Abstract: Molecular-dynamic simulations were performed in order to investigate the melting processes of isotropically confined binary systems. We considered two species of particles, which differ by their amount of electric charge. A Lindemann type of criterion was used to determine the angular melting temperature. We demonstrate that the magic-to-normal cluster transition can evolve in two distinct ways, that is, through a structural phase transition of the first order or via a smooth transition where an increase of the shells' width leads to a continuous decreasing mechanical stability of the system. Moreover, for large systems, we demonstrate that the internal cluster exerts a minor effect on the mechanical stability of the external shell. Furthermore, we show that highly symmetric configurations, such as those found for multiple ring structures, have large mechanical stability, i.e., high angular melting temperature.

Abstract: We study the structure and phonon spectrum of a two-dimensional bilayer system of classical charged dipoles oriented perpendicular to the plane of the layers for equal density in each layer. This system can be tuned through six different crystalline phases by changing the interlayer separation or the charge and/or dipole moment of the particle. The presence of the charge on the dipole particles is responsible for the nucleation of five staggered phases and a disordered phase which are not found in the magnetic dipole bilayer system. These extra phases are a consequence of the competition between the repulsive Coulomb and the attractive dipole interlayer interaction. We present the phase diagram and determine the order of the phase transitions. The phonon spectrum of the system was calculated within the harmonic approximation, and a nonmonotonic behavior of the phonon spectrum is found as a function of the effective strength of the interparticle interaction. The stability of the different phases is determined.

Abstract: The autoregressive neural networks are emerging as a powerful computational tool to solve relevant problems in classical and quantum mechanics. One of their appealing functionalities is that, after they have learned a probability distribution from a dataset, they allow exact and efficient sampling of typical system configurations. Here we employ a neural autoregressive distribution estimator (NADE) to boost Markov chain Monte Carlo (MCMC) simulations of a paradigmatic classical model of spin-glass theory, namely, the two-dimensional Edwards-Anderson Hamiltonian. We show that a NADE can be trained to accurately mimic the Boltzmann distribution using unsupervised learning from system configurations generated using standard MCMC algorithms. The trained NADE is then employed as smart proposal distribution for the Metropolis-Hastings algorithm. This allows us to perform efficient MCMC simulations, which provide unbiased results even if the expectation value corresponding to the probability distribution learned by the NADE is not exact. Notably, we implement a sequential tempering procedure, whereby a NADE trained at a higher temperature is iteratively employed as proposal distribution in a MCMC simulation run at a slightly lower temperature. This allows one to efficiently simulate the spin-glass model even in the low-temperature regime, avoiding the divergent correlation times that plague MCMC simulations driven by local-update algorithms. Furthermore, we show that the NADE-driven simulations quickly sample ground-state configurations, paving the way to their future utilization to tackle binary optimization problems.

Abstract: Molecular dynamics simulations are used to study the effects of different cations on the permeation of charged polymers through flat capillaries with heights below 2 nm. Interestingly, we found that, despite being monovalent, Li+ , Na+ , and K+ cations have different effects on polymer permeation, which consequently affects their transmission speed throughout those capillaries. We attribute this phenomenon to the interplay of the cations' hydration free energies and the hydrodynamic drag in front of the polymer when it enters the capillary. Different alkali cations exhibit different surface versus bulk preferences in small clusters of water under the influence of an external electric field. This paper presents a tool to control the speed of charged polymers in confined spaces using cations.

Abstract: The initial stage of nanoparticle formation and growth in radiofrequency acetylene (C2H2) plasmas is investigated by means of a self-consistent one-dimensional fluid model. A detailed chemical kinetic scheme, containing electron impact, ion-neutral, and neutral-neutral reactions, has been developed in order to predict the underlying dust growth mechanisms and the most important dust precursors. The model considers 41 different species (neutrals, radicals, ions, and electrons) describing hydrocarbons (CnHm) containing up to 12 carbon atoms. Possible routes for particle growth are discussed. Both positive and negative ion reaction pathways are considered, as consecutive anion- and cation-molecule reactions seem to lead to a fast build up of the carbon skeleton.

Abstract: We expand on a recent study of a lattice model of interacting particles [Phys. Rev. Lett. 111, 110601 (2013)]. The adsorption isotherm and equilibrium fluctuations in particle number are discussed as a function of the interaction. Their behavior is similar to that of interacting particles in porous materials. Different expressions for the particle jump rates are derived from transition-state theory. Which expression should be used depends on the strength of the interparticle interactions. Analytical expressions for the self-and transport diffusion are derived when correlations, caused by memory effects in the environment, are neglected. The diffusive behavior is studied numerically with kinetic Monte Carlo (kMC) simulations, which reproduces the diffusion including correlations. The effect of correlations is studied by comparing the analytical expressions with the kMC simulations. It is found that the Maxwell-Stefan diffusion can exceed the self-diffusion. To our knowledge, this is the first time this is observed. The diffusive behavior in one-dimensional and higher-dimensional systems is qualitatively the same, with the effect of correlations decreasing for increasing dimension. The length dependence of both the self-and transport diffusion is studied for one-dimensional systems. For long lengths the self-diffusion shows a 1/L dependence. Finally, we discuss when agreement with experiments and simulations can be expected. The assumption that particles in different cavities do not interact is expected to hold quantitatively at low and medium particle concentrations if the particles are not strongly interacting.

