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At least 19 records

Anisotropic single-particle dissipative particle dynamics model

We have developed a new single-particle dissipative particle dynamics (DPD) model for anisotropic particles with different shapes, e.g., prolate or oblate spheroids. In particular, the conservative and dissipative interactions between anisotropic single DPD particles are formulated using a linear mapping from the isotropic model of spherical particles. The proper mapping operator is constructed between each interacting pair of particles at every time step. Correspondingly, the random forces are properly formulated to satisfy the fluctuation-dissipation theorem (FDT). Notably, the model exactly conserves both linear and angular momentum. We demonstrate the proposed model's accuracy and efficiency by applying it for modeling colloidal ellipsoids. Specifically, we show it efficiently captures the static properties of suspensions of colloidal ellipsoids. The isotropic-nematic transition in an ellipsoidal suspension is reproduced by increasing its volume fraction or the aspect ratio of ellipsoid particles. Moreover, the hydrodynamics and diffusion of a single colloidal ellipsoid (prolate or oblate with moderate aspect ratios) are accurately captured. The calculated drag force on the ellipsoid and its diffusion coefficients (both translational and rotational) agree quantitatively with the theoretical predictions in the Stokes limit.

Computer Science↗

Smoothed dissipative particle dynamics model for mesoscopic multiphase flows in the presence of thermal fluctuations

Thermal fluctuations cause perturbations of fluid-fluid interfaces and highly nonlinear hydrodynamics in multiphase flows. In this work, we develop a novel multiphase smoothed dissipative particle dynamics model. This model accounts for both bulk hydrodynamics and interfacial fluctuations. Interfacial surface tension is modeled by imposing a pairwise force between SDPD particles. We show that the relationship between the model parameters and surface tension, previously derived under the assumption of zero thermal fluctuation, is accurate for fluid systems at low temperature but overestimates the surface tension for intermediate and large thermal fluctuations. To analyze the effect of thermal fluctuations on surface tension, we construct a coarse-grained Euler lattice model based on the mean field theory and derive a semi-analytical formula to directly relate the surface tension to model parameters for a wide range of temperatures and model resolutions. We demonstrate that the present method correctly models the dynamic processes, such as bubble coalescence and capillary spectra across the interface.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Comprehensive comparison of two tracking codes for single-particle dynamics evaluation of a next-generation storage ring light source

Next-generation light sources based on the multibend achromat concept place great reliance on the accuracy of beam dynamics modeling. To ensure the success of such light sources, confirmation of design performance with at least two independent codes is prudent. The APS Upgrade (APS-U) lattice has been designed using the code ELEGANT, which has existing and new features that are needed by the design. Corresponding, independent improvements have recently been made to the accelerator toolbox (AT), in order to permit an independent check of nonlinear dynamics predictions. The new developments include the modeling of combined-function bending magnets with straight geometry and improved fringe field effects of quadrupole magnets. Calculations of linear and nonlinear lattice parameters and particle tracking results were compared, showing remarkable agreement was found between the two independently developed codes. This provides significant confirmation of the feasibility of the APS-U design.

storage ring↗

Efficient bi-directional coupling of 3D computational fluid-particle dynamics and 1D Multiple Path Particle Dosimetry lung models for multiscale modeling of aerosol dosimetry

