Structural Flyby Characterization of Nanoporosity

Recently, Ferreira da Silva et al. [3] have performed a gradient pattern analysis of a canonical sample set (CSS) of scanning force microscopy (SFM) images of p-Si. They applied the so-called Gradient Pattern Analysis to images of three typical p-Si samples distinguished by different absorption energy levels and aspect ratios. Taking into account the measures of spatial asymmetric fluctuations they interpreted the global porosity not only in terms of the amount of roughness, but rather in terms of the structural complexity (e.g., walls and fine structures as slots). This analysis has been adapted in order to operate in a OpenGL flyby environment (the StrFB code), whose application give the numerical characterization of the structure during the flyby real time. Using this analysis we compare the levels of asymmetric fragmentation of active porosity related to different materials as p-Si and "porous diamond-like" carbon. In summary we have shown that the gradient pattern analysis technique in a flyby environment is a reliable sensitive method to investigate, qualitatively and quantitatively, the complex morphology of active nanostructures

Gradient Pattern Analysis of Cosmic Structure Formation: Norm and Phase Statistics

This paper presents the preliminary results of the characterization of pattern evolution in the process of cosmic structure formation. We are applying on N-body cosmological simulations data the technique proposed by Rosa, Sharma & Valdivia (1999) and Ramos et al. (2000) to estimate the time behavior of asymmetries in the gradient field. The gradient pattern analysis is a well tested tool, used to build asymmetrical fragmentation parameters estimated over a gradient field of an image matrix able to quantify a complexity measure of nonlinear extended systems. In this investigation we work with the high resolution cosmological data simulated by the Virgo consortium, in different time steps, in order to obtain a diagnostic of the spatio-temporal disorder in the matter density field. We perform the calculations of the gradient vectors statistics, such as mean, variance, skewness, kurtosis, and correlations on the gradient field. Our main goal is to determine different dynamical regimes through the analysis of complex patterns arising from the evolutionary process of structure formation. The results show that the gradient pattern technique, specially the statistical analysis of second and third gradient moment, may represent a very useful tool to describe the matter clustering in the Universe.Comment: Accepted for publication in Physica