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Dive into the research topics where Andrés Yáñez is active.

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Featured researches published by Andrés Yáñez.


Microscopy and Microanalysis | 2007

Error Quantification in Strain Mapping Methods

Elisa Guerrero; Pedro L. Galindo; Andrés Yáñez; T. Ben; S. I. Molina

In this article a method for determining errors of the strain values when applying strain mapping techniques has been devised. This methodology starts with the generation of a thickness/defocus series of simulated high-resolution transmission electron microscopy images of InAsxP1-x/InP heterostructures and the application of geometric phase. To obtain optimal defocusing conditions, a comparison of different defocus values is carried out by the calculation of the strain profile standard deviations among different specimen thicknesses. Finally, based on the analogy of real state strain to a step response, a characterization of strain mapping error near an interface is proposed.


Archive | 2005

Strain mapping from HRTEM images

Pedro L. Galindo; Andrés Yáñez; J. Pizarro; Elisa Guerrero; T. Ben; S. I. Molina

Strain mapping is defined as a numerical image processing technique that measures the local shifts of image details around a crystal defect with respect to the ideal, defect-free, positions in the bulk. The most common algorithms for strain mapping are based on peak finding (real space) and geometric phase (Fourier space) methods. In this paper, we discuss both algorithms and propose an alternative algorithm (Peak Pairs) based on the detection of pairs of intensity maxima in the affine transformed space which exhibits good behavior at dislocations. Quantitative results are reported from experiments to determine local stresses in different types of quantum heterostructures.


Ultramicroscopy | 2017

Evaluation of high-quality image reconstruction techniques applied to high-resolution Z-contrast imaging

Guillermo Bárcena-Gonzalez; M P Guerrero-Lebrero; Elisa Guerrero; Andrés Yáñez; D. Fernández-Reyes; D. González; Pedro L. Galindo

High-quality image reconstruction techniques allow the generation of high pixel density images from a set of low-resolution micrographs. In general, these techniques consist of two main steps, namely, accurate registration, and formulation of an appropriate forward image model via some restoration method. There exist a wide variety of algorithms to cope with both stages and depending on their practical applications, some methods can outperform others, since they can be sensitive to the assumed data model, noise, drift, etc. When dealing with images generated by Z-contrast scanning transmission electron microscopes, a current trend is based on non-rigid approximations in the registration stage. In our work we aimed at reaching similar accuracy but addressing the most complex calculations in the reconstruction stage, instead of in the registration stage (as the non-rigid approaches do), but using a much smaller number of images. We review some of the most significant methods and address their shortcomings when they are applied to the field of microscopy. Simulated images with known targets will be used to evaluate and compare the main approaches in terms of quality enhancement and computing time. In addition, a procedure to determine the reference image will be proposed to minimise the global drift on the series. The best registration and restoration strategies will be applied to experimental images in order to point up the enhanced capability of this high quality image reconstruction methodology in this field.


Journal of Physics: Conference Series | 2014

A methodology for the extraction of quantitative information from electron microscopy images at the atomic level

Pedro L. Galindo; J. Pizarro; Elisa Guerrero; M P Guerrero-Lebrero; G. Scavello; Andrés Yáñez; B M Núñez-Moraleda; J M Maestre; D. L. Sales; M. Herrera; S. I. Molina

In this paper we describe a methodology developed at the University of Cadiz (Spain) in the past few years for the extraction of quantitative information from electron microscopy images at the atomic level. This work is based on a coordinated and synergic activity of several research groups that have been working together over the last decade in two different and complementary fields: Materials Science and Computer Science. The aim of our joint research has been to develop innovative high-performance computing techniques and simulation methods in order to address computationally challenging problems in the analysis, modelling and simulation of materials at the atomic scale, providing significant advances with respect to existing techniques. The methodology involves several fundamental areas of research including the analysis of high resolution electron microscopy images, materials modelling, image simulation and 3D reconstruction using quantitative information from experimental images. These techniques for the analysis, modelling and simulation allow optimizing the control and functionality of devices developed using materials under study, and have been tested using data obtained from experimental samples.


international conference on artificial neural networks | 2011

Genetic algorithms applied to the design of 3D photonic crystals

Agustín Morgado-León; Alejandro Escuín; Elisa Guerrero; Andrés Yáñez; Pedro L. Galindo; Lorenzo Sanchis

We aim at determining the optimal configuration of photonic crystal structures capable of carrying out a certain optical task. An exhaustive search would require a high computational cost, in this work we show how genetic algorithms can be applied to reliably find an optimal topology of threedimensional photonic crystals. The fitness, representing the performance of each potential configuration, is calculated by means of finite element analysis. Different experiments are presented in order to illustrate the potential of this 3D design approach.