The development of predictive aerosol dosimetry models has been a major focus of environmental toxicology and pharmaceutical health research for decades. One-dimensional (1D) models successfully predict overall deposition averages but fail to accurately predict local deposition. Computational fluid-particle dynamics (CFPD) models provide site-specific predictions but at a computational cost that prohibits whole lung predictions. Thus, there is a need for developing multiscale strategies to provide a realistic subject-specific picture of the fate of inhaled aerosol in the lungs. CT-based 3D/CFPD models of the large airways were bidirectionally coupled with individualized 1D Navier-Stokes airflow and particle transport based upon the widely used Multiple Path Particle Dosimetry Model (MPPD). Distribution of airflows among lobes was adjusted by measured lobar volume changes observed in CT images between FRC and FRC + 1.5 L. Additionally, as a test of the effectiveness of the coupling procedures, deposition modeling of previous 1 µm aerosol exposure studies was performed. The complete coupled model was run for 3 breaths, with the computation-intense portion being the 3D CFD Lagrangian particle tracking calculation. The average deposition per breath was 11% in the combined multiscale model with site-specific doses available in the CFPD portion of the model and airway- or region-specific deposition available for the MPPD portion. In conclusion, the key methods developed in this study enable predictions of ventilation heterogeneities and aerosol deposition across the lungs that are not captured by 3D or 1D models alone. Overall, these methods can be used as the foundation for multi-scale modeling of the full respiratory system.

60 APPLIED LIFE SCIENCES↗

An integrated boundary approach for colloidal suspensions simulated using smoothed dissipative particle dynamics

We report that in particle-based continuum solvers such as smoothed particle hydrodynamics (SPH) and smoothed dissipative particle dynamics (SDPD), one of the most significant challenges is the treatment of solid boundaries like walls and colloidal particles, whose presence leads to a truncation of the integral approximation, and hence, error in the numerical solution. In this work, we describe an integrated boundary framework for modeling colloidal suspensions composed of rigid spherical particles. The integral corresponding to the colloid's contribution is analytically evaluated, giving a simple and computationally inexpensive approach relative to conventional boundary particle techniques. We formulate a thermodynamically-consistent version of this top-down method for mesoscale simulations, in which the fluid exchanges momentum with the suspended particles due to thermal fluctuations, giving a framework for modeling the dynamics of colloids at arbitrary Reynolds and Péclet numbers. The resulting evolution equations are validated for a single colloidal particle in a fluid at constant temperature. This simple approach requires ~ N c (p/m) R$2\atop{c}$ fewer pair force calculations relative to traditional boundary particle strategies, where N c is the number of colloids in the system, R c is the colloid radius, ρ is the colloid mass density, and m is the mass of the SDPD particles. Additionally, the use of integrated boundaries removes the need for rigid body constraint dynamics, giving an elegant and efficient basis for large-scale simulations of colloidal suspensions that is general and does not make any physical assumptions about the flow.

42 ENGINEERING↗

Peculiarities of charged particle dynamics under cyclotron resonance conditions

Peculiarities of the dynamics of charged particles interacting with electromagnetic radiation under nearly autoresonance conditions are analyzed. In particular, analysis of nonlinear cyclotron resonances shows that their widths increase when the autoresonance conditions are approached. In this case, however, the distance between nonlinear resonances increases even faster, due to which nonlinear resonances do not overlap and, accordingly, regimes with dynamic chaos do not occur. According to calculations, the dynamics of charged particles under the autoresonance conditions is very sensitive to fluctuations, the effect of which can be anomalously large and lead to superdiffusion. It is shown that, under the autoresonance conditions, particle dynamics on small time intervals can differ significantly from that on large time intervals. This effect is most pronounced in the presence of fluctuations in the system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Towards modelling AR Sco: generalized particle dynamics and strong radiation-reaction regimes

Numerical simulations of relativistic plasmas have become more feasible, popular, and crucial for various astrophysical sources with the availability of computational resources. The necessity for high-accuracy particle dynamics is especially highlighted in pulsar modelling due to the extreme associated electromagnetic fields and particle Lorentz factors. Including the radiation-reaction force in the particle dynamics adds even more complexity to the problem, but is crucial for such extreme astrophysical sources. We have also realized the need for such modelling concerning magnetic mirroring and particle injection models proposed for AR Sco, the first white dwarf pulsar. This paper demonstrates the benefits of using higher-order explicit numerical integrators with adaptive time-step methods to solve the full particle dynamics with radiation-reaction forces included. We show that for standard test scenarios, namely various combinations of uniform E- and B-fields and a static dipole B-field, the schemes we use are equivalent to and in extreme field cases outperform standard symplectic integrators in accuracy. We show that the higher-order schemes have massive computational time improvements due to the adaptive time-steps we implement, especially in non-uniform field scenarios and included radiation reaction where the particle gyro-radius rapidly changes. When balancing accuracy and computational time, we identified the adaptive Dormand–Prince eighth-order scheme to be ideal for our use cases. The schemes we use maintain accuracy and stability in describing the particle dynamics and we indicate how a charged particle enters radiation-reaction equilibrium and conforms to the analytical Aristotelian Electrodynamics expectations.

