Particle Simulation Research Articles

Application investigations of force fields for molecular dynamic simulations of medical aluminum particles

The phase transition of metals is a research hotspot in molecular dynamic (MD) simulation. With the increase of the development of MD, different force fields with different requirements have emerged, which helps to select the appropriate force field and also increases the difficulty of selection. In addition, previous studies have been affected by particle size, which affects the melting point accuracy. MD simulation of the melting and condensing behavior of Aluminum (Al) particles was carried out by using EAM force fields from different sources. The thermal behavior of phase transition was studied by means of potential energy, specific heat, MSD, FCC lattice number, etc. The melting and condensation process of 2–10[Formula: see text]nm cubic without boundary under the NPT system was simulated, and the steady-state simulation was discussed by means of an isometric temperature point. It is proved that the borderless simulation can completely eliminate the boundary effect. The parameter setting of efficient use of EAM is widely discussed by using this method, and the effectiveness of the EAM force field is compared, so as to improve the efficiency of scholars engaged in related research and avoid the difficult choice of force field files. The results show that the borderless simulation has quite high advantages in terms of phase transition potential energy and melting point, while the current EAM force field is inherently deficient in this kind of discussion, and the development of new force field is urgent.

Predictions of the interfacial free energy along the coexistence line from single-state calculations.

The calculation of the interfacial free energy between two thermodynamic phases is crucial across various fields, including materials science, chemistry, and condensed matter physics. In this study, we apply an existing thermodynamic approach, the Gibbs-Cahn integration method, to determine the interfacial free energy under different coexistence conditions, relying on data from a single-state calculation at specified pressure and temperature. This approach developed by Laird et al. [J. Chem. Phys. 131, 114110 (2009)] reduces the computational demand and enhances efficiency compared to methods that require separate measurements at each thermodynamic state. The integration scheme computes the excess interfacial free energy using unbiased constant volume, temperature, and number of particle simulations (NVT), where the two phases coexist, to provide input for the calculations. We apply this method to the Lennard-Jones and mW water models for liquid-solid interfaces, as well as the Lennard-Jones and TIP4P/2005 models for liquid-vapor interfaces. Our results demonstrate the accuracy and effectiveness of this integration route for estimating the interfacial free energy along a coexistence line.

Solar System Migration Points to a Renewed Concept: Galactic Habitable Orbits

Abstract Astrophysical evidence suggests that the Sun was born near 5 kpc from the Galactic center, within the corotation radius of the Galactic bar, around 6–7 kpc. This presents challenges for outward migration due to the Jacobi energy constraint, preventing stars from easily overcoming the corotation barrier. In this study, we use test particle simulations to explore two possible migration pathways for the Sun: a “trapped” scenario, where the Sun's orbit was influenced by a slowing Galactic bar, and an “untrapped” scenario driven by dynamic spiral arms. Our results demonstrate that both mechanisms can explain how the Sun migrated from its birth radius (≈5 kpc) to its current orbital radius around 8.5–9 kpc. Furthermore, we investigate the environmental changes experienced by the Sun along these migration pathways, focusing on variations in radiation hazards and comet fluxes, which may have impacted planetary habitability. These findings highlight the dynamic nature of galactic habitability, emphasizing that the path a star takes within the Milky Way can significantly affect its surrounding environment and the potential for life. We propose a new concept of “Galactic habitable orbits,” which accounts for evolving galactic structures and their effects on stellar and planetary systems. This work contributes to a deeper understanding of the solar system's migration and its implications for habitability within the Milky Way.

Directed motion of cognitive active agents in a crowded three-way intersection

Understanding the navigation through semi-dense crowds at intersections poses a significant challenge in pedestrian dynamics, with implications for facility design and insights into emergent collective behavior. To tackle this problem, a system of cognitive active agents at a crowded three-way intersection is studied using Langevin simulations of intelligent active Brownian particles (iABPs) with directed visual perception (resulting in non-reciprocal interactions) and self-steering avoidance—without volume exclusion. We find that the emergent self-organization depends on agent maneuverability, goal fixation, and vision angle, and identify several forms of collective behavior, including localized flocking, jamming and percolation, and self-organized rotational flows. Additionally, we demonstrate that the motion of individual agents can be characterized by fractional Brownian motion and Lévy walk models across different parameter regimes. Moreover, despite the rich variety of collective behavior, the fundamental flow diagram shows a universal curve for different vision angles. Our research highlights the impact of collision avoidance, goal following, and vision angle on the individual and collective dynamics of interacting pedestrians.

