Vipul Kheraj

Effects of Hydrogen-Dilution on Opto-Structural Properties of Hot-wire CVD Grown a-Si:H/nc-Si:H Multilayer for Photovoltaics

The multilayered thin film structure of amorphous silicon (a-Si:H) and nanocrystalline silicon (nc-Si:H) provides the possibility of bandgap tuning for fabrication of multijunction solar cells. This paper communicates a detailed analysis of optical and structural properties of a-Si:H/nc-Si:H multilayer thin films by hot-wire chemical vapor deposition at low hydrogen (H2) and silane (SiH4) flow rates. A set of multilayer films with 25 bilayers of a-Si:H/nc-Si:H are prepared using different hydrogen-dilution of SiH4 in the alternating nc-Si:H layers. The first and the second order Raman scattering studies reveal the presence of mixed phases of silicon in the nc-Si:H layers. Raman and XRD investigation of the films confirm the presence of different sizes of the silicon nanocrystals. The optical spectroscopic analysis instead of FTIR analysis of multilayer films is utilized uniquely to determine the hydrogen content in the a-Si:H/nc-Si:H multilayers and is related to the amorphous phase of the films. No significant change in hydrogen content is observed and the amorphous phase is found to decrease with increase in hydrogen dilution. Further, no quantum size effect (QSE) was observed due to the large growth time of nc-Si:H layers. Thus the experimental result shows that the bandgap of multilayer films decreases due to reduction in amorphous silicon phase, ineffective QSE and relative loss of hydrogen content.

Maximum power point computation using current–voltage data from open and short circuit regions of photovoltaic module: A teaching learning based optimization approach

Solar photovoltaic module operating with constant solar irradiance needs entire power (P)-voltage (V) curve tracing to find the maximum power point (MPP), if perturb and observe or incremental conductance algorithms are used. Therefore, there is a need of an algorithm which tracks the MPP without tracing entire P-V curve. This paper focuses on an MPP prediction method which is only based on a few data collected in the open-circuit and short-circuit regions of current (I)–voltage (V) curves of a cell or a module. The work presented here assumes I-V curve of a module to follow I-V power relation, I = aVb + c. The power model coefficients a, b, and c are determined by teaching-learning based optimization. The voltage at the MPP (Vmp) is computed by correlating the incremental conductance algorithm with the I-V power model and thereafter power at the MPP (Pmax) is obtained. The effectiveness of the algorithm is confirmed by applying it to the reported I-V curve of different types of solar cells. The obtained ...

Reduction of Fermi level pinning and recombination at polycrystalline CdTe surfaces by laser irradiation

Laser processing of polycrystalline CdTe is a promising approach that could potentially increase module manufacturing throughput while reducing capital expenditure costs. For these benefits to be realized, the basic effects of laser irradiation on CdTe must be ascertained. In this study, we utilize surface photovoltage spectroscopy (SPS) to investigate the changes to the electronic properties of the surface of polycrystalline CdTe solar cell stacks induced by continuous-wave laser annealing. The experimental data explained within a model consisting of two space charge regions, one at the CdTe/air interface and one at the CdTe/CdS junction, are used to interpret our SPS results. The frequency dependence and phase spectra of the SPS signal are also discussed. To support the SPS findings, low-temperature spectrally-resolved photoluminescence and time-resolved photoluminescence were also measured. The data show that a modest laser treatment of 250 W/cm2 with a dwell time of 20 s is sufficient to reduce the ef...

Determination of refractive index and thickness of thin-film from reflectivity spectrum using genetic algorithm

The precise determination of refractive index (n) of material and thickness (t) of thin-films are desirable for many applications in the field of optics and optoelectronics. In the proposed work, we have utilized a computational genetic algorithm (GA) to find the refractive index and the thickness from the experimentally measured reflectivity spectra of thin-film. The algorithm was implemented using the Lab VIEW as a programming tool. The obtained results show that the prepared algorithm successfully calculates the spectral dependence of refractive index and thickness of thin-films by fitting an experimentally measured reflectivity spectra with the calculated ones.

SnS2 films deposited from molecular ink as Cd-free alternative buffer layer for solar cells

This work investigates the potential of SnS2 as a Cd-free alternative buffer layer for CIGS solar cells. The suitability of SnS2 film as a buffer layer has been evaluated by numerical analysis using SCAPS software. A new simple method for preparation of SnS2 films by dip-coating from molecular ink is reported. The formation of SnS2 is confirmed by Raman spectroscopy. The films are smooth and shiny with roughness of 2-3 nm. The films are n-type with band gap of 2.6 eV and electrical conductivity of 10−3 S/cm.This work investigates the potential of SnS2 as a Cd-free alternative buffer layer for CIGS solar cells. The suitability of SnS2 film as a buffer layer has been evaluated by numerical analysis using SCAPS software. A new simple method for preparation of SnS2 films by dip-coating from molecular ink is reported. The formation of SnS2 is confirmed by Raman spectroscopy. The films are smooth and shiny with roughness of 2-3 nm. The films are n-type with band gap of 2.6 eV and electrical conductivity of 10−3 S/cm.

A novel teaching-learning based optimization approach for design of broad-band anti-reflection coatings

Abstract The design of thin-film multilayered anti-reflection (AR) coating is quite an intricate task due to highly nonlinear and complex dimensional search space, which includes many local minima. In this paper, a novel teaching-learning based optimization (TLBO) approach is employed to design ultra-low reflective coating over a broad wavelength-band using multilayer thin-film structures for optoelectronic devices. The algorithm is implemented using LabVIEW as a programming tool. Various design specific input parameters such as scanning range of wavelengths, step-size, angle of incidence, number of layers, the name and sequence of coating materials etc. are required to be fed by the user on the graphical user interface. The algorithm minimizes the average reflectivity computed over given wavelength range by tuning the thickness of layers in the multilayer stack. The reliability and evolution of design solution with iterations have been systematically investigated for different learner-sizes. Finally, using the optimized learner size and desired number of iterations, the optimum AR design is obtained in terms of the thickness of each layer for the multilayer AR coating. The effectiveness of the TLBO approach has been compared with that of an established algorithm, i.e. genetic algorithm (GA), by means of Wilcoxon singed ranked test. It is concluded that the TLBO can be a very efficient, simpler and relatively faster approach to address complex optimization problems such as broad-band AR coating designs.