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Porous silicon (PS) films were investigated by Raman, and photoluminescence spectroscopies using different laser excitations at 488.0, 514.5, 632.8, and 782.0 nm. The exposure of PS layers to high laser powers causes an increase in the 480 cm −1 Raman intensity and a shift and enhancement of the PL emission. A laser-assisted surface reaction is proposed to explain these observations. The analysis of the first-and second-order Raman spectra showed that the band gaps of the PS films are indirect as in bulk c-Si. The Raman phonon and the PL spectra and also the spectral distribution of the linear polarization degree (LPD) of PS layers were shown to be dependent on the laser excitation energy. This dependence cannot be explained within the quantum confinement model. A mechanism for the PL emission in PS layers is presented in which the radioactive recombination of electron-hole pairs occurs in localized centres (the Si -O -SiR moieties) at the pore/crystallite interface. These quasi-molecular centres are Jahn-Teller active, i.e. the radioactive recombination is a phonon-assisted phenomenon.

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. IntroductionGranulometry is the process of measuring sizes of different objects/grains in an image of granular material. The granulometric curve or pattern spectrum of an image is the histogram of objects as the function of radius. The objective of the granulometry is, given an image, to obtain its pattern spectrum. There are two main groups of image-based granulometry algorithms: Mathematical morphology-based algorithms;  Edge detection-based algorithms.Mathematical morphology-based granulometry obtains the pattern spectrum of an image without explicitly segmenting it. Dougherty et al. present a popular morphologybased granulometry for binary images (1). Raimundo et al. used this algorithm to characterize porous material (2). Unfortunately, this algorithm cannot be directly applied to grayscale images. If the original image is grayscale, the algorithm must somehow convert it into a binary image and any binarization discards many important information. Vincent presents a morphology-based granulometry for grayscale images (3). A demonstration program of this algorithm with source code is available at (4). This algorithm seems to be scarcely used in practice. Indeed, the output of this algorithm is highly non-intuitive, difficult to be used in practice. It represents the pattern spectrum as the "sum of pixel values in opened image as a function of radius." Ordinaly, the user wants to obtain simply the "quantity of objects as a function of radius." Moreover, in many applications the spatial localization of each grain is important, and this information is not provided by grayscale morphology granulometry. Edge detection-based granulometry detects the edges of the image using conventional gradient operators and thresholding (5). Then, it delimitates the objects using the edges. Edge-detection is a noise-sensible operation and may not be reliable, especially in blurred low-contrast images. This paper presents a entirely ne...

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The present work reports the two types of silicon nanotubes fabrication. The tubular structures based on silicon have been fabricated by immersing mesoporous silicon layer into aqueous electrolyte based on a mixture of NH 4 F and NiSO 4 . Similar results are achieved by immersing mesoporous silicon layer that was formed from the silicon wafer previously metallized on its smooth surface with aluminum and after annealing in a N 2 environment. In this case, either silicon or nickel nanotubes can easily be formed only by tuning the pH level of the ammonium fluoride solution. The range of the inner diameter of these tubes varies from 40 to 110 nm, whereas the mean value of their tube-wall thicknesses is about 25 nm. The SNT characterization by energy-dispersive X-ray spectroscopy, X-ray diffraction spectroscopy and their open-circuit potential behaviors show that the silicon tubes have been formed by an etch-stop process where the space-charge region on the silicon side plays a key role for tubes formation. In this paper, the SNT formation mechanism in the aqueous mixture solution of NH 4 F:NiSO 4 using the mesoporous silicon layer as a starting material is discussed. We show that this proposed procedure is new and easy to implement.

In this paper, we report the results of the investigation about the optical properties of one‐dimensional photonic crystals based on porous silicon multilayer structures having unit cells with optical properties that vary as a function of the device thickness. These devices were obtained by anodizing crystalline silicon in electrolyte aqueous solution of HF at different concentrations. The effective refractive index and extinction coefficients, of porous silicon layers of unit cells had been obtained by fitting the experimental reflectance spectra using the transfer matrix method. The effective–refractive indexes, for devices obtained in electrolyte solution of high HF concentration, were shown to have a significant gradient in the depth of the layers, whereas it was low (negligible) for devices obtained in electrolyte solution with low HF concentration, but the mechanical stability of these latter devices is poor. It was found that this fragility depends on the layer number and upon their physical thicknesses ratio.