Mustafa Kamal Pasha; Khurram Munawar

Data Driven Through Machine Learning on Electricity Production by Anode Respiring Bacteria Using the Microbial Fuel Cells

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Author(s)

Mustafa Kamal Pasha ^1,* Khurram Munawar ¹

1. Department of Environment, Society and Design, Lincoln University - New Zealand

* Corresponding author.

DOI: https://doi.org/10.5815/ijeme.2021.03.01

Received: 8 Nov. 2020 / Revised: 29 Dec. 2020 / Accepted: 20 Jan. 2021 / Published: 8 Jun. 2021

Index Terms

MFCs, ARB, Machine Learning, ANN

Abstract

Microbial Fuel Cell (MFC) is a bio-electrochemical device that generates electric current by using bacteria. MFCs are currently a topic of intense research and interest due to their ability to produce renewable energy along with added benefits such as wastewater treatment. Although the theoretical concepts and applicability of MFCs are great, their application, thus far has been limited due to the limits of power production. Current research aims to improve the efficiency as well as the upper limit of power production by MFCs. In parallel to current research, this study is designed with a similar aim to do a comprehensive data analysis on the topic of MFCs by using techniques of Artificial Intelligence. Therefore, we started this study by obtaining the relevant data through an extensive literature retrieval for developing Artificial Neural Network model. The data from the output layer was viewed by using VOSviewer software and was further subjected to analysis. The data collected through machine learning provided an insight about the optimal conditions of MFCs which would allow for maximum current production. It discusses two existing types of MFCs; namely mediator type and mediator free type of MFC. Anode respiring bacteria (ARB), also known as exoelectrogenes can be used as the mediator to transfer electrons by utilizing the substrate present at the anode. Our results suggest that different combinations of bacterium and biofilms can produce more electric current with improved stability. This study will provide an insight to improve the working capacity of MFCs. It is likely that MFCs will one day be used as a stand-alone power production method by optimizing the current production capacity. Moreover, these advancements will have a significant by utilizing MFCs for making chips and biosensors, and treating wastewater.

Cite This Paper

Mustafa Kamal Pasha, Khurram Munawar, " Data Driven Through Machine Learning on Electricity Production by Anode Respiring Bacteria Using the Microbial Fuel Cells", International Journal of Education and Management Engineering (IJEME), Vol.11, No.3, pp. 1-10, 2021. DOI: 10.5815/ijeme.2021.03.01

Reference

[1]Lefebvre, O., Tan, Z., Kharkwal, S., & Ng, H. Y. Effect of increasing anodic NaCl concentration on microbial fuel cell performance. Bioresour Technol, 112, 336-340. doi: 10.1016/j.biortech.2012.02.048

[2]Torres, C. I., Krajmalnik-Brown, R., Parameswaran, P., Marcus, A. K., Wanger, G., Gorby, Y. A., & Rittmann, B. E. Selecting anode-respiring bacteria based on anode potential: phylogenetic, electrochemical, and microscopic characterization. Environmental science & technology; 2009, 43(24), 9519-9524.

[3]Zhou, D., Dong, S., Ki, D., & Rittmann, B. E. Photocatalytic-induced electron transfer via anode-respiring bacteria (ARB) at an anode that intimately couples ARB and a TiO 2 photocatalyst. Chemical Engineering Journal; 2018, 338, 745-7

[4]Rabaey, K., Lissens, G., Siciliano, S. D., & Verstraete, W. A microbial fuel cell capable of converting glucose to electricity at high rate and efficiency. Biotechnology letters; 2003, 25(18), 1531-1535.

[5]Pierra, M., Carmona-Martínez, A. A., Trably, E., Godon, J. J., & Bernet, N. Microbial characterization of anode-respiring bacteria within biofilms developed from cultures previously enriched in dissimilatory metal-reducing bacteria. Bioresource technology; 2015, 195, 283-287.

[6]Lee, H.-S., Torres, C. I., & Rittmann, B. E.. Effects of substrate diffusion and anode potential on kinetic parameters for anode-respiring bacteria. Environmental science & technology; 2009, 43(19), 7571-7577.

[7]Liu, H., & Logan, B. E. Electricity generation using an air-cathode single chamber microbial fuel cell in the presence and absence of a proton exchange membrane. Environmental science & technology; 2004. 38(14), 4040-4046.

[8]Heilmann, J., & Logan, B. E. Production of electricity from proteins using a microbial fuel cell. Water Environment Research,; 2006, 78(5), 531-537.

[9]Logan, B. E. (2009). Exoelectrogenic bacteria that power microbial fuel cells. Nature Reviews Microbiology, 7(5), 375.

[10]Chen, C.-Y., Chen, T.-Y., & Chung, Y.-C. (2013). A comparison of bioelectricity in microbial fuel cells with aerobic and anaerobic anodes. Environmental Technology, 35(3), 286–293.

[11]Flimban, S. G., Ismail, I. M., Kim, T., & Oh, S. E. (2019). Overview of recent advancements in the microbial fuel cell from fundamentals to applications: design, major elements, and scalability. Energies, 12(17), 3390.

[12]Rabaey, K., Boon, N., Siciliano, S. D., Verhaege, M., & Verstraete, W. Biofuel cells select for microbial consortia that self-mediate electron transfer. Applied and environmental microbiology; 2004, 70(9), 5373-5382.

