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A robust correlation based on dimensional analysis to characterize microbial fuel cells.

Siddharth Gadkari1,2, Jhuma Sadhukhan3,4

  • 1Centre for Environment and Sustainability, University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom. s.gadkari@surrey.ac.uk.

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This study introduces a new correlation for microbial fuel cell power density using dimensional analysis. It accurately predicts power output based on key operational and design factors, aiding in MFC optimization.

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Area of Science:

  • Electrochemistry
  • Bioengineering
  • Renewable Energy

Background:

  • Microbial fuel cells (MFCs) offer a promising route for sustainable energy generation.
  • Predicting MFC power output is crucial for their design and optimization.
  • Existing models may lack broad applicability or require complex computations.

Purpose of the Study:

  • To develop a simplified correlation for MFC power density.
  • To establish a model based on dimensional analysis.
  • To improve the prediction of MFC performance.

Main Methods:

  • Dimensional analysis was employed to identify key scaling variables.
  • Operational, design, and biological parameters were non-dimensionalized.
  • Experimental data from diverse MFC studies were used for validation.

Main Results:

  • A novel correlation for MFC power density was established.
  • The model reveals nonlinear relationships between power density and parameters like substrate concentration, conductivity, resistance, and electrode spacing.
  • The correlation demonstrated high accuracy in predicting experimental power outputs.

Conclusions:

  • The developed correlation provides an accurate and computationally inexpensive method for predicting MFC power density.
  • This tool can guide experimental efforts in MFC design and optimization.
  • The findings facilitate a better understanding of MFC performance drivers.