Characterization of epitaxial heavily-doped silicon regions formed by HWCVD using Micro-Raman and Micro-Photoluminescence Spectroscopy
Characterization of epitaxial heavily-doped silicon regions formed by HWCVD using Micro-Raman and Micro-Photoluminescence Spectroscopy
We report on the characterization of heavily boron doped epitaxial silicon regions grown in a hot-wire chemical vapor deposition tool, using micro-Raman and photoluminescence spectroscopy. In particular, the use of this approach for emitter fabrication in an interdigitated back contact silicon solar cell is studied, by analyzing its suitability concerning selective growth, uniformity, anneal time, and luminescent defects. We show that by reducing the silane flow rate, both the required postanneal time and intensity of defect luminescence are reduced. Furthermore, we show that selective area growth does not affect either the quality of the films or the sharpness of the resulting lateral doping profile. The uniformity of the doping is shown to be better than that achieved using laser doping.
Epitaxy, hot-wire chemical vapor deposition (HWCVD), laser doping, silicon, spectral photoluminescence (PL)
813-819
Rahman, Tasmiat
e7432efa-2683-484d-9ec6-2f9c568d30cd
Nguyen, Hieu T.
4d696a0e-438c-44dd-9807-d75a82459b4a
Tarazona, Antulio
c6ae87c5-c746-4f89-9ff0-9e7b6874e94f
Shi, Jingxing
2632e5a1-10ba-4b05-9bec-f86facfcee66
Han, Young Joon
d96ceb63-3997-4719-b08e-fbe7e7ce777f
Franklin, Evan
93c5d1dc-a75c-4ebc-8e42-57d49bba8be2
Macdonald, Daniel
1ece9ed2-8749-4cd1-9f12-1bb7d7882f0e
Boden, Stuart A.
01b35080-37e4-48ca-bdc7-bde7971002d6
May 2018
Rahman, Tasmiat
e7432efa-2683-484d-9ec6-2f9c568d30cd
Nguyen, Hieu T.
4d696a0e-438c-44dd-9807-d75a82459b4a
Tarazona, Antulio
c6ae87c5-c746-4f89-9ff0-9e7b6874e94f
Shi, Jingxing
2632e5a1-10ba-4b05-9bec-f86facfcee66
Han, Young Joon
d96ceb63-3997-4719-b08e-fbe7e7ce777f
Franklin, Evan
93c5d1dc-a75c-4ebc-8e42-57d49bba8be2
Macdonald, Daniel
1ece9ed2-8749-4cd1-9f12-1bb7d7882f0e
Boden, Stuart A.
01b35080-37e4-48ca-bdc7-bde7971002d6
Rahman, Tasmiat, Nguyen, Hieu T., Tarazona, Antulio, Shi, Jingxing, Han, Young Joon, Franklin, Evan, Macdonald, Daniel and Boden, Stuart A.
(2018)
Characterization of epitaxial heavily-doped silicon regions formed by HWCVD using Micro-Raman and Micro-Photoluminescence Spectroscopy.
IEEE Journal of Photovoltaics, 8 (3), .
(doi:10.1109/JPHOTOV.2018.2818284).
Abstract
We report on the characterization of heavily boron doped epitaxial silicon regions grown in a hot-wire chemical vapor deposition tool, using micro-Raman and photoluminescence spectroscopy. In particular, the use of this approach for emitter fabrication in an interdigitated back contact silicon solar cell is studied, by analyzing its suitability concerning selective growth, uniformity, anneal time, and luminescent defects. We show that by reducing the silane flow rate, both the required postanneal time and intensity of defect luminescence are reduced. Furthermore, we show that selective area growth does not affect either the quality of the films or the sharpness of the resulting lateral doping profile. The uniformity of the doping is shown to be better than that achieved using laser doping.
Text
08336871
- Version of Record
More information
Accepted/In Press date: 1 March 2018
e-pub ahead of print date: 12 April 2018
Published date: May 2018
Keywords:
Epitaxy, hot-wire chemical vapor deposition (HWCVD), laser doping, silicon, spectral photoluminescence (PL)
Identifiers
Local EPrints ID: 421612
URI: http://eprints.soton.ac.uk/id/eprint/421612
PURE UUID: ad8ef38c-5270-4b1c-b093-cb74f79003e4
Catalogue record
Date deposited: 15 Jun 2018 16:31
Last modified: 16 Jul 2024 01:46
Export record
Altmetrics
Contributors
Author:
Tasmiat Rahman
Author:
Hieu T. Nguyen
Author:
Antulio Tarazona
Author:
Jingxing Shi
Author:
Young Joon Han
Author:
Evan Franklin
Author:
Daniel Macdonald
Author:
Stuart A. Boden
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics