Performance of a Batch Operation Microbial Fuel Cell (MFC) with Cobalt Micronutrient Addition Based on Kinetic Models
The generation of electricity via MFC is subject to alteration by the concentration of the substrate. The objective of this study was to examine the performance of MFCs using both theoretical and experimental methods to ascertain the kinetic parameters associated with the addition of cobalt, with th...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Masyarakat Katalis Indonesia - Indonesian Catalyst Society (MKICS)
2025-04-01
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| Series: | Bulletin of Chemical Reaction Engineering & Catalysis |
| Subjects: | |
| Online Access: | https://journal.bcrec.id/index.php/bcrec/article/view/20259 |
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| Summary: | The generation of electricity via MFC is subject to alteration by the concentration of the substrate. The objective of this study was to examine the performance of MFCs using both theoretical and experimental methods to ascertain the kinetic parameters associated with the addition of cobalt, with the aim of enhancing electricity generation via MFCs. The study demonstrated the impact of varying substrate concentrations and the composition of food waste and water, with formulas 0:5, 1:4, 2:3, 3:2, 4:1, and 5:0 (w/v). The kinetics of biochemical reactions were determined by employing the Monod and Gates-Marlar equations. The Monod equations were evaluated using three distinct representation methods. The Langmuir, Lineweaver-Burk, and Eadie-Hofstee models were employed. Conversely, the electrochemical reaction rate is evaluated through the Butler-Volmer equation. The current density derived from the theoretical approach exhibited a comparable pattern to that observed in the experimental data. The maximum power density was attained at a substrate concentration of 4:1 (w/v) exceeding 25,000 mW/m². The presented model facilitated the enhancement and optimization of MFC performance. Substrate concentration and biomass concentration exert a significant influence on MFC performance, as evidenced by the analysis of variance (ANOVA) and response surface methodology (RSM). Copyright © 2025 by Authors, Published by BCREC Publishing Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0). |
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| ISSN: | 1978-2993 |