A robust correlation based on dimensional analysis to characterize microbial fuel cells
Siddharth Gadkari, Jhuma Sadhukhan
AI summary
65% confidenceA correlation for determining power density in microbial fuel cells is presented, using dimensional analysis and experimental data from various studies.
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Abstract
Abstract 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.
Key findings
- The correlation predicts nonlinear dependencies between power density and substrate concentration, solution conductivity, external resistance, and electrode spacing.
- The model is accurate in predicting power output and can be applied without significant computational resources.
- The correlation is useful for designing and optimizing microbial fuel cells by focusing experimental effort.
Keywords
Identifiers
- Journal
- Scientific Reports
- Year
- 2020