Study of black silicon wafer through wet chemical etching for parametric optimization in enhancing solar cell performance by pc1d numerical simulation
Black silicon (BSi) fabrication via surface texturization of Si-wafer in recent times has become an attractive concept regarding photon trapping and improved light absorption properties for photovoltaic applications. In this study, surface texturization has been conducted on mono-crystalline Si(100)...
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my.uniten.dspace-260642023-05-29T17:06:29Z Study of black silicon wafer through wet chemical etching for parametric optimization in enhancing solar cell performance by pc1d numerical simulation Arafat M.Y. Islam M.A. Mahmood A.W.B. Abdullah F. Kiong T.S. Amin N. 57226548627 57220973693 57226550425 56613644500 57216824752 7102424614 Black silicon (BSi) fabrication via surface texturization of Si-wafer in recent times has become an attractive concept regarding photon trapping and improved light absorption properties for photovoltaic applications. In this study, surface texturization has been conducted on mono-crystalline Si(100) wafer using a wet chemical anisotropic etching process with IPA:KOH solution to form micro-pyramidal surface structures. Moreover, the optimized properties of the fabricated BSi wafers are used for numerical simulation using PC1D software to analyze the performance of the solar cell and establish the correlation among relevant parameters. Effects such as doping concentration, texturization, passivation, and anti-reflection coating of BSi on the solar cell performance have numerically been investigated. Results show that textured surface obtained from the wet chemical anisotropic etching process has successfully reduced the reflectance of the BSi wafer and surpassed the solar cell efficiency by 2%, which is mainly attributed to the optical confinement of the textured pyramids on the surface with a height of 1�2 �m and angles of 70 degrees. Furthermore, the doping concentration of the p-type wafer and n-type emitter were optimized to be 1 � 1016 cm?3 and 1 � 1018 cm?3, respectively. In the case of device optimization, the SiO2 passivation layer with a refractive index of 1.48 and the Si3N4 ARC layer with a refractive index of 2.015 has been identified as the best combination for the solar cell performance. These optimized parameters eventually result in 23.14% conversion efficiency from numerical simulation for solar cells that use black silicon wafers as fabricated in this study. � 2021 by the authors. Licensee MDPI, Basel, Switzerland. Final 2023-05-29T09:06:29Z 2023-05-29T09:06:29Z 2021 Article 10.3390/cryst11080881 2-s2.0-85111934748 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111934748&doi=10.3390%2fcryst11080881&partnerID=40&md5=4dba63dce4db9b5e3a8f8b5018e4807c https://irepository.uniten.edu.my/handle/123456789/26064 11 8 881 All Open Access, Gold MDPI AG Scopus |
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Black silicon (BSi) fabrication via surface texturization of Si-wafer in recent times has become an attractive concept regarding photon trapping and improved light absorption properties for photovoltaic applications. In this study, surface texturization has been conducted on mono-crystalline Si(100) wafer using a wet chemical anisotropic etching process with IPA:KOH solution to form micro-pyramidal surface structures. Moreover, the optimized properties of the fabricated BSi wafers are used for numerical simulation using PC1D software to analyze the performance of the solar cell and establish the correlation among relevant parameters. Effects such as doping concentration, texturization, passivation, and anti-reflection coating of BSi on the solar cell performance have numerically been investigated. Results show that textured surface obtained from the wet chemical anisotropic etching process has successfully reduced the reflectance of the BSi wafer and surpassed the solar cell efficiency by 2%, which is mainly attributed to the optical confinement of the textured pyramids on the surface with a height of 1�2 �m and angles of 70 degrees. Furthermore, the doping concentration of the p-type wafer and n-type emitter were optimized to be 1 � 1016 cm?3 and 1 � 1018 cm?3, respectively. In the case of device optimization, the SiO2 passivation layer with a refractive index of 1.48 and the Si3N4 ARC layer with a refractive index of 2.015 has been identified as the best combination for the solar cell performance. These optimized parameters eventually result in 23.14% conversion efficiency from numerical simulation for solar cells that use black silicon wafers as fabricated in this study. � 2021 by the authors. Licensee MDPI, Basel, Switzerland. |
| author2 |
57226548627 |
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57226548627 Arafat M.Y. Islam M.A. Mahmood A.W.B. Abdullah F. Kiong T.S. Amin N. |
| format |
Article |
| author |
Arafat M.Y. Islam M.A. Mahmood A.W.B. Abdullah F. Kiong T.S. Amin N. |
| spellingShingle |
Arafat M.Y. Islam M.A. Mahmood A.W.B. Abdullah F. Kiong T.S. Amin N. Study of black silicon wafer through wet chemical etching for parametric optimization in enhancing solar cell performance by pc1d numerical simulation |
| author_sort |
Arafat M.Y. |
| title |
Study of black silicon wafer through wet chemical etching for parametric optimization in enhancing solar cell performance by pc1d numerical simulation |
| title_short |
Study of black silicon wafer through wet chemical etching for parametric optimization in enhancing solar cell performance by pc1d numerical simulation |
| title_full |
Study of black silicon wafer through wet chemical etching for parametric optimization in enhancing solar cell performance by pc1d numerical simulation |
| title_fullStr |
Study of black silicon wafer through wet chemical etching for parametric optimization in enhancing solar cell performance by pc1d numerical simulation |
| title_full_unstemmed |
Study of black silicon wafer through wet chemical etching for parametric optimization in enhancing solar cell performance by pc1d numerical simulation |
| title_sort |
study of black silicon wafer through wet chemical etching for parametric optimization in enhancing solar cell performance by pc1d numerical simulation |
| publisher |
MDPI AG |
| publishDate |
2023 |
| _version_ |
1806426251414470656 |
| score |
13.211869 |