Danilo R. Huanca

Porous silicon optical cavity structure applied to high sensitivity organic solvent sensor

The present work reports the thermal annealing process, the number of layer and electrochemical process effect in the optical response quality of Bragg and microcavity devices that were applied as organic solvent sensors. These devices have been obtained by using porous silicon (PS) technology. The optical characterization of the Bragg reflector, before annealing, showed a broad photonic band-gap structure with blue shifted and narrowed after annealing process. The electrochemical process used to obtain the PS-based device imposes the limit in the number of layers because of the chemical dissolution effect. The interface roughness minimizations in the devices have been achieved by using the double electrochemical cell setup. The microcavity devices showed to have a good sensibility for organic solvent detection. The thermal annealed device showed better sensibility feature and this result was attributed to passivation of the surface devices.

Anodic porous alumina structural characteristics study based on SEM image processing and analysis

The present work reports the porous alumina structures fabrication and their quantitative structural characteristics study based on mathematical morphology analysis by using the SEM images. The algorithm used in this work was implemented in 6.2 MATLAB software. Using the algorithm it was possible to obtain the distribution of maximum, minimum and average radius of the pores in porous alumina structures. Additionally, with the calculus of the area occupied by the pores, it was possible to obtain the porosity of the structures. The quantitative results could be obtained and related to the process fabrication characteristics, showing to be reliable and promising to be used to control the pores formation process. Then, this technique could provide a more accurate determination of pore sizes and pores distribution.

Correlation-based multi-shape granulometry with application in porous silicon nanomaterial characterization

Image-based granulometry measures the size distribution of objects in an image of granular material. Usually, algorithms based on mathematical morphology or edge detection are used for this task. We propose an entirely new approach, using cross correlations with kernels of different shapes and sizes. We use pyramidal structure to accelerate the multi-scale searching. The local maxima of cross correlations are the primary candidates for the centers of the objects. These candidate objects are filtered using criteria based on their correlations and intersection areas with other objects. Our technique spatially localizes each object with its shape, size and rotation angle. This allows us to measure many different statistics (besides the traditional objects size distribution) e.g. the shape and spatial distribution of the objects. Experiments show that the new algorithm is greatly robust to noise and can detect even very faint and noisy objects. We use the new algorithm to extract quantitative structural characteristics of Scanning Electron Microscopy (SEM) images of porous silicon layer. The new algorithm computes the size, shape and spatial distribution of the pores. We relate these quantitative results to the fabrication process and discuss the rectangle porous silicon formation mechanism. The new algorithm is a reliable tool for the SEM image processing.

Backside contact effect on the morphological and optical features of porous silicon photonic crystals

The present work reports on the effect of the type of backside contact used in the electrochemical process and their relation with the structural features and optical responses of the one-dimensional photonic crystal (PC) anodized in simple and double electrochemical cell. The PC, obtained in the single cell, showed to have thicker layers than of the PC obtained in double electrochemical cell. Additionally, the PC obtained in double cell showed highest reflectance in the band gap region than of the PCs obtained in single cell. These results suggest that the interface roughness between adjacent layers in the PC devices obtained in double electrochemical cell is minimized.

Characterization of the semi-insulating properties of AlHfO3.5 for power devices

Physical and electrical characterization of hafnium aluminates gate dielectrics was carried out to investigate their semi-insulating characteristics as passivating layer for power devices. The deposited films were annealed in pure nitrogen to simulate the thermal budget during a conventional CMOS processing. C-V measurements were performed having as a result a high-frequency behavior of the flat band voltage (VFB) and values greater than or equal to zero. On the other hand, the leakage phenomenon was modeled with a simplified electrical model using a leakage admittance YC whose influence was predominant at the accumulation region. Using X-ray reflectometry (XRR), the average thickness obtained was 15.5nm and a leakage process was inferred to occur for AlHfO3.5 due to the observed phase separation and crystallization that occurs after annealing in pure N2.

A New Correlation-Based Granulometry Algorithm with Application in Characterizing Porous Silicon Nanomaterials

Granulometry is the process of measuring the size distribution of objects in an image of granular material. Usually, algorithms based on mathematical morphology or edge detection are used for this task. We propose a entirely new approach for the granulometry using the cross correlations with circles of different sizes. This technique is primarily adequate for detecting circular-shaped objects, but it can be extended to other shapes using other correlation kernels. Experiments show that the new algorithm is greatly robust to noise and can detect even faint objects. This paper also reports the quantitative structural characteristics of the porous silicon layer based on the proposed algorithm applied to Scanning Electron Microscopy (SEM) images. The new algorithm computes the size distribution of pores and classifies the pores in circular or square ones. We relate these quantitative results to the fabrication process and discuss the square porous silicon formation mechanism. The new algorithm shows to be reliable in SEM images processing and is a promising tool to control the pores formation process.