Explicit Symplectic Integrators with Adaptive Time Steps in Curved Spacetimes

Recently, our group developed explicit symplectic methods for curved spacetimes that are not split into several explicitly integrable parts but are via appropriate time transformations. Such time-transformed explicit symplectic integrators should have employed adaptive time steps in principle, but they are often difficult in practical implementations. In fact, they work well if time transformation functions cause the time-transformed Hamiltonians to have the desired splits and approach 1 or constants for sufficiently large distances. However, they do not satisfy the requirement of step-size selections in this case. Based on the step-size control technique proposed by Preto & Saha, the nonadaptive time-step time-transformed explicit symplectic methods are slightly adjusted as adaptive ones. The adaptive methods have only two additional steps and a negligible increase in computational cost compared with the nonadaptive ones. Their implementation is simple. Several dynamical simulations of particles and photons near black holes have demonstrated that the adaptive methods typically improve the efficiency of the nonadaptive methods. Because of the desirable property, the new adaptive methods are applied to investigate the chaotic dynamics of particles and photons outside the horizon in a Schwarzschild–Melvin spacetime. The new methods are widely applicable to all curved spacetimes corresponding to Hamiltonians or time-transformed Hamiltonians with the expected splits. In addition, application to the backward ray-tracing method for studying the motion of photons and shadows of black holes is possible.

Environmental dependence of geometrical efficiency for the scintillation cell in radon and thoron measurement.

222Rn is recognized as a matter of international concern for human health risk. Because 220Rn as well as 222Rn coexist in the natural environment, thoron sometimes influences the experiment for radon measurement. It is important to measure radon and thoron separately to evaluate the risk of the exposure to 222Rn. As a discriminative measurement method for 222Rn and 220Rn, a simple technique with a single scintillation cell is well known. However, in recent years, the influence of atmospheric environment on the geometrical efficiency of the scintillation cell has not yet been investigated. In this study, environmental dependence of geometrical efficiency for the scintillation cell in 222Rn and 220Rn measurement was investigated using the Lucas type scintillation cell and Monte Carlo particle simulation. It was found that the influence of temperature and pressure on the geometrical efficiencies were larger than that of relative humidity.

Quantitative Equivalence and Performance Comparison of Particle and Field-Theoretic Simulations.

Particle and field-theoretic simulations are both commonly used methods to study the equilibrium properties of polymeric materials. Yet despite the formal equivalence of the two methods, no comprehensive comparisons of particle and field-theoretic simulations exist in the literature. In this work, we seek to fill this gap by performing a systematic and quantitative comparison of particle and field-theoretic simulations. In our comparison, we consider four representative polymeric systems: a homopolymer melt/solution, a diblock copolymer melt, a polyampholyte solution, and a polyelectrolyte gel. For each of these systems, we first demonstrate that particle and field-theoretic simulations are equivalent and yield exactly the same results for the pressure and the chemical potential. We next quantify the performance of each method across a range of different conditions including variations in chain length, system density, interaction strength, system size, and polymer volume fraction. The outcome of these calculations is a comprehensive look into the performance of each method and the systems and conditions when either particle or field-theoretic simulations are preferred. We find that field-theoretic simulations are equal to or faster than particle simulations for nearly all of the systems and conditions examined. In many situations, field-theoretic simulations are several orders of magnitude faster than particle simulations, especially if the polymer chains are long, the system density is high, and long-range Coulombic interactions are present. We also demonstrate that field-theoretic simulations are considerably faster at calculating the chemical potential and bypass the challenges associated with particle-based Widom insertion techniques. Taken together, our results provide quantitative evidence that field-theoretic simulations can reach and sample equilibrium considerably faster than particle simulations while simultaneously producing equivalent results.