79 ASTRONOMY AND ASTROPHYSICS↗

New electric force and charge exchange modules in discrete element model enables particle dynamics simulation in electric field

Discrete element modeling (DEM) is an important technique for particle dynamics simulation. The field of metal additive manufacturing often utilizes DEM to simulate the rheological behaviors of powder. Standard contact and short-range interactions are sufficient in most cases but insufficient to describe the particle dynamics with the influence of an electric field. Modeling such a system requires additional physics to describe the particle–field interactions. The relevant physics has been experimentally understood but is not yet available in DEM. Here, we develop a charge exchange and an electric force module. The electric force module governs particle response to the electric field, while the charge exchange module enables particles to acquire proper charge during contact with charged geometries. We validate the modules against analytical calculations and high-speed videos of electrostatic powder deposition experiments. Notably, the model struggles to capture the initial particle levitation. We later deploy a modified electric field, as supported by static electric field simulation, to better approximate the electric field penetration into the powder layer. This modification improves the model’s capability of simulating realistic particle levitation. The results highlight the challenges of modeling particle behaviors in the electric field while demonstrating the feasibility of obtaining quantitative results, which are difficult to measure experimentally.

charge exchange↗

Flow reduction of hydrocarbon liquid in silica nanochannel: Insight from many-body dissipative particle dynamics simulations

A modified many-body dissipative particle dynamics (mDPD) model recently developed for realistic mesoscale multiphase flow simulations is rigorously parameterized, calibrated, and applied for elucidating the flow mechanisms of hydrocarbon liquids (i.e., heptane in this work) in amorphous silica cylindrical nanochannels with inner diameters ranging from 4.5 to 22.5 nm. The simulation results suggest the presence of a strong threshold of pressure gradient under which heptane cannot be driven to flow. The threshold for the 4.5 nm diameter pore is 10 to 100 times as high as for the 9–22.5 nm diameter pore, highlighting a remarkable nanoconfinement effect. Fluid viscosity is found to exhibit a shear-thinning phenomenon with intensity to weaken with increasing channel diameter — a phenomenon not observed in nanochannel flow of liquid water and gas in literature. Most remarkably, the radial profiles of average longitudinal flow velocity fitted by the modified Hagen-Poiseuille equation showed a negative slip length (–2.5% to –0.5% relative to the diameter) and a reduction of apparent permeability by 16% to 23%. Furthermore, this finding suggests silica nanochannels tend to deter hydrocarbon flow, a phenomenon that is opposed to the flow enhancement reported in most of the prior nanochannel flow studies in literature.

74 ATOMIC AND MOLECULAR PHYSICS↗

Symplectic neural network and its application to charged particle dynamics in electromagnetic fields

Recently, machine learning models have shown many successes in various applications in science and technology. In this work, we focus on the charged particle dynamics, with the development of a class of symplectic neural networks, including a linear version, SympMat, and a nonlinear version, HénonNet. Both are designed to preserve the structure of Hamiltonian systems. We show that they can be used to model relevant Hamiltonian systems of interest in plasma physics and astrophysics, for linear and nonlinear charged particle dynamics, with the potential to bridge multi-scale simulations. These symplectic neural networks are adapted to the applications in plasma simulations and particle-wave interaction with parametric dependence and periodicity, where we have investigated their performance and accuracy. In particular, SympMat is shown to outperform the traditional Boris particle pusher down to the sub-gyroperiod scale in the case of charged particles in uniform magnetic fields. HénonNet successfully predicts the hot electron distribution, which is validated against theoretical results. These results highlight the potential of symplectic neural networks as a trajectory integrator for particle-in-cell simulations or a fast surrogate to replace conventional numerical schemes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Particle Dynamics in a Diblock-Copolymer-Based Dodecagonal Quasicrystal and Its Periodic Approximant by X-Ray Photon Correlation Spectroscopy

