Wet granular materials

Most studies on granular physics have focused on dry granular media, with no liquids between the grains. However, in geology and many real world applications (e.g. food processing, pharmaceuticals, ceramics, civil engineering, construction, and many industrial applications), liquid is present between the grains. This produces inter-grain cohesion and drastically modifies the mechanical properties of the granular media (e.g. the surface angle can be larger than 90 degrees). Here we present a review of the mechanical properties of wet granular media, with particular emphasis on the effect of cohesion. We also list several open problems that might motivate future studies in this exciting but mostly unexplored field.

Wet granular materials

All authors

Namiko Mitarai &; Franco Nori

https://doi.org/10.1080/00018730600626065

Published online:

01 February 2007

Table     

Global analysis of multiple routes of disease transmission on heterogeneous networks

In this paper, we propose and study an SIS epidemic model with multiple transmission routes on heterogeneous networks. We focus on the dynamical evolution of the prevalence. Through mathematical analysis, we obtain the basic reproduction number _R0$R_0$ by investigating the local stability of the disease-free equilibrium and also investigate the effects of various immunization schemes on disease spread. We further obtain that the disease will die out independent of the initial infections if the basic reproduction number is less than one, otherwise if the basic reproduction number is larger than one, the system converges to a unique endemic equilibrium, which is globally stable and thus the disease persists in the population. Our theoretical results are conformed by a series of numerical simulations and suggest a promising way for the control of infectious diseases with multiple routes.     

Ranking the spreading influence in complex networks

Identifying the node spreading influence in networks is an important task to optimally use the network structure and ensure the more efficient spreading in information. In this paper, by taking into account the shortest distance between a target node and the node set with the highest k$k$-core value, we present an improved method to generate the ranking list to evaluate the node spreading influence. Comparing with the epidemic process results for four real networks and the Barabási–Albert network, the parameterless method could identify the node spreading influence more accurately than the ones generated by the degree k$k$, closeness centrality, k$k$-shell and mixed degree decomposition methods. This work would be helpful for deeply understanding the node importance of a network.     

Solid-state NMR concepts for the investigation of supported transition metal catalysts and nanoparticles

In recent years, solid-state NMR spectroscopy has evolved into an important characterization tool for the study of solid catalysts and chemical processes on their surface. This interest is mainly triggered by the need of environmentally benign organic transformations (“green chemistry”), which has resulted in a large number of new catalytically active hybrid materials, which are organized on the meso- and nanoscale. Typical examples of these catalysts are supported homogeneous transition metal catalysts or transition metal nanoparticles (MNPs). Solid-state NMR spectroscopy is able to characterize both the structures of these materials and the chemical processes on the catalytic surface. This article presents recent trends both on the characterization of immobilized homogeneous transition metal catalysts and on the characterization of surface species on transition metal surfaces.     

Long-range critical wetting: Experimental phase diagram

We present ellipsometry and interferrometry experiments which allow us to observe the transition point between the standard first-order wetting and the long-range critical wetting. Moreover we provide a direct measurement of the free-energy singularities in the sequential wetting scenario of alkanes on water.     

Ordinal analysis of time series

In order to develop fast and robust methods for extracting qualitative information from non-linear time series, Bandt and Pompe have proposed to consider time series from the pure ordinal viewpoint. On the basis of counting ordinal patterns, which describe the up-and-down in a time series, they have introduced the concept of permutation entropy for quantifying the complexity of a system behind a time series. The permutation entropy only provides one detail of the ordinal structure of a time series. Here we present a method for extracting the whole ordinal information.     

Global exponential stability and existence of periodic solutions in BAM networks with delays and reaction–diffusion terms

Both exponential stability and periodic solutions are considered for a class of bi-directional associative memory (BAM) neural networks with delays and reaction–diffusion terms by constructing suitable Lyapunov functional and some analysis techniques. The general sufficient conditions are given ensuring the global exponential stability and existence of periodic solutions of BAM neural networks with delays and reaction–diffusion terms. These presented conditions are in terms of system parameters and have important leading significance in the design and applications of globally exponentially stable and periodic oscillatory neural circuits for BAM with delays and reaction–diffusion terms.     

Robust synchronization of chaotic non-autonomous systems using adaptive-feedback control

In this paper, we apply the simple adaptive-feedback control scheme to synchronize a class of chaotic non-autonomous systems. Based on the invariance principle of differential equations, some generic sufficient conditions for global asymptotic synchronization are obtained. Unlike the usual linear feedback, the variable feedback strength is automatically adapted to completely synchronize two identical systems and simple to implement in practice. As illustrative examples, synchronization of two parametrically excited chaotic pendulums and that of two 4D new systems are considered here. Numerical simulations show the proposed method is effective and robust against the effect of noise.     

Lattice Boltzmann Model for the Incompressible Navier–Stokes Equation

In this paper a lattice Boltzmann (LB) model to simulate incompressible flow is developed. The main idea is to explicitly eliminate the terms of o(M ²), where M is the Mach number, due to the density fluctuation in the existing LB models. In the proposed incompressible LB model, the pressure p instead of the mass density ρ is the independent dynamic variable. The incompressible Navier–Stokes equations are derived from the incompressible LB model via Chapman–Enskog procedure. Numerical results of simulations of the plane Poiseuille flow driven either by pressure gradient or a fixed velocity profile at entrance as well as of the 2D Womersley flow are presented. The numerical results are found to be in excellent agreement with theory.     

Evaluation of the intramolecular basis set superposition error in the calculations of larger molecules: [n]helicenes and Phe-Gly-Phe tripeptide

Correlated ab initio calculations on large systems, such as the popular MP2 (or RI-MP2) method, suffer from the intramolecular basis set superposition error (BSSE). This error is typically manifested in molecules with folded structures, characterized by intramolecular dispersion interactions. It can dramatically affect the energy differences between various conformers as well as intramolecular stabilities, and it can even impair the accuracy of the predictions of the equilibrium molecular structures. In this study, we will present two extreme cases of intramolecular BSSE, the internal stability of [n]helicene molecules and the relative energies of various conformers of phenylalanyl-glycyl-phenylalanine tripeptide (Phe-Gly-Phe), and compare the calculated data with benchmark values (experimental or high-level theoretical data). As a practical and cheap solution to the accurate treatment of the systems with large anticipated value of intramolecular BSSE, the recently developed density functional method augmented with an empirical dispersion term (DFT-D) is proposed and shown to provide very good results in both of the above described representative cases.