Backward test particle simulation of nonlinear cyclotron wave-particle interactions in the radiation belts

Wave-particle interaction plays a crucial role in the dynamics of the Earth’s radiation belts. Cyclotron resonance between coherent whistler mode electromagnetic waves and energetic electrons of the radiation belts is often called a coherent instability. Coherent instability leads to wave amplification/generation and particle acceleration/scattering. The effect of wave on particle’s distribution function is a key component of the instability. In general, whistler wave amplitude can grow over threshold of quasi-linear (linear) diffusion theory which analytically tracks the time-evolution of a particle distribution. Thus, a numerical approach is required to model the nonlinear wave induced perturbations on particle distribution function. A backward test particle model is used to determine the energetic electrons phase space dynamics as a result of coherent whistler wave instability. The results show the formation of a phase space features with much higher resolution than is available with forward scattering models. In the nonlinear regime the formation of electron phase space holes upstream of a monochromatic wave is observed. The results validate the nonlinear phase trapping mechanism that drives nonlinear whistler mode growth. The key differences in phase-space perturbations between the linear and nonlinear scenarios are also illustrated. For the linearized equations or for low (below threshold) wave amplitudes in the nonlinear case, there is no formation of a phase-space hole and both models show features that can be characterized as linear striations or ripples in phase-space.

Radial Wave in the Galactic Disk: New Clues to Discriminate Different Perturbations

Decoding the key dynamical processes that shape the Galactic disk structure is crucial for reconstructing the Milky Way’s evolution history. The second Gaia data release unveils a novel wave pattern in the L Z −〈V R 〉 space, but its formation mechanism remains elusive due to the intricate nature of involved perturbations and the challenges in disentangling their effects. Utilizing the latest Gaia DR3 data, we find that the L Z −〈V R 〉 wave systematically shifts toward lower L Z for dynamically hotter stars with larger J Z values. The amplitude of this phase shift between stars of different dynamical hotness (ΔL Z ) peaks at around 2100 km s−1 kpc. To differentiate the role of different perturbations, we perform three sets of test particle simulations, wherein a satellite galaxy, transient spiral arms, and a bar plus the transient spiral arms act as the sole perturber, respectively. Under the satellite impact, the phase shift amplitude ΔL Z decreases toward higher L Z , which we interpret through a toy model of radial phase mixing. While neither the transient spiral arms nor the bar generates an azimuthally universal phase shift variation pattern, combining the bar and spirals generates a characteristic ΔL Z peak at the 2:1 outer Lindblad resonance (OLR) of the bar, qualitatively resembling the observed feature. Therefore, the L Z −〈V R 〉 wave is more likely of internal origin. Furthermore, linking the ΔL Z peak to the 2:1 OLR offers a novel approach to constraining the pattern speed of the Galactic bar, supporting the long/slow bar model.

Microparticle sorting in microfluidic Taylor–Couette flows

In this experimental study, we demonstrate that settling polymethyl methacrylate (PMMA) microparticles with diameters ranging from 6 to 60 µm segregate into distinct bands according to their size when subjected to a rotating laminar annular gap flow with a diverging gap width in the axial direction. Different gap widths ranging from 130 to 1200 µm have been investigated in the fully laminar flow regime. Distinct, spatially separated particle bands of different particle sizes have been observed for nine different geometric configurations, including non-conical, conical, double conical, and variously inclined conical inner cylinder shapes. The study considers different rotation rates, geometric combinations, particle volume fractions, and particle size combinations. Particle size separation was achieved at volume fractions ranging from 2.2% to 11% for rotating inner cylinders. In contrast, no separation occurs during the experimental run when both the outer and inner cylinders are perfectly cylindrical, with no significant variation in the annular gap height. Our experiments also show that rotation of the inner cylinder results in more pronounced particle separation than rotation of the outer cylinder. Microscopic particle image velocimetry (µPIV) measurements show that the presence of particles induces an axial velocity component, which acts as a key transport mechanism. In addition, a significant variation in shear rate is observed across particle bands, which may explain size segregation by shear-induced migration. Furthermore, single particle simulations show that particle trajectories and velocities vary significantly with particle size.

