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Spectroscopic investigations of polycrystalline InxSb20−xAg10Se70 (0 6 x 6 15) multicomponent chalcogenides

Sharma R., Sharma S., Kumar P., Chander R., Thangaraj R., Mian M.

Materials Science Poland

2016

Vol. 34, No. 4

794--799

The composition dependence of physical properties of chalcogenides has recently been studied for their phase change properties and energy conversion. In the present work, we report the structure, composition, optical and Raman spectroscopy results for bulk polycrystalline InxSb20-xAg10Se70 (0 ≤ × ≤ 15) samples. The phase quantification and composition have been studied by using XRD and EDX techniques. The alloy composition up to 5 at.% of indium resulted in crystallization of AgSbSe2, while further increase in In content favored the formation of another chalcopyrite AgInSe2 phase yielding the solid solutions for this alloy system. A decrease in band gap up to x = 5 followed by its increase with an increase in indium concentration has been observed. The variations in shape and position of characteristic Raman bands has been used for understanding the structural modifications of the network with the variation in indium content.

Low Discrepancy Initialized Particle Swarm Optimization for Solving Constrained Optimization Problems

Pant M., Thangaraj R., Abraham A.

Fundamenta Informaticae

2009

Vol. 95, nr 4

511-531

Population based metaheuristics are commonly used for global optimization problems. These techniques depend largely on the generation of initial population. A good initial population may not only result in a better fitness function value but may also help in faster convergence. Although these techniques have been popular since more than three decades very little research has been done on the initialization of the population. In this paper, we propose a modified Particle Swarm Optimization (PSO) called Improved Constraint Particle Swarm Optimization (ICPSO) algorithm for solving constrained optimization. The proposed ICPSO algorithm is initialized using quasi random Vander Corput sequence and differs from unconstrained PSO algorithm in the phase of updating the position vectors and sorting every generation solutions. The performance of ICPSO algorithm is validated on eighteen constrained benchmark problems. The numerical results show that the proposed algorithm is a quite promising for solving constraint optimization problems.