreement with experimental data. It is also shown that the shear-induced structure factor distortion is orders of magnitude larger for the Yukawa repulsion than for the hard spheres.