The Diffusion Tensor of Protons at 1 au: Comparing Simulation, Observation, and Theory

The natural variation in plasma parameters observed at 1 au can lead to a variation in transport parameters, such as diffusion and drift coefficients, for energetic charged particles of solar and galactic origin. Given the importance of these parameters to particle transport studies, this variation is investigated through test particle simulations over a range of energies in the presence of simulated turbulence with properties corresponding to an ensemble of observed turbulence conditions at Earth. The resulting transport coefficients are then compared with observational estimates from the literature, as well as the predictions of several scattering theories. Parallel and perpendicular mean free paths are shown to vary widely, for the former in agreement with prior observational estimates, but not for the latter. Furthermore, a large disparity between the predictions of theory and the simulation results is noted for the perpendicular mean free path. As such, these results indicate that particle transport studies, particularly predictive ones, need to take into account this natural variation in transport coefficients.

Reduced-order condensed-phase kinetic models for polyethylene, polypropylene and polystyrene thermochemical recycling

Thermochemical recycling of plastic waste (PW) into chemicals and energy vectors requires coupling particle and reactor-scale simulations to accurate condensed phase pyrolysis mechanisms for each constituent. This work proposes a methodology to derive reduced-order condensed-phase kinetic models from validated semi-detailed kinetic mechanisms. Two types of kinetic models are obtained for polyethylene (PE), polypropylene (PP) and polystyrene (PS): reduced semi-detailed models and multi-step fully lumped ones. These families offer different compromises between accuracy and computational cost. The former employ 50–100 gas + liquid species and describe both the radical degradation and the detailed carbon distribution of the products. Conversely, the latter involves 5–10 species per polymer tracking only the main petroleum cuts. The kinetic mechanisms are complemented by the definition of thermochemical properties of gas, liquid, and solid-phase species, accounting for phase-transitions through pseudo-chemical reactions. Model validations are performed by comparison with experimental data and the original semi-detailed mechanisms in terms of mass loss, heat fluxes and product distribution profiles. The resulting CHEMKIN-like condensed-phase models are attached as Supplementary Material and as a GitHub repository. Extending the proposed approach to other polymers and coupling it with existing subsets in the CRECK kinetic framework (e.g., biomass, PVC, PET) offers a powerful tool to model thermochemical recycling of PW and biomass/PW mixtures.

Cosmic Ray Diffusion in Magnetic Fields Amplified by Nonlinear Turbulent Dynamo

The diffusion of cosmic rays (CRs) in turbulent magnetic fields is fundamental to understanding various astrophysical processes. We explore the CR diffusion in the magnetic fluctuations amplified by the nonlinear turbulent dynamo in the absence of a strong mean magnetic field. Using test particle simulations, we identify three distinct CR diffusion regimes: mirroring, wandering, and magnetic moment scattering (MMS). With highly inhomogeneous distribution of the dynamo-amplified magnetic fields, we find that the diffusion of CRs is also spatially inhomogeneous. Our results reveal that lower-energy CRs preferentially undergo the mirror and wandering diffusion in the strong-field regions, and the MMS diffusion in the weak-field regions. The former two diffusion mechanisms play a more important role toward lower CR energies, resulting in a relatively weak energy dependence of the overall CR mean free path (MFP). In contrast, higher-energy CRs predominantly undergo the MMS diffusion, for which the incomplete particle gyration, i.e., the limit case of mirroring, in strong fields has a more significant effect than the scattering by small-scale field tangling/reversal. Compared with lower-energy CRs, they are more poorly confined in space and their MFPs have a stronger energy dependence. We stress the fundamental role of magnetic field inhomogeneity of nonlinear turbulent dynamo in causing the different diffusion behavior of CRs compared to that in sub-Alfvénic magnetohydrodynamic turbulence.

