Statistical modeling and performance optimization of a two-chamber microbial fuel cell by response surface methodology
Microbial fuel cell, as a promising technology for simultaneous power production and waste treatment, has received a great deal of attention in recent years; however, generation of a relatively low power density is the main limitation towards its commercial application. This study contributes toward...
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my.um.eprints.345472022-09-15T04:06:59Z http://eprints.um.edu.my/34547/ Statistical modeling and performance optimization of a two-chamber microbial fuel cell by response surface methodology Naseer, Muhammad Nihal Zaidi, Asad A. Khan, Hamdullah Kumar, Sagar bin Owais, Muhammad Taha Abdul Wahab, Yasmin Dutta, Kingshuk Jaafar, Juhana Hamizi, Nor Aliya Islam, Mohammad Aminul Hussin, Hanim Badruddin, Irfan Anjum Alrobei, Hussein QD Chemistry TP Chemical technology Microbial fuel cell, as a promising technology for simultaneous power production and waste treatment, has received a great deal of attention in recent years; however, generation of a relatively low power density is the main limitation towards its commercial application. This study contributes toward the optimization, in terms of maximization, of the power density of a microbial fuel cell by employing response surface methodology, coupled with central composite design. For this optimization study, the interactive effect of three independent parameters, namely (i) acetate concentration in the influent of anodic chamber; (ii) fuel feed flow rate in anodic chamber; and (iii) oxygen concentration in the influent of cathodic chamber, have been analyzed for a two-chamber microbial fuel cell, and the optimum conditions have been identified. The optimum value of power density was observed at an acetate concentration, a fuel feed flow rate, and an oxygen concentration value of 2.60 mol m(-3), 0.0 m(3), and 1.00 mol m(-3), respectively. The results show the achievement of a power density of 3.425 W m(-2), which is significant considering the available literature. Additionally, a statistical model has also been developed that correlates the three independent factors to the power density. For this model, R-2, adjusted R-2, and predicted R-2 were 0.839, 0.807, and 0.703, respectively. The fact that there is only a 3.8% error in the actual and adjusted R-2 demonstrates that the proposed model is statistically significant.</p> MDPI 2021-10 Article PeerReviewed Naseer, Muhammad Nihal and Zaidi, Asad A. and Khan, Hamdullah and Kumar, Sagar and bin Owais, Muhammad Taha and Abdul Wahab, Yasmin and Dutta, Kingshuk and Jaafar, Juhana and Hamizi, Nor Aliya and Islam, Mohammad Aminul and Hussin, Hanim and Badruddin, Irfan Anjum and Alrobei, Hussein (2021) Statistical modeling and performance optimization of a two-chamber microbial fuel cell by response surface methodology. Catalysts, 11 (10). ISSN 2073-4344, DOI https://doi.org/10.3390/catal11101202 <https://doi.org/10.3390/catal11101202>. 10.3390/catal11101202 |
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QD Chemistry TP Chemical technology Naseer, Muhammad Nihal Zaidi, Asad A. Khan, Hamdullah Kumar, Sagar bin Owais, Muhammad Taha Abdul Wahab, Yasmin Dutta, Kingshuk Jaafar, Juhana Hamizi, Nor Aliya Islam, Mohammad Aminul Hussin, Hanim Badruddin, Irfan Anjum Alrobei, Hussein Statistical modeling and performance optimization of a two-chamber microbial fuel cell by response surface methodology |
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Microbial fuel cell, as a promising technology for simultaneous power production and waste treatment, has received a great deal of attention in recent years; however, generation of a relatively low power density is the main limitation towards its commercial application. This study contributes toward the optimization, in terms of maximization, of the power density of a microbial fuel cell by employing response surface methodology, coupled with central composite design. For this optimization study, the interactive effect of three independent parameters, namely (i) acetate concentration in the influent of anodic chamber; (ii) fuel feed flow rate in anodic chamber; and (iii) oxygen concentration in the influent of cathodic chamber, have been analyzed for a two-chamber microbial fuel cell, and the optimum conditions have been identified. The optimum value of power density was observed at an acetate concentration, a fuel feed flow rate, and an oxygen concentration value of 2.60 mol m(-3), 0.0 m(3), and 1.00 mol m(-3), respectively. The results show the achievement of a power density of 3.425 W m(-2), which is significant considering the available literature. Additionally, a statistical model has also been developed that correlates the three independent factors to the power density. For this model, R-2, adjusted R-2, and predicted R-2 were 0.839, 0.807, and 0.703, respectively. The fact that there is only a 3.8% error in the actual and adjusted R-2 demonstrates that the proposed model is statistically significant.</p> |
| format |
Article |
| author |
Naseer, Muhammad Nihal Zaidi, Asad A. Khan, Hamdullah Kumar, Sagar bin Owais, Muhammad Taha Abdul Wahab, Yasmin Dutta, Kingshuk Jaafar, Juhana Hamizi, Nor Aliya Islam, Mohammad Aminul Hussin, Hanim Badruddin, Irfan Anjum Alrobei, Hussein |
| author_facet |
Naseer, Muhammad Nihal Zaidi, Asad A. Khan, Hamdullah Kumar, Sagar bin Owais, Muhammad Taha Abdul Wahab, Yasmin Dutta, Kingshuk Jaafar, Juhana Hamizi, Nor Aliya Islam, Mohammad Aminul Hussin, Hanim Badruddin, Irfan Anjum Alrobei, Hussein |
| author_sort |
Naseer, Muhammad Nihal |
| title |
Statistical modeling and performance optimization of a two-chamber microbial fuel cell by response surface methodology |
| title_short |
Statistical modeling and performance optimization of a two-chamber microbial fuel cell by response surface methodology |
| title_full |
Statistical modeling and performance optimization of a two-chamber microbial fuel cell by response surface methodology |
| title_fullStr |
Statistical modeling and performance optimization of a two-chamber microbial fuel cell by response surface methodology |
| title_full_unstemmed |
Statistical modeling and performance optimization of a two-chamber microbial fuel cell by response surface methodology |
| title_sort |
statistical modeling and performance optimization of a two-chamber microbial fuel cell by response surface methodology |
| publisher |
MDPI |
| publishDate |
2021 |
| url |
http://eprints.um.edu.my/34547/ |
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1744649186219917312 |
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13.211869 |