Abstract: A quantitative HPLC method was applied to determine the amounts of C-60 and C-70 present in extracts of soot produced in the electric arc reactor and in flames. The combustion method was found to yield a higher C-70/C-60 ratio (0.67) compared with the evaporation experiment where the C-70/C-60 ratio amounts to 0.27.

Abstract: We present results of Monte Carlo simulations of chains of C-60 and chains of C-70 molecules encapsulated in a single-walled carbon nanotube (SWCNT). We observe the changes in the configuration of the fullerene molecules when varying tube radius and temperature. In particular, the evolution of the pair correlation functions reveal a transition from linear harmonic chain behavior to a hard-sphere liquid upon heating, demonstrating the possibility of tuning properties of C-60- and C-70@SWCNT peapods with radius and temperature.

Abstract: We investigate the optimal orientations and positions of tubular fullerene molecules C-70, C-80 and C-90 encapsulated in single-walled carbon nanotubes (SWCNTs). We find that increasing the tube radius leads to the following succession of energetically stable regimes: 1) lying molecules positioned on the tube's long axis, 2) tilted molecules on the tube's long axis and 3) lying molecules shifted away from the tube's long axis. In the case of C-70 and C-80 molecules, standing on-axis configurations also occur. Our findings are relevant for the possible application of molecular-orientation-dependent electronic properties of fullerene nanopeapods.

Abstract: The installation of urban green infrastructure, particularly green walls, has proven to be an effective strategy for the mitigation of particulate matter (PM) pollution and the urban heat island effect. For the interaction between vegetation, PM and the local microclimate, wind flow is the main driving force. In order to investigate these interactions in detail, it is important to know how air flows through vegetation. This study proposes a method based on the DarcyForchheimer equation, where vegetation is considered as a porous medium and several plant species and the effects of plant morphological characteristics are examined both experimentally and using computer simulations. Results showed that the DarcyForchheimer model is a simple and robust way to describe air flow through vegetation regardless of its morphology. This research provides a new vision on studying aerodynamic properties of vegetation in relation to their morphology and provides opportunities for model the interaction between vegetation and its environment.

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-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 investigated the mixing and segregation of a system consisting of two different species of particles, having different charges, interacting through a pure Coulomb potential, and confined in a three-dimensional parabolic trap. The structure of the cluster and its normal mode spectrum are analyzed as a function of the relative charge and the relative number of different types of particles. We found that (a) the system can be in a mixed or segregated state depending on the relative charge ratio parameter and (b) the segregation process is mediated by a first or second order structural phase transition which strongly influences the magic cluster properties of the system.

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: We present experimental and numerical studies of the properties of a capacitively coupled 13.56 MHz discharge in a mixture of Ar and C2H2 with growing nanosize particles. It is found that at the initial stage of the growth, nanoparticles are accumulated near the sheath-plasma boundaries, where the ionization by electrons is maximal. The nanoparticles suppress the ionization due to the absorbing fast electrons and stimulate a quick change of the plasma parameters followed by a transition between different modes of discharge operation. At that moment the peaked distribution of the dust particles transforms into a flat one.

Abstract: The influence of an ellipsoid on the angular order of two-dimensional classical clusters is investigated through Brownian dynamics simulations. We found the following: (1) The presence of an ellipsoid does not influence the start of the angular melting, but reduces the rate at which the inner rings can rotate with respect to each other. (2) Even a small eccentricity of the ellipsoid leads to a stabilization of the angular order of the system. (3) Depending on the position of the ellipsoid in the cluster, a reentrant behavior in the angular order is observed before full radial melting of the cluster sets in. (4) The ellipsoid can lead to a two-step angular melting process: First, the rotation of the inner rings with respect to each other is hindered by the ellipsoid, but on further increasing the kinetic energy of the system, the ellipsoid just starts to behave as a spherical particle with different mobility. The effect of an ellipsoid on the molten system does not depend crucially on the interparticle interaction, but a softer parabolic confinement reduces the angular stabilization.