Synthesis of SnS thin films via galvanostatic electrodeposition and fabrication of CdS/SnS heterostructure for photovoltaic applications

In this work SnS thin films were electrochemically deposited on ITO coated glass substrate by galvanostatic electrodeposition at different pH of the plating bath. The working electrode used in these studies was low cost high purity graphite rod. The as-deposited films were found to be smooth, pinhole free and well adherent to the substrate with no powdery deposition. EDX measurements revealed that all the SnS films were non-stoichiometric in nature with variation from Sn-excess to S-excess compositions. XRD pattern showed that all the SnS thin films had orthorhombic polycrystalline structure. The direct bandgaps of all the films were found to be in the range 1.54-1.58 eV. ITO/SnS/In structure exhibited linear current-voltage characteristics, establishing the ohmic nature of both ITO/SnS and SnS/In junctions. Furthermore, SnS layer was grown on CdS film using electrodeposition technique. The heterostructure ITO/CdS/SnS/In was characterized under dark and illuminated conditions. From forward biased I-V characteristics several junction parameters like barrier height, diode ideality factor and series resistance of the heterostructure were extracted using Cheung model.     

Ion beam synthesis of metal-quantum dots for photonic applications

Although electronics technologies have made great advances in device speed, optical devices can function in the time domain inaccessible to electronics. In the time domain less than 1 ps, optical devices have no competition. Photonic or optical devices are designed to switch and process light signals without converting them to electronic form. The major advantages that these devices offer are speed and preservation of bandwidth. The switching is accomplished through changes in refractive index of the material that are proportional to the light intensity. The third-order optical susceptibility, χ⁽³⁾, known as the optical Kerr susceptibility which is related to the non-linear part of the total refractive index, is the nonlinearity which provides this particular feature. Future opportunities in photonic switching and information processing will depend critically on the development of improved photonic materials with enhanced Kerr susceptibilities, as these materials are still in a relatively early stage of development. Different glass systems are now under investigation to increase their nonlinearity by introducing a variety of modifiers into the glass-network. Ion implantation is an attractive method for inducing colloid formation at a high local concentration unattainable by the melt-glass fabrication process and for confining the non-linearities to specific patterned regions in a variety of host matrices. Recent works on metal-ion implanted colloid generation in bulk fused silica glasses have shown that these nanocluster-glass composites under favourable circumstances have significant enhancement of χ⁽³⁾ with picosecond to femtosecond temporal responses.     

An analytic analysis of the pion decay constant in three-flavoured chiral perturbation theory

A representation of the two-loop contribution to the pion decay constant in SU(3) chiral perturbation theory is presented. The result is analytic up to the contribution of the three (different) mass sunset integrals, for which an expansion in their external momentum has been taken. We also give an analytic expression for the two-loop contribution to the pion mass based on a renormalized representation and in terms of the physical eta mass. We find an expansion of \(F_{\pi }\) and \(M_{\pi }^2\) in the strange-quark mass in the isospin limit, and we perform the matching of the chiral SU(2) and SU(3) low-energy constants. A numerical analysis demonstrates the high accuracy of our representation, and the strong dependence of the pion decay constant upon the values of the low-energy constants, especially in the chiral limit. Finally, we present a simplified representation that is particularly suitable for fitting with available lattice data.     

Performance of different normal dispersion fibers to generate triangular optical pulses

Optical and Quantum Electronics - The nonlinear scattering of two non-collinear Gaussian pulses with different central frequencies and lengths, incident on the periodic stacks of semiconductor...     

Excess noise generation during spectral broadening in a microstructured fiber

We observe that nanojoule femtosecond pulses that are spectrally broadened in a microstructured fiber acquire excess noise. The excess noise is manifested as an increase in the noise floor of the rf spectrum of the photocurrent from a photodetector illuminated by the pulse train from the laser oscillator. Measurements are made of the intensity dependence of the excess noise for both 100 fs and sub-10 fs pulses. The excess noise is very strong for 100 fs pulses, but barely measurable for sub-10 fs pulses. A rigorous quantum treatment of the nonlinear propagation of ultrashort pulses predicts that, for a fixed generated bandwidth, the amount of excess noise decreases with pulse duration, in agreement with the experimental results.     

Automated leukocyte recognition using fuzzy divergence

This paper aims at introducing an automated approach to leukocyte recognition using fuzzy divergence and modified thresholding techniques. The recognition is done through the segmentation of nuclei where Gamma, Gaussian and Cauchy type of fuzzy membership functions are studied for the image pixels. It is in fact found that Cauchy leads better segmentation as compared to others. In addition, image thresholding is modified for better recognition. Results are studied and discussed.     

