Absolute measurement of roughness and lateral-correlation length of random surfaces by use of the simplified model of image-speckle contrast

We present a method of image-speckle contrast for the nonprecalibration measurement of the root-mean-square roughness and the lateral-correlation length of random surfaces with Gaussian correlation. We use the simplified model of the speckle fields produced by the weak scattering object in the theoretical analysis. The explicit mathematical relation shows that the saturation value of the image-speckle contrast at a large aperture radius determines the roughness, while the variation of the contrast with the aperture radius determines the lateral-correlation length. In the experimental performance, we specially fabricate the random surface samples with Gaussian correlation. The square of the image-speckle contrast is measured versus the radius of the aperture in the 4f system, and the roughness and the lateral-correlation length are extracted by fitting the theoretical result to the experimental data. Comparison of the measurement with that by an atomic force microscope shows our method has a satisfying accuracy. (C) 2002 Optical Society of America.

Mechanism study of femtosecond laser induced selective metallization (FLISM) on glass surfaces

We investigate the mechanism of selective metallization on glass surfaces with the assistance of femtosecond laser irradiation followed by electroless plating. Irradiation of femtosecond laser makes it possible to selectively deposit copper microstructures in the irradiated area on glass surfaces coated with silver nitrate films. The energy-dispersive X-ray (EDX) analyses reveal that silver atoms are produced on the surface of grooves formed by laser ablation, which serve as catalysis seeds for subsequent electroless copper plating. (C) 2008 Elsevier B.V. All rights reserved.

The autocorrelation of speckles in deep Fresnel diffraction region and characterizations of random self-affine fractal surfaces

This paper studies the correlation properties of the speckles in the deep Fresnel diffraction region produced by the scattering of rough self-affine fractal surfaces. The autocorrelation function of the speckle intensities is formulated by the combination of the light scattering theory of Kirchhoff approximation and the principles of speckle statistics. We propose a method for extracting the three surface parameters, i.e. the roughness w, the lateral correlation length xi and the roughness exponent alpha, from the autocorrelation functions of speckles. This method is verified by simulating the speckle intensities and calculating the speckle autocorrelation function. We also find the phenomenon that for rough surfaces with alpha = 1, the structure of the speckles resembles that of the surface heights, which results from the effect of the peak and the valley parts of the surface, acting as micro-lenses converging and diverging the light waves.

The accuracy of Kirchhoff's approximation in describing the far field speckles produced by random self-affine fractal surfaces

Based on the rigorous formulation of integral equations for the propagations of light waves at the medium interface, we carry out the numerical solutions of the random light field scattered from self-affine fractal surface samples. The light intensities produced by the same surface samples are also calculated in Kirchhoff's approximation, and their comparisons with the corresponding rigorous results show directly the degree of the accuracy of the approximation. It is indicated that Kirchhoff's approximation is of good accuracy for random surfaces with small roughness value w and large roughness exponent alpha. For random surfaces with larger w and smaller alpha, the approximation results in considerable errors, and detailed calculations show that the inaccuracy comes from the simplification that the transmitted light field is proportional to the incident field and from the neglect of light field derivative at the interface.

Selective metallization on insulator surfaces with femtosecond laser pulses

We report selective metallization on surfaces of insulators ( glass slides and lithium niobate crystal) based on femtosecond laser modification combined with electroless plating. The process is mainly composed of four steps: (1) formation of silver nitrate thin films on the surfaces of glass or crystal substrates; (2) generation of silver particles in the irradiated area by femtosecond laser direct writing; (3) removal of unirradiated silver nitrate films; and (4) selective electroless plating in the modified area. We discuss the mechanism of selective metallization on the insulators. Moreover, we investigate the electrical and adhesive properties of the copper microstructures patterned on the insulator surfaces, showing great potential of integrating electrical functions into lab-on-a-chip devices. (C) 2007 Optical Society of America.

Intensity-moments characterization of general pulsed paraxial beams with the Wigner distribution function

On the basis of the space-time Wigner distribution function (STWDF), we use the matrix formalism to study the propagation laws for the intensity moments of quasi-monochromatic and polychromatic pulsed paraxial beams. The advantages of this approach are reviewed. Also, a least-squares fitting method for interpreting the physical meaning of the effective curvature matrix is described by means of the STWDF. Then the concept is extended to the higher-order situation, and what me believe is a novel technique for characterizing the beam phase is presented. (C) 1999 Optical Society of America [S0740-3232(99)001009-1].

