Silver fractal networks for surface-enhanced Raman scattering substrates

Based on diffusion-limited aggregation process, a convenient nanotechnique is demonstrated to obtain large silver fractal networks for a surface-enhanced Raman scattering (SERS)-active substrate. The silver fractal networks are of high SERS enhancement factor, large dynamical range. The observed SERS efficiency can be explained in terms of strongly localized plasmon modes relative to the single particle plasmon resonance.     

Large Relative Raman Shift for Molecules Adsorbed on Metallic Nano-particles

The enhancement of two order-of-magnitudes is observed in surface-enhanced Raman spectroscopy （SERS） of gases （CO, C2H2, C2H4, etc） adsorbed on nitric acid-roughened metal foil. In addition, some Raman lines of gases adsorbed on these active substrates show larger frequency shifts and linewidth broadening, compared with the Raman spectroscopy of free gases. Using the two-oscillator electromagnetic model, we explain this phenomenon. It is related to the large non-regular particles on the active substrate we prepared. It is found that the parameters of the surface-plasmon dispersion, the distance of molecules from the surface and the radius of particles play crucial roles on the relative large Raman shifts.     

Undercooling and Unidirectional Solidification of CuNi Alloy Melts

Cylinder-shaped CusoNi20 alloy melt is undercooled and solidified by the combination of the electromagnetic levitation technique and the flux treatment method. Nearly constant temperature gradient of 8-10 K/cm is realized for the cylindrical melts with differen~ undercooling levels at the bottom ends. The experimental results reveal that with the increase of the undercoo]ing of the melts from 35 to 220 K, the microstructures undergo transition from coarse dendrites to granular grains, unidirectional dendrites, and finally to equiaxed grains.     

Calculations of Photo-Ionization Cross Sections for Lithium Atoms

Photo-ionization cross sections for the ground and the ≤5 excited states of lithium atoms are calculated in the photoelectron energy ranging from threshold to 0.5 Rydberg. The wavefunctions for both the bound and continuum states are obtained by solving the SchrSdinger equation numerically in a symplectic scheme. Our results are in excellent agreement with the recent experimental measurements and in harmony with other theoretical calculations.     

The rate matching effect: A hidden property of aperiodic stochastic resonance

We study a system S generating Poisson events, and a corresponding dichotomous signal as well, perturbed by a system P, also generating Poisson events and a corresponding dichotomous signal. The rates of events productions for system and perturbation are gS and gP, respectively. We call S events the events produced by the system S and P events those produced by the perturbation P. We show that this simple model reproduces the essence of recent experimental and theoretical results on aperiodic stochastic resonance. More remarkably, this simplified version of aperiodic stochastic resonance allows us to discover a property that has been overlooked by the earlier research work. The rate matching condition gS=gP is the border between two distinctly different conditions: For gS<gP, the P events are attractors of the S events and for gS>gP they become repellers of the S events. The transition from the former to the latter condition is very marked and takes place in a short region of either gS or gP, depending on which is the parameter changed, thereby resulting in a discontinuous transition.     

Influence of different initial distributions on robust cooperation in scale-free networks: A comparative study

We study the evolutionary Prisoner's dilemma game on scale-free networks, focusing on the influence of different initial distributions for cooperators and defectors on the evolution of cooperation. To address this issue, we consider three types of initial distributions for defectors: uniform distribution at random, occupying the most connected nodes, and occupying the lowest-degree nodes, respectively. It is shown that initial configurations for defectors can crucially influence the cooperation level and the evolution speed of cooperation. Interestingly, the situation where defectors initially occupy the lowest-degree vertices can exhibit the most robust cooperation, compared with two other distributions. That is, the cooperation level is least affected by the initial percentage of defectors. Moreover, in this situation, the whole system evolves fastest to the prevalent cooperation. Besides, we obtain the critical values of initial frequency of defectors above which the extinction of cooperators occurs for the respective initial distributions. Our results might be helpful in explaining the maintenance of high cooperation in scale-free networks.     

Measuring distances between complex networks

A previously introduced concept of higher order neighborhoods in complex networks, [R.F.S. Andrade, J.G.V. Miranda, T.P. Lobão, Phys. Rev. E 73 (2006) 046101] is used to define a distance between networks with the same number of nodes. With such measure, expressed in terms of the matrix elements of the neighborhood matrices of each network, it is possible to compare, in a quantitative way, how far apart in the space of neighborhood matrices two networks are. The distance between these matrices depends on both the network topologies and the adopted node numberings. While the numbering of one network is fixed, a Monte Carlo algorithm is used to find the best numbering of the other network, in the sense that it minimizes the distance between the matrices. The minimal value found for the distance reflects differences in the neighborhood structures of the two networks that arise only from distinct topologies. This procedure ends up by providing a projection of the first network on the pattern of the second one. Examples are worked out allowing for a quantitative comparison for distances among distinct networks, as well as among distinct realizations of random networks.     

An empirical study of Chinese language networks

Chinese is spoken by the largest number of people in the world, and it is regarded as one of the most important languages. In this paper, we explore the statistical properties of Chinese language networks (CLNs) within the framework of complex network theory. Based on one of the largest Chinese corpora, i.e. People’s Daily Corpus, we construct two networks (CLN1 and CLN2) from two different respects, with Chinese words as nodes. In CLN1, a link between two nodes exists if they appear next to each other in at least one sentence; in CLN2, a link represents that two nodes appear simultaneously in a sentence. We show that both networks exhibit small-world effect, scale-free structure, hierarchical organization and disassortative mixing. These results indicate that in many topological aspects Chinese language shapes complex networks with organizing principles similar to other previously studied language systems, which shows that different languages may have some common characteristics in their evolution processes. We believe that our research may shed some new light into the Chinese language and find some potentially significant implications.     

Unified index to quantifying heterogeneity of complex networks

Although recent studies have revealed that degree heterogeneity of a complex network has significant impact on the network performance and function, a unified definition of the heterogeneity of a network with any degree distribution is absent. In this paper, we define a heterogeneity index 0≤H<1 to quantify the degree heterogeneity of any given network. We analytically show the existence of an upper bound of H=0.5 for exponential networks, thus explain why exponential networks are homogeneous. On the other hand, we also analytically show that the heterogeneity index of an infinite power law network is between 1 and 0.5 if and only if its degree exponent is between 2 and 2.5. We further show that for any power law network with a degree exponent greater than 2.5, there always exists an exponential network such that both networks have the same heterogeneity index. This may help to explain why 2.5 is a critical degree exponent for some dynamic behaviors on power law networks.     

Mixing navigation on networks

In this article, we propose a mixing navigation mechanism, which interpolates between random-walk and shortest-path protocol. The navigation efficiency can be remarkably enhanced via a few routers. Some advanced strategies are also designed: For non-geographical scale-free networks, the targeted strategy with a tiny fraction of routers can guarantee an efficient navigation with low and stable delivery time almost independent of network size. For geographical localized networks, the clustering strategy can simultaneously increase efficiency and reduce the communication cost. The present mixing navigation mechanism is of significance especially for information organization of wireless sensor networks and distributed autonomous robotic systems.