Efficient dispersion tailoring by designing alternately arranged dispersion compensating fibers and fiber amplifiers to create self-similar parabolic pulses

The parabolic similariton pulse formation by alternate arrangements of passive and active dispersion compensating fibers (DCFs) is presented here. These combinations of passive and active DCFs with constant core radii and constant nonlinearities are suggested as equivalent profiles of a dispersion tailored fiber amplifier in normal dispersion regime. The dispersion tailored fibers, usually known as dispersion decreasing fibers (DDFs) in normal dispersion regime, are capable of producing linearly chirped parabolic self-similar pulses. The DDF is designed and optimized with proper choice of fiber parameters so that considerable variation of nonlinearity can be achieved, which in turn enhances the effective gain coefficient of the fiber. Inclusion of this nonlinear variation along the DDF amplifier length leads to obtain the simulated output pulses with very small misfit parameters with respect to perfect parabolic pulse at sufficiently reduced optimum length. At the same time to avoid the fabrication difficulties of the DDF, the alternately arranged passive and active DCFs are suggested as suitable alternatives of the DDF. The performances of the cascaded systems for generation of self-similar parabolic pulses are compared with that of the DDF amplifier as well as combined systems consisting of DCFs with equal gain. The results show that the proposed alternately arranged cascaded system with less pumping requirements, are efficient enough to produce similar parabolic pulses as compared to the previously designed DDF, even when considerable amount of splice loss at each joint is included.     

A novel frequency encoded all optical CNOT gate exploiting difference frequency generation and implementation of fast binary adders using frequency encoding and nonlinear dielectric films

Optics has an important role in logic implementation and computation is established in two and half decades by many researchers. Recently frequency encoding technique is established. This technique does not suffer from intensity dependent loss problems like other schemes. Amorphous dielectric thin films with reflecting edges can also be used for logic realization and has very fast response speed. It also does not use any semiconductor device and simple to construct. In this communication the authors have proposed all optical CNOT gate using frequency encoded difference frequency generation exploiting nonlinear response of some material and implementation of binary adders by CNOT gate and dielectric thin film AND gate.     

He(I) and He(II) populations in the Nagoya TPD plasma machine

A collisional-radiative model is used to explain the He(I) population densities observed by Otsuka, Ikee and Ishii in their TPD plasma machine. It is shown that a plasma model, which is partially optically thick to He(II) Lyman radiation, can explain the experimentally observed He(II) population density at T_e=3.17 eV. The agreement between the experimental and calculated He(II) population densities observed by Otsuka and others is shown to be due to an error in their calculations.     

Artificial neural network‐based modeling of snow properties using field data and hyperspectral imagery

This study attempts to model snow wetness and snow density of Himalayan snow cover using a combination of Hyperspectral image processing and Artificial Neural Network (ANN). Initially, a total of 300 spectral signature measurements, synchronized with snow wetness and snow density, were collected in the field. The spectral reflectance of snow was then modeled as a function of snow properties using ANN. Four snow wetness and three snow density models were developed. A strong correlation was observed in near‐infrared and shortwave‐infrared region. The correlation analysis of ANN modeled snow density and snow wetness showed a strong linear relationship with field‐based data values ranging from 0.87–0.90 and 0.88–0.91, respectively. Our results indicate that an Artificial Intelligence (AI) approach, using a combination of Hyperspectral image processing and ANN, can be efficiently used to predict snow properties (wetness and density) in the Himalayan region. Recommendations for resource managers

• Snow properties, such as snow wetness and snow density are mainly investigated through field‐based survey but rugged terrains, difficult weather conditions, and logistics management issues establish remote sensing as an efficient alternative to monitor snow properties, especially in the mountain environment.
• Although Hyperspectral remote sensing is a powerful tool to conduct the quantitative analysis of the physical properties of snow, only a few studies have used hyperspectral data for the estimation of snow density and wetness in the Himalayan region. This could be because of the lack of synchronized snow properties data with field‐based spectral acquisitions.
• In combination with Hyperspectral image processing, Artificial Neural Network (ANN) can be a useful tool for effective snow modeling because of its ability to capture and represent complex input‐output relationships.
• Further research into understanding the applicability of neural networks to determine snow properties is required to obtain results from large snow cover areas of the Himalayan region.