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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Main Authors: 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
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Published: MDPI 2021
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Online Access:http://eprints.um.edu.my/34547/
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spelling 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
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic QD Chemistry
TP Chemical technology
spellingShingle 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
description 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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score 13.160551