Effective recombination velocity of textured surfaces

Surface texturization is an effective way to enhance the absorption of light for optoelectronic devices but it also aggravates the surface recombination by enlarging the surface area. In order to evaluate the influence of texture structures on the surface recombination, an effective surface recombination velocity is defined which is assumed to have an equivalent recombination effect on a flat surface. Based on numerical and analytical calculation, the dependences of effective surface recombination on the pattern geometry, the surface recombination velocity, and the diffusion length are analyzed.

Improved light extraction of GaN-based LEDs with nano-roughened p-GaN surfaces

p-GaN surfaces are nano-roughened by plasma etching to improve the optical performance of GaN-based light emitting diodes (LEDs). The nano-roughened GaN present a relaxation of stress. The light extraction of the LEDs with nano-roughened surfaces is greatly improved when compared with that of the conventional LEDs without nano-roughening. PL-mapping intensities of the nano-roughened LED epi-wafers for different roughening times present two to ten orders of enhancement. The light output powers are also higher for the nano-roughened LED devices. This improvement is attributed to that nano-roughened surfaces can provide photons multiple chances to escape from the LED surfaces.

Growth of nano-structures on composition-modulated InAlAs surfaces

InAs self-organized nanostructures were grown with variant deposition thickness and growth rate on closely matched InAlAs/InP by molecular-beam epitaxy. The structural properties. of InAs and InAlAs layer were studied. It is found that the InAs morphology is insensitive to the growth conditions. Transmission electron microscopy and reflectance difference spectroscopy measurements show that the InAlAs matrix presents lateral composition modulation which gives birth to surface anisotropy. Based on the dependence of the InAs morphology on the anisotropy of the InAlAs layer, a modified Stranski-Krastanow growth mode is presented to describe the growth of the nanostructure on a composition-modulated surface.

Effects of different modified underlayer surfaces on growth and optical properties of InGaN quantum dots

InGaN/GaN quantum dots were grown on the sapphire (0 0 0 1) substrate in a metalorganic chemical vapor deposition system. The morphologies of QDs deposited on different modified underlayer (GaN) surfaces, including naturally as grown, Ga-mediated, In-mediated, and air-passivated ones, were investigated by atomic force microscopy (AFM). Photo luminescence (PL) method is used to evaluate optical properties. It is shown that InGaN QDs can form directly on the natural GaN layer. However, both the size and distribution show obvious inhomogeneities. Such a heavy fluctuation in size leads to double peaks for QDs with short growth time, and broad peaks for QDs with long growth time in their low-temperature PL spectra. QDs grown on the Ga-mediated GaN underlayer tends to coalesce. Distinct transform takes place from 3D to 2D growth on the In-mediated ones, and thus the formation of QDs is prohibited. Those results clarify Ga and In's surfactant behavior. When the GaN underlayer is passivated in the air, and together with an additional low-temperature-grown seeding layer, however, the island growth mode is enhanced. Subsequently, grown InGaN QDs are characterized by a relatively high density and an improved Gaussian-like distribution in size. Short surface diffusion length at low growth temperature accounts for that result. It is concluded that reduced temperature favors QD's 3D growth and surface passivation can provide another promising way to obtain high-density QDs that especially suits MOCVD system. (c) 2004 Elsevier Ltd. All rights reserved.

Discussion on the basic mathematical models of neurons - Double synaptic weight neuron in general-purpose neurocomputer, theory and application

Based on the introduction of the traditional mathematical models of neurons in general-purpose neurocomputer, a novel all-purpose mathematical model-Double synaptic weight neuron (DSWN) is presented, which can simulate all kinds of neuron architectures, including Radial-Basis-Function (RBF) and Back-propagation (BP) models, etc. At the same time, this new model is realized using hardware and implemented in the new CASSANN-II neurocomputer that can be used to form various types of neural networks with multiple mathematical models of neurons. In this paper, the flexibility of the new model has also been described in constructing neural networks and based on the theory of Biomimetic pattern recognition (BPR) and high-dimensional space covering, a recognition system of omni directionally oriented rigid objects on the horizontal surface and a face recognition system had been implemented on CASSANN-H neurocomputer. The result showed DSWN neural network has great potential in pattern recognition.