Theoretical study of band alignment in nano-porous ZnO interacting with substituted Phthalocyanines

The aim of this work is the theoretical study of the band alignment between the two components of a hybrid organic-inorganic solar-cell. The working organic molecules are metal tetra-sulphonated phthalocyanines (M-Pc) and the inorganic material is nano-porous ZnO growth in the 001 direction. The theoretical calculations are being made using the density functional theory (DFT) using a GGA functional with the SIESTA code, which projects electron wave functions and density onto a real space grid and uses as basis set a linear combination of numerical, finite-range localized atomic orbitals. We also used the DFT+U method included in the code that allows a semi-empirical inclusion of electronic correlations in the description of electronic spectra for systems such as zinc oxide.

Image analysis by moment invariants using a set of step-like basis functions

Moment invariants have been thoroughly studied and repeatedly proposed as one of the most powerful tools for 2D shape identification. In this paper a set of such descriptors is proposed, being the basis functions discontinuous in a finite number of points. The goal of using discontinuous functions is to avoid the Gibbs phenomenon, and therefore to yield a better approximation capability for discontinuous signals, as images. Moreover, the proposed set of moments allows the definition of rotation invariants, being this the other main design concern. Translation and scale invariance are achieved by means of standard image normalization. Tests are conducted to evaluate the behavior of these descriptors in noisy environments, where images are corrupted with Gaussian noise up to different SNR values. Results are compared to those obtained using Zernike moments, showing that the proposed descriptor has the same performance in image retrieval tasks in noisy environments, but demanding much less computational power for every stage in the query chain.