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A robust correlation based on dimensional analysis to characterize microbial fuel cells
We present a correlation for determining the power density of microbial fuel cells based on dimensional analysis. Important operational, design and biological parameters are non-dimensionalized using a selection of scaling variables. Experimental data from various microbial fuel cell studies operati...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7242356/ https://www.ncbi.nlm.nih.gov/pubmed/32439969 http://dx.doi.org/10.1038/s41598-020-65375-5 |
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author | Gadkari, Siddharth Sadhukhan, Jhuma |
author_facet | Gadkari, Siddharth Sadhukhan, Jhuma |
author_sort | Gadkari, Siddharth |
collection | PubMed |
description | We present a correlation for determining the power density of microbial fuel cells based on dimensional analysis. Important operational, design and biological parameters are non-dimensionalized using a selection of scaling variables. Experimental data from various microbial fuel cell studies operating over a wide range of system parameters are analyzed to attest accuracy of the model in predicting power output. The correlation predicts nonlinear dependencies between power density, substrate concentration, solution conductivity, external resistance, and electrode spacing. The straightforward applicability without the need for any significant computational resources, while preserving good level of accuracy; makes this correlation useful in focusing the experimental effort for the design and optimization of microbial fuel cells. |
format | Online Article Text |
id | pubmed-7242356 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-72423562020-05-29 A robust correlation based on dimensional analysis to characterize microbial fuel cells Gadkari, Siddharth Sadhukhan, Jhuma Sci Rep Article We present a correlation for determining the power density of microbial fuel cells based on dimensional analysis. Important operational, design and biological parameters are non-dimensionalized using a selection of scaling variables. Experimental data from various microbial fuel cell studies operating over a wide range of system parameters are analyzed to attest accuracy of the model in predicting power output. The correlation predicts nonlinear dependencies between power density, substrate concentration, solution conductivity, external resistance, and electrode spacing. The straightforward applicability without the need for any significant computational resources, while preserving good level of accuracy; makes this correlation useful in focusing the experimental effort for the design and optimization of microbial fuel cells. Nature Publishing Group UK 2020-05-21 /pmc/articles/PMC7242356/ /pubmed/32439969 http://dx.doi.org/10.1038/s41598-020-65375-5 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Gadkari, Siddharth Sadhukhan, Jhuma A robust correlation based on dimensional analysis to characterize microbial fuel cells |
title | A robust correlation based on dimensional analysis to characterize microbial fuel cells |
title_full | A robust correlation based on dimensional analysis to characterize microbial fuel cells |
title_fullStr | A robust correlation based on dimensional analysis to characterize microbial fuel cells |
title_full_unstemmed | A robust correlation based on dimensional analysis to characterize microbial fuel cells |
title_short | A robust correlation based on dimensional analysis to characterize microbial fuel cells |
title_sort | robust correlation based on dimensional analysis to characterize microbial fuel cells |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7242356/ https://www.ncbi.nlm.nih.gov/pubmed/32439969 http://dx.doi.org/10.1038/s41598-020-65375-5 |
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