Journal of Physics: Conference Series | 2010

Through-focal HAADF-STEM of buried nanostructures

M P Guerrero-Lebrero; J. Pizarro; Elisa Guerrero; Pedro L. Galindo; Andrés Yáñez; S. I. Molina

High-Angle Annular Dark-Field Scanning Transmission Electron Microscopy (HAADF-STEM) in combination with strain mapping techniques provides a powerful tool for quantitative analysis of crystalline semiconductor materials. Due to the complex interaction of a focused probe and a sample in HAADF, the calculation of each pixel in a simulation process requires a complete multislice iteration, making the overall computing process a rather demanding task in time and memory. SICSTEM is a parallel software code recently developed for running on the University of Cadiz Supercomputer (3.75 Tflops) that allows the simulation of images from large nanostructures containing more than one million atoms. The software has been designed to be able to generate not only one dimensional line scans or two dimensional images, but also to perform optical sectioning in the STEM simulation process, providing an easy way to simulate 3D HAADF-STEM images. In this work we consider GaAs capped GaSb nanostructures epitaxially oriented on a GaAs substrate. A methodology has been developed by combining the through-focal series STEM imaging and image analysis to estimate shape and position of buried GaSb nanostructures.


Archive | 2008

HAADF-STEM image simulation of large scale nanostructures

Pedro L. Galindo; J. Pizarro; A. Rosenauer; Andrés Yáñez; Elisa Guerrero; S. I. Molina

The combination of strain measurements1 and the analysis of High Angle Annular Dark Field (HAADF) Scanning Transmission Electron Microscopy (STEM) images constitutes a powerful approach to investigate strained heterostructures on the nanometer scale and has proved to be extremely powerful for characterizing nanomaterials2,3.


Micron | 2018

Correcting sample drift using Fourier harmonics

Guillermo Bárcena-Gonzalez; M P Guerrero-Lebrero; Elisa Guerrero; D.F. Reyes; V. Braza; Andrés Yáñez; B. Nuñez-Moraleda; D. González; Pedro L. Galindo

During image acquisition of crystalline materials by high-resolution scanning transmission electron microscopy, the sample drift could lead to distortions and shears that hinder their quantitative analysis and characterization. In order to measure and correct this effect, several authors have proposed different methodologies making use of series of images. In this work, we introduce a methodology to determine the drift angle via Fourier analysis by using a single image based on the measurements between the angles of the second Fourier harmonics in different quadrants. Two different approaches, that are independent of the angle of acquisition of the image, are evaluated. In addition, our results demonstrate that the determination of the drift angle is more accurate by using the measurements of non-consecutive quadrants when the angle of acquisition is an odd multiple of 45°.


Archive | 2008

Influence of atomic displacements due to elastic strain in HAADF-STEM simulated images

Elisa Guerrero; Andrés Yáñez; Pedro L. Galindo; J. Pizarro; S. I. Molina

In this work, we analyze the influence of atomic displacements due to elastic strain in HAADF-STEM simulated images. This methodology is demonstrated on an InP/InAsxP(1−x) nanowire heterostructure theoretical model under strained/unstrained conditions. Since the HRTEM image simulation requires an enormous amount of computing power, all simulations have been obtained using a parallel version of HAADFSTEM simulation software[1] running in the University of Cadiz supercomputer (3.8 Tflops). This program is able to simulate HAADF-STEM images from nanostructures containing more than one million of atoms in a few days.


Archive | 2005

Quantification of the influence of TEM operation parameters on the error of HREM image matching

J. Pizarro; Elisa Guerrero; Pedro L. Galindo; Andrés Yáñez; T. Ben; S. I. Molina

In this paper we describe a pattern recognition system implemented to determine thickness and defocus from HRTEM simulated images. A specific task has been designed to quantify the influence of certain operation parameters of a transmission electron microscope in the global recognition error rate. This influence allows us to estimate human recognition confidence when applying pattern matching to the determination of thickness and defocus from HRTEM maps. The images considered in this task correspond to InP with the sphalerite crystalline structure and were simulated using the EMS computer software package.

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T. Ben

University of Cádiz

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