Browsing by Author "Mallick, Subha Prakash"

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Effect of Passivation Layer on the Thin Film Perovskite Random Lasers
(2020-05-01)
Mallick, Subha Prakash
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Hong, Yu-Heng
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Chen, Lih-Ren
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Kao, Tsung Sheng
;
Lu, Tien-Chang
Novel functionalities of disorder-induced scattering effect in random lasers, attributed to low spatial coherence, draw remarkable attention in high-contrast to superior quality speckle-free imaging applications. This paper demonstrates perovskite-polystyrene (PS)-based random lasing action with robust optical performance at room temperature. Optical characterizations are carried out upon perovskite thin films addition with polystyrene of different mixing concentrations (wt.%). A low threshold lasing operation is achieved with an increasing concentration of polystyrene, accompanying a wavy surface texture with high surface roughness. The rough surface dominating multiple scattering effects leads to enhanced feedback efficiency. Moreover, this study also elucidates efficient fabrication process steps for the development of high quality and durable PS-based random lasers. With the advantages of reduced coherent artifacts and low spatial coherence, speckle free projection images of the USAF (U. S. Air Force MIL-STD-150A standard of 1951) resolution test chart are shown for different PS-based random lasers.
Metaheuristic optimization approach and computational study on advanced mathematical modeling of solar cell
(2020-02-01)
Mallick, Subha Prakash
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光電工程學系
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Department of Photonics
A solar cell current usually depends on bandgap, carrier lifetime, diffusion length, diffusion constant, ideality factor, and so on. This article proposes a model that shows direct dependency of bandgap in the solar cell current equation. It is based on foundation principles satisfactory of a single junction being extended to multi-junction solar cell applications with different bandgaps. Different proven optimization techniques such as the Gauss-Newton optimization, Levenberg-Marquardt optimization, differential evolution algorithm, and whale optimization algorithm (WOA) were used for parameter extraction and optimization. To demonstrate the better optimization of model data with experimental data, further analysis of results was carried out on the basis of percentage deviation and error comparison. Complete comprehensive and comparative analysis of results of error and percentage deviation from different standard iterative optimization techniques proves the WOA as one of the best optimization techniques among all. As a result, the WOA offers a better optimal solution of model parameters with the best convergence of model data with the experimental data that shows the smallest possible value of error and minimum percentage deviation. (C) 2020 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license.