Temperature-dependent X-ray photon correlation spectroscopy (XPCS) measurements are reported for a binary diblock copolymer blend that self-assembles into an aperiodic dodecagonal quasicrystal (DDQC) and a periodic Frank-Kasper σ phase approximant. The measured structural relaxation times are Bragg scattering wavevector-independent and are five times faster in the DDQC than the σ phase, with minimal temperature dependence. Further, the underlying dynamical relaxations are ascribed to differences in particle motion at the grain boundaries within each of these tetrahedrally close-packed assemblies. These results identify unprecedented particle dynamics measurements of tetrahedrally-coordinated micellar block polymers, thus expanding the application of XPCS to ordered soft materials.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Pairwise adaptive thermostats for improved accuracy and stability in dissipative particle dynamics

We examine the formulation and numerical treatment of dissipative particle dynamics (DPD) and momentum-conserving molecular dynamics. We show that it is possible to improve both the accuracy and the stability of DPD by employing a pairwise adaptive Langevin thermostat that precisely matches the dynamical characteristics of DPD simulations (e.g., autocorrelation functions) while automatically correcting thermodynamic averages using a negative feedback loop. In the low friction regime, it is possible to replace DPD by a simpler momentum-conserving variant of the Nosé–Hoover–Langevin method based on thermostatting only pairwise interactions; we show that this method has an extra order of accuracy for an important class of observables (a superconvergence result), while also allowing larger timesteps than alternatives. All the methods mentioned in the article are easily implemented. Numerical experiments are performed in both equilibrium and nonequilibrium settings; using Lees–Edwards boundary conditions to induce shear flow.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Dissipative particle dynamics for directed self-assembly of block copolymers

The dissipative particle dynamics (DPD) simulation method has been shown to be a promising tool to study self-assembly of soft matter systems. In particular, it has been used to study block copolymer (BCP) self-assembly. However, previous parameterizations of this model are not able to capture most of the rich phase behaviors of BCPs in thin films nor in directed self-assembly (chemoepitaxy or graphoepitaxy). Here, we extend the applicability of the DPD method for BCPs to make it applicable to thin films and directed self-assembly. Our new reparameterization not only is able to reproduce the bulk phase behavior but also manages to predict thin film structures obtained experimentally from chemoepitaxy or graphoepitaxy. A number of different complex structures, such as bilayer nanomeshes, 90° bend structures, circular cylinders/lamellae and Frank-Kasper phases directed by trenches, and post arrays or chemically patterned substrates, have all been reproduced in this work. This reparameterized DPD model should serves as a powerful tool to predict BCP self-assembly, especially in some complex systems where it is difficult to implement self-consistent field theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stable schemes for dissipative particle dynamics with conserved energy

This article presents a new numerical scheme for the discretization of dissipative particle dynamics with conserved energy. The key idea is to reduce elementary pairwise stochastic dynamics (either fluctuation/dissipation or thermal conduction) to effective single-variable dynamics, and to approximate the solution of these dynamics with one step of a Metropolis–Hastings algorithm. This ensures by construction that no negative internal energies are encountered during the simulation, and hence allows to increase the admissible timesteps to integrate the dynamics, even for systems with small heat capacities. Stability is only limited by the Hamiltonian part of the dynamics, which suggests resorting to multiple timestep strategies where the stochastic part is integrated less frequently than the Hamiltonian one.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