Close-Packing of Clusters: Application to Al_100

The lowest energy configurations of close-packed clusters up to N=110 atoms with stacking faults are studied using the Monte Carlo method with Metropolis algorithm. Two types of contact interactions, a pair-potential and a many-atom interaction, are used. Enhanced stability is shown for N=12, 26, 38, 50, 59, 61, 68, 75, 79, 86, 100 and 102, of which only the sizes 38, 75, 79, 86, and 102 are pure FCC clusters, the others having stacking faults. A connection between the model potential and density functional calculations is studied in the case of Al_100. The density functional calculations are consistent with the experimental fact that there exist epitaxially grown FCC clusters starting from relatively small cluster sizes. Calculations also show that several other close-packed motifs existwith comparable total energies.Comment: 9 pages, 7 figure

AN ALTERNATIVE METHOD FOR ANALYZING FORAGE/LIVESTOCK SYSTEMS

A mixed integer program solves for profit-maximizing forage and beef enterprises. Dry matter, total digestible nutrients, and crude protein characterize livestock nutritional needs and production of warm and cool season forages.Livestock Production/Industries,

Identifying "communities" within energy landscapes

Potential energy landscapes can be represented as a network of minima linked by transition states. The community structure of such networks has been obtained for a series of small Lennard-Jones clusters. This community structure is compared to the concept of funnels in the potential energy landscape. Two existing algorithms have been used to find community structure, one involving removing edges with high betweenness, the other involving optimization of the modularity. The definition of the modularity has been refined, making it more appropriate for networks such as these where multiple edges and self-connections are not included. The optimization algorithm has also been improved, using Monte Carlo methods with simulated annealing and basin hopping, both often used successfully in other optimization problems. In addition to the small clusters, two examples with known heterogeneous landscapes, LJ_13 with one labelled atom and LJ_38, were studied with this approach. The network methods found communities that are comparable to those expected from landscape analyses. This is particularly interesting since the network model does not take any barrier heights or energies of minima into account. For comparison, the network associated with a two-dimensional hexagonal lattice is also studied and is found to have high modularity, thus raising some questions about the interpretation of the community structure associated with such partitions.Comment: 13 pages, 11 figure

Coordination motifs and large-scale structural organization in atomic clusters

The structure of nanoclusters is complex to describe due to their noncrystallinity, even though bonding and packing constraints limit the local atomic arrangements to only a few types. A computational scheme is presented to extract coordination motifs from sample atomic configurations. The method is based on a clustering analysis of multipole moments for atoms in the first coodination shell. Its power to capture large-scale structural properties is demonstrated by scanning through the ground state of the Lennard-Jones and C$_{60}$ clusters collected at the Cambridge Cluster Database.Comment: 6 pages, 7 figure

Elementary transitions and magnetic correlations in two-dimensional disordered nanoparticle ensembles

The magnetic relaxation processes in disordered two-dimensional ensembles of dipole-coupled magnetic nanoparticles are theoretically investigated by performing numerical simulations. The energy landscape of the system is explored by determining saddle points, adjacent local minima, energy barriers, and the associated minimum energy paths (MEPs) as functions of the structural disorder and particle density. The changes in the magnetic order of the nanostructure along the MEPs connecting adjacent minima are analyzed from a local perspective. In particular, we determine the extension of the correlated region where the directions of the particle magnetic moments vary significantly. It is shown that with increasing degree of disorder the magnetic correlation range decreases, i.e., the elementary relaxation processes become more localized. The distribution of the energy barriers, and their relation to the changes in the magnetic configurations are quantified. Finally, some implications for the long-time magnetic relaxation dynamics of nanostructures are discussed.Comment: 19 pages, 6 figure

Decoupling of diffusion from structural relaxation and spatial heterogeneity in a supercooled simple liquid

We report a molecular dynamics simulation of a supercooled simple monatomic glass-forming liquid. It is found that the onset of the supercooled regime results in formation of distinct domains of slow diffusion which are confined to the long-lived icosahedrally structured clusters associated with deeper minima in the energy landscape. As these domains, possessing a low-dimensional geometry, grow with cooling and percolate below $T_c$, the critical temperature of the mode coupling theory, a sharp slowing down of the structural relaxation relative to diffusion is observed. It is concluded that this latter anomaly cannot be accounted for by the spatial variation in atomic mobility; instead, we explain it as a direct result of the configuration-space constraints imposed by the transient structural correlations. We also conjecture that the observed tendency for low-dimensional clustering may be regarded as a possible mechanism of fragility.Comment: To be published in PR

A molecular dynamics simulation of polymer crystallization from oriented amorphous state

Molecular process of crystallization from an oriented amorphous state was reproduced by molecular dynamics simulation for a realistic polyethylene model. Initial oriented amorphous state was obtained by uniaxial drawing an isotropic glassy state at 100 K. By the temperature jump from 100 K to 330 K, there occurred the crystallization into the fiber structure, during the process of which we observed the developments of various order parameters. The real space image and its Fourier transform revealed that a hexagonally ordered domain was initially formed, and then highly ordered crystalline state with stacked lamellae developed after further adjustment of the relative heights of the chains along their axes.Comment: 4 pages, 3 figure

Taming the rugged energy landscape: Techniques for the production, reordering, and stabilization of selected cluster inherent structures

We report our studies of the potential energy surface (PES) of selected binary Lennard-Jones clusters. The effect of adding selected impurity atoms to a homogeneous cluster is explored. Inherent structures and transition states are found by combination of conjugate-gradient and eigenvector-following methods while the topography of the PES is mapped with the help of a disconnectivity analysis. We show that we can controllably induce new structures as well as reorder and stabilize existing structures that are characteristic of higher-lying minima.Comment: 9 pages, 9 figures, accepted for publication in J. Chem. Phy

Size reduction of complex networks preserving modularity

The ubiquity of modular structure in real-world complex networks is being the focus of attention in many trials to understand the interplay between network topology and functionality. The best approaches to the identification of modular structure are based on the optimization of a quality function known as modularity. However this optimization is a hard task provided that the computational complexity of the problem is in the NP-hard class. Here we propose an exact method for reducing the size of weighted (directed and undirected) complex networks while maintaining invariant its modularity. This size reduction allows the heuristic algorithms that optimize modularity for a better exploration of the modularity landscape. We compare the modularity obtained in several real complex-networks by using the Extremal Optimization algorithm, before and after the size reduction, showing the improvement obtained. We speculate that the proposed analytical size reduction could be extended to an exact coarse graining of the network in the scope of real-space renormalization.Comment: 14 pages, 2 figure

The Approach to Ergodicity in Monte Carlo Simulations

The approach to the ergodic limit in Monte Carlo simulations is studied using both analytic and numerical methods. With the help of a stochastic model, a metric is defined that enables the examination of a simulation in both the ergodic and non-ergodic regimes. In the non-ergodic regime, the model implies how the simulation is expected to approach ergodic behavior analytically, and the analytically inferred decay law of the metric allows the monitoring of the onset of ergodic behavior. The metric is related to previously defined measures developed for molecular dynamics simulations, and the metric enables the comparison of the relative efficiencies of different Monte Carlo schemes. Applications to Lennard-Jones 13-particle clusters are shown to match the model for Metropolis, J-walking and parallel tempering based approaches. The relative efficiencies of these three Monte Carlo approaches are compared, and the decay law is shown to be useful in determining needed high temperature parameters in parallel tempering and J-walking studies of atomic clusters.Comment: 17 Pages, 7 Figure