Spectral and nonlinear optical characterization of ZnO nanocomposites

The spectral and nonlinear optical characteristics of nano ZnO and its composites are investigated. The fluorescence behaviour of nano colloids of ZnO has been studied as a function of the excitation wavelength and there is a red shift in emission peak with excitation wavelength. Apart from the observation of the reported ultra violet and green emissions, our results reveal that additional blue emissions at 420 nm and 490 nm are developed with increasing particle size. Systematic studies on nano ZnO have indicated the presence of luminescence due to excitonic emissions when excited with 255 nm as well as significant contribution from surface defect states when excited with 325 nm. In the weak confinement regime, the third-order optical susceptibility χ(3) increases with increasing particle size (R) and annealing temperature (T) and a R2 and T2.5 dependence of χ(3) is obtained for nano ZnO. ZnO nanocolloids exhibit induced absorption whereas the self assembled films of ZnO exhibit saturable absorption due to saturation of linear absorption of ZnO defect states and electronic effects. ZnO nanocomposites exhibit negative nonlinear index of refraction which can be attributed to two photon absorption followed by weak free carrier absorption. The increase of the third-order nonlinearity in the composites can be attributed to the enhancement of exciton oscillator strength. The nonlinear response of ZnO nanocomposites is wavelength dependent and switching from induced absorption to saturable absorption has been observed at resonant wavelengths. Such a change-over is related to the interplay of plasmon/exciton band bleach and optical limiting mechanisms. This study is important in identifying the spectral range and the composition over which the nonlinear material acts as an optical limiter. ZnO based nanocomposites are potential materials for enhanced and tunable light emission and for the development of nonlinear optical devices with a relatively small optical limiting threshold.

Size dependent fluorescence spectroscopy of nanocolloids of ZnO

In this article we present size dependent spectroscopic observations of nanocolloids of ZnO. ZnO is reported to show two emission bands, an ultraviolet (UV) emission band and another in the green region. Apart from the known band gap 380 nm and impurity 530 nm emissions, we have found some peculiar features in the fluorescence spectra that are consistent with the nanoparticle size distribution. Results show that additional emissions at 420 and 490 nm are developed with particle size. The origin of the visible band emission is discussed. The mechanism of the luminescence suggests that UV luminescence of ZnO colloid is related to the transition from conduction band edge to valence band, and visible luminescence is caused by the transition from deep donor level to valence band due to oxygen vacancies and by the transition from conduction band to deep acceptor level due to impurities and defect states. A correlation analysis between the particle size and spectroscopic observations is also discussed.

Analysis and Optimization of Machining Process Using Evolutionary Algorithms

To ensure quality of machined products at minimum machining costs and maximum machining effectiveness, it is very important to select optimum parameters when metal cutting machine tools are employed. Traditionally, the experience of the operator plays a major role in the selection of optimum metal cutting conditions. However, attaining optimum values each time by even a skilled operator is difficult. The non-linear nature of the machining process has compelled engineers to search for more effective methods to attain optimization. The design objective preceding most engineering design activities is simply to minimize the cost of production or to maximize the production efficiency. The main aim of research work reported here is to build robust optimization algorithms by exploiting ideas that nature has to offer from its backyard and using it to solve real world optimization problems in manufacturing processes.In this thesis, after conducting an exhaustive literature review, several optimization techniques used in various manufacturing processes have been identified. The selection of optimal cutting parameters, like depth of cut, feed and speed is a very important issue for every machining process. Experiments have been designed using Taguchi technique and dry turning of SS420 has been performed on Kirlosker turn master 35 lathe. Analysis using S/N and ANOVA were performed to find the optimum level and percentage of contribution of each parameter. By using S/N analysis the optimum machining parameters from the experimentation is obtained.Optimization algorithms begin with one or more design solutions supplied by the user and then iteratively check new design solutions, relative search spaces in order to achieve the true optimum solution. A mathematical model has been developed using response surface analysis for surface roughness and the model was validated using published results from literature.Methodologies in optimization such as Simulated annealing (SA), Particle Swarm Optimization (PSO), Conventional Genetic Algorithm (CGA) and Improved Genetic Algorithm (IGA) are applied to optimize machining parameters while dry turning of SS420 material. All the above algorithms were tested for their efficiency, robustness and accuracy and observe how they often outperform conventional optimization method applied to difficult real world problems. The SA, PSO, CGA and IGA codes were developed using MATLAB. For each evolutionary algorithmic method, optimum cutting conditions are provided to achieve better surface finish.The computational results using SA clearly demonstrated that the proposed solution procedure is quite capable in solving such complicated problems effectively and efficiently. Particle Swarm Optimization (PSO) is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. From the results it has been observed that PSO provides better results and also more computationally efficient.Based on the results obtained using CGA and IGA for the optimization of machining process, the proposed IGA provides better results than the conventional GA. The improved genetic algorithm incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. Finally, a comparison among these algorithms were made for the specific example of dry turning of SS 420 material and arriving at optimum machining parameters of feed, cutting speed, depth of cut and tool nose radius for minimum surface roughness as the criterion. To summarize, the research work fills in conspicuous gaps between research prototypes and industry requirements, by simulating evolutionary procedures seen in nature that optimize its own systems.

Photoluminescence Studies Of Microwave Assisted Synthesized Zno Micro Structures

ZnO micro particles in the range 0.4-0.6 μm were synthesized by microwave irradiation method. The XRD analysis reveals that the sample is in the wurtzite phase with orientation along the (101) plane. SAED pattern of the sample reveals the single crystalline nature of the micro grains. TEM images show the formation of cylindrical shaped ZnO micro structures with hexagonal faces. The optical phonon modes were slightly shifted in the Raman spectrum,attributed to the presence of various crystalline defects and laser induced local heating at the grain boundaries. A broad transmission profile was observed in the FTIR spectrum from 1550-3400 cm-1 which falls in the atmospheric transparency window region. PL spectrum centered at 500 nm with a broad band in the region 420-570 nm comprised of different emission peaks attributed to transition between defect levels. Various emission levels in the sample were expliained with a band diagram