Statistical modeling of solar cell using Taguchi method and TCAD tool

This paper focuses on optimizing silicon based solar cell fabrication using Taguchi Optimization Method (TOM). Optimization focused on 3 parameters namely doping concentration of boron, creating phosphorus PN-junction and energy used for ion-implantation with 2 noise factors, Diffuse time and diffus...

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Main Authors: Bahrudin M.S., Abdullah S.F., Ahmad I.
Other Authors: 55603412800
Format: Conference paper
Published: 2023
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spelling my.uniten.dspace-302902023-12-29T15:46:22Z Statistical modeling of solar cell using Taguchi method and TCAD tool Bahrudin M.S. Abdullah S.F. Ahmad I. 55603412800 14319069500 12792216600 ion-implantation and Silvaco TCAD software PN-junction Solar cell Taguchi Optimization Method Boron Computer simulation Experiments Optimization Phosphorus Semiconductor doping Signal to noise ratio Silicon solar cells Solar cells Taguchi methods Testing Best value Doping concentration Electrical testing Fill factor Junction depth Noise factor Orthogonal array P-n junction Recombination process Shallow junction Silicon-based Silvaco Simulation environment Solar cell fabrication Statistical modeling Taguchi optimization method TCAD software Semiconductor junctions This paper focuses on optimizing silicon based solar cell fabrication using Taguchi Optimization Method (TOM). Optimization focused on 3 parameters namely doping concentration of boron, creating phosphorus PN-junction and energy used for ion-implantation with 2 noise factors, Diffuse time and diffuse temperature. The aim is to have a shallow junction in order to decrease the recombination process but higher fill factor (FF) for better efficiency. Fabricating are done in computer simulation environment by Silvaco TCAD software that also conducting an electrical testing for measurement. Each factor (product from the parameters through TOM) has 2 levels of best values taken from the previous researches. In this research, L8 orthogonal array consists of 8 set of different combination of experiment has been done. Optimized values are analyzed by finding Signal to Noise Ratio (SNR) of each experiment and applied it on Larger the Better (LTB) for highest FF and Smaller the Better (STB) for shallowest junction depth. Result reveal that boron at concentration of 5.0�10 15 cm-3, phosphorus at concentration of 2.0�10 16 cm-3, and energy at 10 keV gave a result of 0.3 um ? 0.5 um for junction depth and stable FF value of 0.8 at any noise factor contributing efficiency of 15% to 16%. As a conclusion, TOM has achieved predicting the best solution for optimizing silicon solar cell fabrication. � 2012 IEEE. Final 2023-12-29T07:46:22Z 2023-12-29T07:46:22Z 2012 Conference paper 10.1109/SMElec.2012.6417073 2-s2.0-84874136502 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84874136502&doi=10.1109%2fSMElec.2012.6417073&partnerID=40&md5=ddff966877bd5577b3d5a20fd74438cc https://irepository.uniten.edu.my/handle/123456789/30290 6417073 1 5 Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic ion-implantation and Silvaco TCAD software
PN-junction
Solar cell
Taguchi Optimization Method
Boron
Computer simulation
Experiments
Optimization
Phosphorus
Semiconductor doping
Signal to noise ratio
Silicon solar cells
Solar cells
Taguchi methods
Testing
Best value
Doping concentration
Electrical testing
Fill factor
Junction depth
Noise factor
Orthogonal array
P-n junction
Recombination process
Shallow junction
Silicon-based
Silvaco
Simulation environment
Solar cell fabrication
Statistical modeling
Taguchi optimization method
TCAD software
Semiconductor junctions
spellingShingle ion-implantation and Silvaco TCAD software
PN-junction
Solar cell
Taguchi Optimization Method
Boron
Computer simulation
Experiments
Optimization
Phosphorus
Semiconductor doping
Signal to noise ratio
Silicon solar cells
Solar cells
Taguchi methods
Testing
Best value
Doping concentration
Electrical testing
Fill factor
Junction depth
Noise factor
Orthogonal array
P-n junction
Recombination process
Shallow junction
Silicon-based
Silvaco
Simulation environment
Solar cell fabrication
Statistical modeling
Taguchi optimization method
TCAD software
Semiconductor junctions
Bahrudin M.S.
Abdullah S.F.
Ahmad I.
Statistical modeling of solar cell using Taguchi method and TCAD tool
description This paper focuses on optimizing silicon based solar cell fabrication using Taguchi Optimization Method (TOM). Optimization focused on 3 parameters namely doping concentration of boron, creating phosphorus PN-junction and energy used for ion-implantation with 2 noise factors, Diffuse time and diffuse temperature. The aim is to have a shallow junction in order to decrease the recombination process but higher fill factor (FF) for better efficiency. Fabricating are done in computer simulation environment by Silvaco TCAD software that also conducting an electrical testing for measurement. Each factor (product from the parameters through TOM) has 2 levels of best values taken from the previous researches. In this research, L8 orthogonal array consists of 8 set of different combination of experiment has been done. Optimized values are analyzed by finding Signal to Noise Ratio (SNR) of each experiment and applied it on Larger the Better (LTB) for highest FF and Smaller the Better (STB) for shallowest junction depth. Result reveal that boron at concentration of 5.0�10 15 cm-3, phosphorus at concentration of 2.0�10 16 cm-3, and energy at 10 keV gave a result of 0.3 um ? 0.5 um for junction depth and stable FF value of 0.8 at any noise factor contributing efficiency of 15% to 16%. As a conclusion, TOM has achieved predicting the best solution for optimizing silicon solar cell fabrication. � 2012 IEEE.
author2 55603412800
author_facet 55603412800
Bahrudin M.S.
Abdullah S.F.
Ahmad I.
format Conference paper
author Bahrudin M.S.
Abdullah S.F.
Ahmad I.
author_sort Bahrudin M.S.
title Statistical modeling of solar cell using Taguchi method and TCAD tool
title_short Statistical modeling of solar cell using Taguchi method and TCAD tool
title_full Statistical modeling of solar cell using Taguchi method and TCAD tool
title_fullStr Statistical modeling of solar cell using Taguchi method and TCAD tool
title_full_unstemmed Statistical modeling of solar cell using Taguchi method and TCAD tool
title_sort statistical modeling of solar cell using taguchi method and tcad tool
publishDate 2023
_version_ 1806424528034725888