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Identifying optimal photovoltaic technologies for underwater applications

Improving solar energy collection in aquatic environments would allow for superior environmental monitoring and remote sensing, but the identification of optimal photovoltaic technologies for such applications is challenging as evaluation requires either field deployment or access to large water tan...

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Autores principales: Röhr, Jason A., Sartor, B. Edward, Duenow, Joel N., Qin, Zilun, Meng, Juan, Lipton, Jason, Maclean, Stephen A., Römer, Udo, Nielsen, Michael P., Zhao, Suling, Kong, Jaemin, Reese, Matthew O., Steiner, Myles A., Ekins-Daukes, N.J., Taylor, André D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9240794/
https://www.ncbi.nlm.nih.gov/pubmed/35784795
http://dx.doi.org/10.1016/j.isci.2022.104531
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author Röhr, Jason A.
Sartor, B. Edward
Duenow, Joel N.
Qin, Zilun
Meng, Juan
Lipton, Jason
Maclean, Stephen A.
Römer, Udo
Nielsen, Michael P.
Zhao, Suling
Kong, Jaemin
Reese, Matthew O.
Steiner, Myles A.
Ekins-Daukes, N.J.
Taylor, André D.
author_facet Röhr, Jason A.
Sartor, B. Edward
Duenow, Joel N.
Qin, Zilun
Meng, Juan
Lipton, Jason
Maclean, Stephen A.
Römer, Udo
Nielsen, Michael P.
Zhao, Suling
Kong, Jaemin
Reese, Matthew O.
Steiner, Myles A.
Ekins-Daukes, N.J.
Taylor, André D.
author_sort Röhr, Jason A.
collection PubMed
description Improving solar energy collection in aquatic environments would allow for superior environmental monitoring and remote sensing, but the identification of optimal photovoltaic technologies for such applications is challenging as evaluation requires either field deployment or access to large water tanks. Here, we present a simple bench-top characterization technique that does not require direct access to water and therefore circumvents the need for field testing during initial trials of development. Employing LEDs to simulate underwater solar spectra at various depths, we compare Si and CdTe solar cells, two commercially available technologies, with GaInP cells, a technology with a wide bandgap close to ideal for underwater solar harvesting. We use this method to show that while Si cells outperform both CdTe and GaInP cells under terrestrial AM1.5G solar irradiance, CdTe and GaInP cells outperform Si cells at depths >2 m, with GaInP cells operating with underwater efficiencies approaching 54%.
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spelling pubmed-92407942022-06-30 Identifying optimal photovoltaic technologies for underwater applications Röhr, Jason A. Sartor, B. Edward Duenow, Joel N. Qin, Zilun Meng, Juan Lipton, Jason Maclean, Stephen A. Römer, Udo Nielsen, Michael P. Zhao, Suling Kong, Jaemin Reese, Matthew O. Steiner, Myles A. Ekins-Daukes, N.J. Taylor, André D. iScience Article Improving solar energy collection in aquatic environments would allow for superior environmental monitoring and remote sensing, but the identification of optimal photovoltaic technologies for such applications is challenging as evaluation requires either field deployment or access to large water tanks. Here, we present a simple bench-top characterization technique that does not require direct access to water and therefore circumvents the need for field testing during initial trials of development. Employing LEDs to simulate underwater solar spectra at various depths, we compare Si and CdTe solar cells, two commercially available technologies, with GaInP cells, a technology with a wide bandgap close to ideal for underwater solar harvesting. We use this method to show that while Si cells outperform both CdTe and GaInP cells under terrestrial AM1.5G solar irradiance, CdTe and GaInP cells outperform Si cells at depths >2 m, with GaInP cells operating with underwater efficiencies approaching 54%. Elsevier 2022-06-06 /pmc/articles/PMC9240794/ /pubmed/35784795 http://dx.doi.org/10.1016/j.isci.2022.104531 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Röhr, Jason A.
Sartor, B. Edward
Duenow, Joel N.
Qin, Zilun
Meng, Juan
Lipton, Jason
Maclean, Stephen A.
Römer, Udo
Nielsen, Michael P.
Zhao, Suling
Kong, Jaemin
Reese, Matthew O.
Steiner, Myles A.
Ekins-Daukes, N.J.
Taylor, André D.
Identifying optimal photovoltaic technologies for underwater applications
title Identifying optimal photovoltaic technologies for underwater applications
title_full Identifying optimal photovoltaic technologies for underwater applications
title_fullStr Identifying optimal photovoltaic technologies for underwater applications
title_full_unstemmed Identifying optimal photovoltaic technologies for underwater applications
title_short Identifying optimal photovoltaic technologies for underwater applications
title_sort identifying optimal photovoltaic technologies for underwater applications
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9240794/
https://www.ncbi.nlm.nih.gov/pubmed/35784795
http://dx.doi.org/10.1016/j.isci.2022.104531
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