Statistical-Physics-Informed Neural Networks (Stat-PINNs): A machine learning strategy for coarse-graining dissipative dynamics

Machine learning, with its remarkable ability for retrieving information and identifying patterns from data, has emerged as a powerful tool for discovering governing equations. It has been increasingly informed by physics, and more recently by thermodynamics, to further uncover the thermodynamic structure underlying the evolution equations, i.e., the thermodynamic potentials driving the system and the operators governing the kinetics. However, despite its great success, the inverse problem of thermodynamic model discovery from macroscopic data is in many cases non-unique, meaning that multiple pairs of potentials and operators can give rise to the same macroscopic dynamics, which significantly hinders the physical interpretability of the learned models. In this work, we consider the problem of deriving the macroscopic (continuum) equations from microscopic (particle) data, and encode knowledge from statistical mechanics to resolve this non-uniqueness for the first time. The proposed machine learning framework, named as Statistical-Physics-Informed Neural Networks (Stat-PINNs), is here developed for purely dissipative isothermal systems. Interestingly, it only uses data from short-time particle simulations to learn the thermodynamic structure, which can in turn be used to predict long-time macroscopic evolutions. We demonstrate the approach for particle systems with Arrhenius-type interactions, common to a wide range of phenomena, such as defect diffusion in solids, surface absorption, and chemical reactions. Our results from Stat-PINNs can successfully recover the known analytic solution for the case with long-range interactions and discover the hitherto unknown potential and operator governing the short-range interaction cases. We compare our results with direct particle simulations and an analogous approach that solely excludes statistical mechanics, and observe that, in addition to recovering the unique thermodynamic structure, statistical mechanics relations can increase the robustness and predictive capability of the learning strategy.

Electromagnetic Landau Resonance: Nonlinear Dynamics and Harmonic Generation

AbstractIn situ particle observations provide useful information for determining the significance of nonlinearity in wave‐particle interactions. Here, we examine an electromagnetic Landau resonance event observed by the Magnetospheric Multiscale mission near the dayside magnetopause along this line of thought. During this event, protons with energy 748 eV and pitch angle are observed to resonate with electromagnetic‐ion‐cyclotron waves. Detailed data analysis reveals the existence of a second harmonic signal in proton modulation. Using an observation‐based test particle simulation, this signal is explained as a low‐resolution manifestation of phase space rolled‐up structures, which themselves are not observable due to limited instrument resolution. The presence of these rolled‐up structures suggests that the waves induce significant displacement of the protons in phase space, consequently confirming the nonlinear nature of the observed interaction. Based on the observations, we further discuss the possibility of the nonlinear electromagnetic Landau resonance generating second harmonic waves.

Ductile and brittle yielding of athermal amorphous solids: A mean-field paradigm beyond the random-field Ising model.

Amorphous solids can yield in either a ductile or brittle manner under strain: plastic deformation can set in gradually, or abruptly through a macroscopic stress drop. Developing a unified theory describing both ductile and brittle yielding constitutes a fundamental challenge of nonequilibrium statistical physics. Recently, it has been proposed that, in the absence of thermal effects, the nature of the yielding transition is controlled by physics akin to that of the quasistatically driven random field Ising model (RFIM), which has served as the paradigm for understanding the effect of quenched disorder in slowly driven systems with short-ranged interactions. However, this theoretical picture neglects both the dynamics of, and the elasticity-induced long-ranged interactions between, the mesoscopic material constituents. Here, we address these two aspects and provide a unified theory building on the Hébraud-Lequeux elastoplastic description. The first aspect is crucial to understanding the competition between the imposed deformation rate and the finite timescale of plastic rearrangements: We provide a dynamical description of the macroscopic stress drop, as well as predictions for the shifting of the brittle yield strain and the scaling of the peak susceptibility with inverse shear rate. The second is essential to capture properly the behavior in the limit of quasistatic driving, where avalanches of plasticity diverge with system size at any value of the strain. We fully characterise the avalanche behavior, which is radically different to that of the RFIM. In the quasistatic, infinite-size limit, we find that both models have mean-field Landau exponents, obscuring the effect of the interactions. We show, however, that the latter profoundly affect the behavior of finite systems approaching the spinodal-like brittle yield point, where we recover qualitatively the finite-size trends found in particle simulations. The interactions also modify the nature of the random critical point separating ductile and brittle yielding, where we predict critical behavior on top of the marginality present at any value of the strain. We finally discuss how all our predictions can be directly tested against particle simulations and eventually experiments, and make first steps in this direction.

