Collective Charge Fluctuations in Single-Electron Processes on Nano-Networks

Using numerical modeling we study emergence of structure and structure-related nonlinear conduction properties in the self-assembled nanoparticle films. Particularly, we show how different nanoparticle networks emerge within assembly processes with molecular bio-recognition binding. We then simulate the charge transport under voltage bias via single-electron tunnelings through the junctions between nanoparticles on such type of networks. We show how the regular nanoparticle array and topologically inhomogeneous nanonetworks affect the charge transport. We find long-range correlations in the time series of charge fluctuation at individual nanoparticles and of flow along the junctions within the network. These correlations explain the occurrence of a large nonlinearity in the simulated and experimentally measured current-voltage characteristics and non-Gaussian fluctuations of the current at the electrode.Comment: 10 pages, 7 figure

Complex networks theory for analyzing metabolic networks

One of the main tasks of post-genomic informatics is to systematically investigate all molecules and their interactions within a living cell so as to understand how these molecules and the interactions between them relate to the function of the organism, while networks are appropriate abstract description of all kinds of interactions. In the past few years, great achievement has been made in developing theory of complex networks for revealing the organizing principles that govern the formation and evolution of various complex biological, technological and social networks. This paper reviews the accomplishments in constructing genome-based metabolic networks and describes how the theory of complex networks is applied to analyze metabolic networks.Comment: 13 pages, 2 figure

Jamming in complex networks with degree correlation

We study the effects of the degree-degree correlations on the pressure congestion J when we apply a dynamical process on scale free complex networks using the gradient network approach. We find that the pressure congestion for disassortative (assortative) networks is lower (bigger) than the one for uncorrelated networks which allow us to affirm that disassortative networks enhance transport through them. This result agree with the fact that many real world transportation networks naturally evolve to this kind of correlation. We explain our results showing that for the disassortative case the clusters in the gradient network turn out to be as much elongated as possible, reducing the pressure congestion J and observing the opposite behavior for the assortative case. Finally we apply our model to real world networks, and the results agree with our theoretical model

Near mean-field behavior in the generalized Burridge-Knopoff earthquake model with variable range stress transfer

Simple models of earthquake faults are important for understanding the mechanisms for their observed behavior in nature, such as Gutenberg-Richter scaling. Because of the importance of long-range interactions in an elastic medium, we generalize the Burridge-Knopoff slider-block model to include variable range stress transfer. We find that the Burridge-Knopoff model with long-range stress transfer exhibits qualitatively different behavior than the corresponding long-range cellular automata models and the usual Burridge-Knopoff model with nearest-neighbor stress transfer, depending on how quickly the friction force weakens with increasing velocity. Extensive simulations of quasiperiodic characteristic events, mode-switching phenomena, ergodicity, and waiting-time distributions are also discussed. Our results are consistent with the existence of a mean-field critical point and have important implications for our understanding of earthquakes and other driven dissipative systems.Comment: 24 pages 12 figures, revised version for Phys. Rev.

Confined water in the low hydration regime

Molecular dynamics results on water confined in a silica pore in the low hydration regime are presented. Strong layering effects are found due to the hydrophilic character of the substrate. The local properties of water are studied as function of both temperature and hydration level. The interaction of the thin films of water with the silica atoms induces a strong distortion of the hydrogen bond network. The residence time of the water molecules is dependent on the distance from the surface. Its behavior shows a transition from a brownian to a non-brownian regime approaching the substrate in agreement with results found in studies of water at contact with globular proteins.Comment: 7 pages with 12 figures (RevTeX4). To be published on J. Chem. Phy

Vortex Lattice Melting in 2D Superconducting Networks and Films

We carry out MC studies of 2D superconducting networks, in an applied magnetic field, for square and honeycomb geometries. We consider both dilute systems (f=1/q) and systems near full frustration (f=1/2-1/q). For the dilute case (which models a film as q->infinity), we find two transitions: at T_c(f)~1/q there is a depinning transition from a pinned to a floating vortex lattice; at T_m(f)~constant the floating vortex lattice melts into an isotropic liquid. We analyze this melting according to the Kosterlitz- Thouless theory of dislocation mediated melting, and find that the melting is weakly first order. For the case near full frustration, the system can be described in terms of the density of defects in an otherwise fully frustrated vortex pattern. We find pinned solid, floating solid, and liquid defect phases, as well as a higher sharp transition corresponding to the disordering of the fully frustrated background.Comment: 55 pages, RevTex3.0, 25 figures (available by mail by contacting [email protected]

Modeling of solvent flow effects in enzyme catalysis under physiological conditions

A stochastic model for the dynamics of enzymatic catalysis in explicit, effective solvents under physiological conditions is presented. Analytically-computed first passage time densities of a diffusing particle in a spherical shell with absorbing boundaries are combined with densities obtained from explicit simulation to obtain the overall probability density for the total reaction cycle time of the enzymatic system. The method is used to investigate the catalytic transfer of a phosphoryl group in a phosphoglycerate kinase-ADP-bis phosphoglycerate system, one of the steps of glycolysis. The direct simulation of the enzyme-substrate binding and reaction is carried out using an elastic network model for the protein, and the solvent motions are described by multiparticle collision dynamics, which incorporates hydrodynamic flow effects. Systems where solvent-enzyme coupling occurs through explicit intermolecular interactions, as well as systems where this coupling is taken into account by including the protein and substrate in the multiparticle collision step, are investigated and compared with simulations where hydrodynamic coupling is absent. It is demonstrated that the flow of solvent particles around the enzyme facilitates the large-scale hinge motion of the enzyme with bound substrates, and has a significant impact on the shape of the probability densities and average time scales of substrate binding for substrates near the enzyme, the closure of the enzyme after binding, and the overall time of completion of the cycle.Comment: 15 pages in double column forma