Performance of nanowire decorated mono- and multi-crystalline Si solarcells

Es, Firat; Demircioglu, Olgu; Günöven, Mete; Kulakçı, Mustafa; Ünalan, Hüsnü Emrah; Turan, Raşit

doi:10.1016/j.physe.2013.01.002

Cited by 9 publications

(7 citation statements)

References 14 publications

(17 reference statements)

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“…During the last few years in the field of photovoltaics, novel etching techniques by varying methodology, time and acid concentration have been proposed to realize pyramidal textures with a much wider range of lateral sizes [35], random patterns [29], or with shallow pits with a worm-like morphology [36] like those analyzed in the present study. The evaluation of the real surface area, which is clearly a multi-scale property dependent on the number of length scales of roughness, influences both reflection [36], which is drastically diminishing by increasing the real surface area in acid etched multi-crystalline silicon, and the applicability of the electrochemical capacitancevoltage method, which also requires the knowledge of the real surface area to profile the surface doping concentration of silicon solar cells [37].…”

Section: Silicon Solar Cells With Anti-reflecting Coatingmentioning

confidence: 95%

“…Although the agreement with experimental data was fairly good in case of metallic surfaces subjected to different types of machining (spark-machined, grit-blasted, sand-blasted surfaces, see, e.g., [6]), the applicability to textured surfaces should be a matter of discussion. This research is motivated by the fact that in the recent years we have seen a rise in designing and tailoring surface roughness in order to optimize adhesion in biological systems [22][23][24], capillary forces promoting the movement of liquids [25,26], thermal and electric contact conductance [18,19], frictional effects [20,27], wave transmission [28] and also light reflectance properties fundamental for high efficiency solar energy conversion [29]. In most of such cases, surfaces present complex textures over multiple scales, probably far beyond the capabilities of models based on the RPT and also not just simply fractals.…”

Section: Introductionmentioning

confidence: 99%

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Topological characterization of antireflective and hydrophobic rough surfaces: are random process theory and fractal modeling applicable?

Borri¹,

Paggi²

2015

J. Phys. D: Appl. Phys.

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The random process theory (RPT) has been widely applied to predict the joint probability distribution functions (PDFs) of asperity heights and curvatures of rough surfaces. A check of the predictions of RPT against the actual statistics of numerically generated random fractal surfaces and of real rough surfaces has been only partially undertaken. The present experimental and numerical study provides a deep critical comparison on this matter, providing some insight into the capabilities and limitations in applying RPT and fractal modeling to antireflective and hydrophobic rough surfaces, two important types of textured surfaces. A multi-resolution experimental campaign by using a confocal profilometer with different lenses is carried out and a comprehensive software for the statistical description of rough surfaces is developed. It is found that the topology of the analyzed textured surfaces cannot be fully described according to RPT and fractal modeling. The following complexities emerge: (i) the presence of cut-offs or bi-fractality in the power-law powerspectral density (PSD) functions; (ii) a more pronounced shift of the PSD by changing resolution as compared to what expected from fractal modeling; (iii) inaccuracy of the RPT in describing the joint PDFs of asperity heights and curvatures of textured surfaces; (iv) lack of resolution-invariance of joint PDFs of textured surfaces in case of special surface treatments, not accounted by fractal modeling.

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Section: Silicon Solar Cells With Anti-reflecting Coatingmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Topological characterization of antireflective and hydrophobic rough surfaces: are random process theory and fractal modeling applicable?

Borri¹,

Paggi²

2015

J. Phys. D: Appl. Phys.

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“…Roughness is a very important feature of real surfaces due to its major role in influencing interface phenomena like contact, adhesion, friction, wear, transport, and heat transfer. [1][2][3][4][5][6][7][8][9][10][11] Rough surfaces appear irregular and show characteristics of randomness. Hence, the random process theory (RPT), previously used to describe random noise signals, 12 has been pioneeringly applied to the analysis of roughness by Longuet-Higgins.…”

Section: Introductionmentioning

confidence: 99%

Topology simulation and contact mechanics of bifractal rough surfaces*

Borri

Paggi

2016

Proceedings of the Institution of Mechanical Engineers, Part J:

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A numerical method to generate bifractal surfaces due to a modification of the slope of the power spectral density function in the low-or high-frequency range is proposed. The method has been applied to simulate real surfaces of Ginkgo Biloba leaf scanned at two different magnifications by matching the corresponding experimental power spectral densities. Slight differences have been found in the statistical distributions of the asperity heights and curvatures for the lowest magnification that had marginal influence on the frictionless normal contact response of the surface. For highest magnification, however, the statistics of the simulated numerical surface were quite different from those of the real one, leading also to a significant difference in the normal contact results.

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“…Different methods have been used in the diffusion process including solid-source doping, spin on doping, POCL 3 gas ambient doping, and so on. 7 Surface recombinations, which are associated with the concentration of minority carriers, are limited by the rate at which minority carriers move toward the surface. 4 Sheet resistance beneath the contact differs from the semiconductor R S beside the contact.…”

Section: Introductionmentioning

confidence: 99%

Process optimization of doping conditions for (100) P-type monocrystalline silicon solar cell using response surface methodology

2013

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The effect of time and temperature on the sheet resistance (R S ) and carrier concentration (N A ) of (100) P-type monocrystalline Si was investigated. Phosphorus-doped n þ -emitters were fabricated through solid-source doping in a quartz tube furnace. The process variable values for 13 runs were proposed by response surface methodology (RSM). The optimized values for time and temperature predicted by RSM were 56 min and 1045°C, respectively, for a sheet resistance of 41.7 Ω∕□ and a carrier concentration of 3.7E18 cm −3 . Optimization-based fabrication was found to be in close agreement with the optimized values. Parameter optimization using RSM could be valuable in achieving predetermined dopant variables in optoelectronic devices as well as in reducing the surface recombinations and series resistance of highly efficient Si solar cells. , and Mat Jafri: Process optimization of doping conditions for (100) P-type monocrystalline. , and Mat Jafri: Process optimization of doping conditions for (100) P-type monocrystalline. , and Mat Jafri: Process optimization of doping conditions for (100) P-type monocrystalline. , and Mat Jafri: Process optimization of doping conditions for (100) P-type monocrystalline. , and Mat Jafri: Process optimization of doping conditions for (100) P-type monocrystalline. , and Mat Jafri: Process optimization of doping conditions for (100) P-type monocrystalline.

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Performance of nanowire decorated mono- and multi-crystalline Si solarcells

Cited by 9 publications

References 14 publications

Topological characterization of antireflective and hydrophobic rough surfaces: are random process theory and fractal modeling applicable?

Topological characterization of antireflective and hydrophobic rough surfaces: are random process theory and fractal modeling applicable?

Topology simulation and contact mechanics of bifractal rough surfaces*

Process optimization of doping conditions for (100) P-type monocrystalline silicon solar cell using response surface methodology

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