Mechanics and Morphology of Proliferating Cell Collectives with Self-Inhibiting Growth.

We study the dynamics of proliferating cell collectives whose microscopic constituents' growth is inhibited by macroscopic growth-induced stress. Discrete particle simulations of a growing collective show the emergence of concentric-ring patterns in cell size whose spatiotemporal structure is closely tied to the individual cell's stress response. Motivated by these observations, we derive a multiscale continuum theory whose parameters map directly to the discrete model. Analytical solutions of this theory show the concentric patterns arise from anisotropically accumulated resistance to growth over many cell cycles. This Letter shows how purely mechanical processes can affect the internal patterning and morphology of cell collectives, and provides a concise theoretical framework for connecting the micro- to macroscopic dynamics of proliferating matter.

The Impact of the 8–10 March 2012 Geomagnetic Storm on Inner Zone Protons as Measured by Van Allen Probes

AbstractThe Relativistic Electron Proton Telescope (REPT) instrument on the Van Allen Probes observed a double‐peaked inner zone proton population throughout the 7 year lifetime of the mission. M. Hudson et al. (2023) showed that a strong SEP event accompanied by a CME‐shock in early March 2012 provided the Solar Energetic Proton (SEP) source for the higher L trapped proton population, which then diffused radially inward to be observed by REPT at . The study followed trajectories of SEP protons launched isotropically from a sphere at 7 Re for 2.5 hr in fields calculated by the LFM‐RCM global MHD model, which includes electric fields needed to model the transport and trapping of the protons by the shock, and then a radial diffusion simulation was run for 2 years using the result from the test‐particle simulation as the initial condition. The simulation result was compared with REPT measurement in November 2013 and showed reasonable agreement. However, the simulation overestimated the Phase Space Density by a factor of four due to lack of field line curvature scattering during the storm in the model. In this study, a test‐particle simulation is performed for 2 days following the injection and trapping of protons in March 2012 using TS05 fields to simulate the field line curvature scattering of the trapped SEP due to the buildup of the ring current during the geomagnetic storm. The resulting sample distribution was then weighted using the flux at the end of the two‐hour MHD‐test particle simulation. A radial diffusion simulation is then run using the initial profile that included the loss effect, with improved comparison with REPT measurements after 2 years.

Toward Predicting the Formation of Integral-Asymmetric, Isoporous Diblock Copolymer Membranes.

The self-assembly and nonsolvent-induced phase separation (SNIPS) process of block copolymers and solvents enables the fabrication of integral-asymmetric, isoporous membranes. An isoporous top layer is formed by evaporation-induced self-assembly (EISA) and imparts selectivity for ultrafiltration of functional macromolecules or water purification. This selective layer issupported by a macroporous bottom structure that is formed by nonsolvent-induced phase separation (NIPS) providing mechanical stability. Thereby the permeability/selectivity tradeoff is optimized. The SNIPS fabrication involves various physical phenomena-e.g.,evaporation, self-assembly, macrophase separation, vitrification - and multiple structural, thermodynamic, kinetic, and process parameters. Optimizing membrane properties and rationally designing fabrication processes is a challenge which particle simulation can significantly contribute to. Using large-scale particle simulations, it is observed that 1) a small incompatibility between matrix-forming block of the copolymer and nonsolvent, 2) a glassy arrest that occurs at a smaller polymer concentration, or 3) a higher dynamical contrast between polymer and solvent results in a finer, spongy substructure, whereas the opposite parameter choice gives rise to larger macropores with an elongated shape. These observations are confirmed by comparison to experiments on polystyrene (PS)-block-poly(4-vinylpyridine) (P4VP) diblock copolymer membranes, varying the chemical nature of the coagulant or the temperature of coagulationbath.

Dynamic Simulation of Metal Particles Randomly and Driving Efficiency of Drive Electrodes for High Voltage DC GIL

Dynamic Simulation of Metal Particles Randomly and Driving Efficiency of Drive Electrodes for High Voltage DC GIL