In the present study, porous silicon films were prepared on N- and P-type silicon wafer (100) crystallographic orientations. We have investigated the influence of the different anodization parameters and silicon wafers on the properties of the obtained porous silicon layer such as thickness and porosity. The reflectance measurement of the prepared samples has presented reduction of reflection due to the porous layers and suggests the antireﬂective character of the realized porous layer.
Part of the book: Applications of Silicon Photonics in Sensors and Waveguides
In previous years, porous silicon is rapidly attracting increasing interest in various fields and has received a great deal of attention from researchers because of its potential use in a variety of industrial applications such as photovoltaic device applications. The present study conclusively suggested that in order to prepare porous silicon samples, we need to determine the optimal conditions that lead to the increase of the optical efficiency. Porous silicon layers were elaborated by the electrochemical etching method using doped 𝑝-type ⟨100⟩-oriented silicon substrate. The photoluminescence (PL) and the spectroscopic ellipsometry (SE) measurements were used to calculate the physical and optical parameters (porosity, thickness) (refractive index and extinction coefficient). This study can give a very important interest in the photovoltaic field.
Part of the book: Solar Cells
In recent years, wavelet analysis has become an effective and important computational tool in signal processing and image processing applications. Wavelet analysis is known for its successful approach to solving the problem of signal analysis in both the time domain and frequency domain. The analysis of the nonstationary signal generated by physical phenomena has posed a great challenge for various conversion techniques. Transformation techniques such as Fourier transform (FT) and short Fourier transform (STFT) fail to analyze nonstationary signals. But wavelet transform (WT) techniques may be able to efficiently analyze both stable and unstable signals. WT is able to analyze one-dimensional signals, such as audio signals and two-dimensional signals such as images. In this chapter, we discuss wavelet transduction techniques and their applications in detail and focus on the analysis and processing of the wave-encoded laser signal as one-dimensional electrical signals and its use in alarm systems. In the second stage, we filter the speech signal and determine the fundamental frequencies using wavelet transformation.
Part of the book: Recent Advances in Wavelet Transforms and Their Applications