Abstract: Using Brownian dynamics simulations, we investigate the dynamics of colloids confined in two-dimensional narrow channels driven by a nonuniform force Fdr(y). We considered linear-gradient, parabolic, and deltalike driving-force profiles. This driving force induces melting of the colloidal solid (i.e., shear-induced melting), and the colloidal motion experiences a transition from elastic to plastic regime with increasing Fdr. For intermediate Fdr (i.e., in the transition region) the response of the system, i.e., the distribution of the velocities of the colloidal chains õi(y), in general does not coincide with the profile of the driving force Fdr(y), and depends on the magnitude of Fdr, the width of the channel, and the density of colloids. For example, we show that the onset of plasticity is first observed near the boundaries while the motion in the central region is elastic. This is explained by: (i) (in)commensurability between the chains due to the larger density of colloids near the boundaries, and (ii) the gradient in Fdr. Our study provides a deeper understanding of the dynamics of colloids in channels and could be accessed in experiments on colloids (or in dusty plasma) with, e.g., asymmetric channels or in the presence of a gradient potential field.

Abstract: Nonequilibrium self-organized patterns formed by particles interacting through competing range interaction are driven over a substrate by an external force. We show that, with increasing driving force, the preexisted static patterns evolve into dynamic patterns either via disordered phase or depinned patterns or via the formation of nonequilibrium stripes. Strikingly, the stripes are formed either in the direction of the driving force or in the transverse direction, depending on the pinning strength. The revealed dynamical patterns are summarized in a dynamical phase diagram.

Abstract: A hybrid Monte Carlofluid modeling network is developed for an argon-hydrogen mixture, to predict the effect of small amounts of hydrogen added to a dc argon glow discharge. The species considered in the model include the Ar gas atoms, electrons, Ar+ ions and fast Ar atoms, ArH+, H+, H+2 and H+3 ions, and H atoms and H2 molecules, as well as Ar metastable atoms, sputtered Cu atoms, and the corresponding Cu+ ions. Sixty-five reactions between these species are incorporated in the model. The effect of hydrogen on various calculation results is investigated, such as the species densities, the relative role of different production and loss processes for the various species, the cathode sputtering rate and contributions by different bombarding species, and the dissociation degree of H2 and the ionization degree of Ar and Cu. The calculation results are presented and discussed for 1% H2 addition, and comparison is also made with a pure argon discharge and with only 0.1% H2 addition.

Abstract: The purpose of this Brief Report is to point out the mistake in a formula for anisotropic electron scattering, previously published in Phys. Rev. A 41, 1112 (1990), which is widely used in Monte Carlo models of gas discharges. Anisotropic electron scattering is investigated based on the screened Coulomb potential between electrons and neutral atoms. The approach is also applied for electron scattering by nonpolar neutral molecules. Differential cross sections for electron scattering by Ar, N2, and CH4 are constructed on the basis of momentum and integrated cross sections. The formula derived in this paper is useful for Monte Carlo simulations of gas discharges.

Abstract: The ordered configurations of a monolayer of interacting magnetic dipoles confined in a circular parabolic potential are investigated as a function of the dipole moment of the particles. Despite the circular confinement, we find very asymmetric ordered structures like chains and Y-shaped configurations when a magnetic field is applied parallel to the plane of the particles. The normal-mode spectrum of the particles and its dependence on the magnetic field and the strength of the dipole moment of the particles are studied. The vibrational and rotational modes of the spectrum, which are associated with the stability of the system, are investigated in detail. The number of particles is varied and we found different ordering of the particles for different values of the dipole moment and the magnetic field. A ring structure with a large number of particles is observed for high values of the dipole moment of the particles.

Abstract: In dc magnetrons the electrons emitted from the cathode may return there due to the applied magnetic field. When that happens, they can be recaptured or reflected back into the discharge, depending on the value of the reflection coefficient (RC). A 2d3v (two-dimensional in coordinate and three-dimensional in velocity space) particle-in-cellMonte Carlo model, including an external circuit, is developed to determine the role of the electron recapture in the discharge processes. The detailed discharge structure as a function of RC for two pressures (4 and 25mtorr) is studied. The importance of electron recapture is clearly manifested, especially at low pressures. The results indicate that the discharge characteristics are dramatically changed with varying RC between 0 and 1. Thus, the electron recapture at the cathode appears to be a significant mechanism in magnetron discharges and RC a very important parameter in their correct quantitative description that should be dealt with cautiously.

Abstract: We analyze the combined effect of three ingredients of an aggregation model-surface tension, particle flow and particle source-representing typical characteristics of many aggregation growth processes in nature. Through extensive numerical experiments and for different underlying lattice structures we demonstrate that the location of incoming particles and their preferential direction of flow can significantly affect the resulting general shape of the aggregate, while the surface tension controls the surface roughness. Combining all three ingredients increases the aggregate shape plasticity, yielding a wider spectrum of shapes as compared to earlier works that analyzed these ingredients separately. Our results indicate that the considered combination of effects is fundamental for modeling the polymorphic growth of a wide variety of structures in confined geometries and/or in the presence of external fields, such as rocks, crystals, corals, and biominerals.