[13]Munawar, H. S., Qayyum, S., Ullah, F., & Sepasgozar, SBig Data and Its Applications in Smart Real Estate and the Disaster Management Life Cycle: A Systematic Analysis. Big Data and Cognitive Computing; 2020, 4(2).

[14]Munawar, H. S., Zhang, J., Li, H., Mo, D., & Chang, L. Mining multispectral aerial images for automatic detection of strategic bridge locations for disaster relief missions. In Pacific-Asia Conference on Knowledge Discovery and Data Mining (pp. 189-200). Springer, Cham. . (2019, April)

[15]Munawar HS, Hammad A, Ullah F, Ali TH. After the flood: A novel application of image processing and machine learning for post-flood disaster management. In Proceedings of the 2nd International Conference on Sustainable Development in Civil Engineering (ICSDC 2019), Jamshoro Pakistan 2019 Dec (pp. 5-7).

[16]Munawar HS, Awan AA, Khalid U, Munawar S, Maqsood A. Revolutionizing Telemedicine by Instilling H. 265. International Journal of Image, Graphics & Signal Processing. 2017 May 1;9(5).

[17]Hafiz Suliman Munawar, " Applications of Leaky-wave Antennas: A Review ", International Journal of Wireless and Microwave Technologies(IJWMT), Vol.10, No.3, pp. 56-62, 2020.DOI: 10.5815/ijwmt.2020.03.05

[18]Hafiz Suliman Munawar, " An Overview of Reconfigurable Antennas for Wireless Body Area Networks and Possible Future Prospects ", International Journal of Wireless and Microwave Technologies(IJWMT), Vol.10, No.2, pp. 1-8, 2020.DOI: 10.5815/ijwmt.2020.02.01

[19]Munawar, H. S., Khalid, U., Jilani, R., & Maqsood, A. (2017). Version Management by Time Based Approach in Modern Era. International Journal of Education and Management Engineering, 4, 13-20.

[20]Hafiz Suliman Munawar, " Reconfigurable Origami Antennas: A Review of the Existing Technology and its Future Prospects ", International Journal of Wireless and Microwave Technologies(IJWMT), Vol.10, No.4, pp. 34-38, 2020.DOI: 10.5815/ijwmt.2020.04.04

[21]Munawar, H. S., & Maqsood, A. Isotropic Surround Suppression based Linear Target Detection using Hough Transform.

[22]Aelterman, P., Freguia, S., Keller, J., Verstraete, W., & Rabaey, K.. The anode potential regulates bacterial activity in microbial fuel cells. Applied microbiology and biotechnology; 2008, 78(3), 409-418.

[23]Yasri, N. G., & Nakhla, G. Electrochemical Behavior of Anode-Respiring Bacteria on Doped Carbon Electrodes. ACS Applied Materials & Interfaces; 2016, 8(51), 35150-35162. doi: 10.1021/acsami.6b09907

[24]Mahmoud, M., Parameswaran, P., Torres, C. I., & Rittmann, B. E. Electrochemical techniques reveal that total ammonium stress increases electron flow to anode respiration in mixed‐species bacterial anode biofilms. Biotechnology and bioengineering; 2017, 114(6), 1151-1159.

[25]Parameswaran, P., Bry, T., Popat, S. C., Lusk, B. G., Rittmann, B. E., & Torres, C. I.. Kinetic, electrochemical, and microscopic characterization of the thermophilic, anode-respiring bacterium Thermincola ferriacetica. Environmental science & technology; 2013, 47(9), 4934-4940.

[26]Mink, J. E., & Hussain, M. M..Sustainable design of high-performance microsized microbial fuel cell with carbon nanotube anode and air cathode. Acs ; 2013, 7(8), 6921-6927.

[27]Liu, H., Cheng, S., & Logan, B. E.. Production of electricity from acetate or butyrate using a single-chamber microbial fuel cell. Environmental science & technology; 2005, 39(2), 658-662.

[28]He, Z., Minteer, S. D., & Angenent, L. T. Electricity generation from artificial wastewater using an upflow microbial fuel cell. Environmental science & technology; 2005, 39(14), 5262-5267.

[29]Logan, B. E., Hamelers, B., Rozendal, R., Schroder, U., Keller, J., Freguia, S.,Rabaey, K. Microbial fuel cells: methodology and technology. Environ Sci Technol; 2006, 40(17), 5181-5192.

[30]Rahimnejad, M., Adhami, A., Darvari, S., Zirepour, A., & Oh, S. E. Microbial fuel cell as new technology for bioelectricity generation: a review. Alexandria Engineering Journal; 2015, 54(3), 745-756.

[31]Torres, C. I., Kato Marcus, A., & Rittmann, B. E.. Proton transport inside the biofilm limits electrical current generation by anode‐respiring bacteria. Biotechnology and Bioengineering; 2008, 100(5), 872-881.

[32]Torres, C. I., Marcus, A. K., Lee, H.-S., Parameswaran, P., Krajmalnik-Brown, R., & Rittmann, B. E. A kinetic perspective on extracellular electron transfer by anode-respiring bacteria. FEMS microbiology reviews; 2009, 34(1), 3-17.

[33]Park, D. H., & Zeikus, J. G. Improved fuel cell and electrode designs for producing electricity from microbial degradation. Biotechnology and Bioengineering; 2003, 81(3), 348-355.

[34]Baudler, A., Schmidt, I., Langner, M., Greiner, A., & Schröder, U.. Does it have to be carbon? Metal anodes in microbial fuel cells and related bioelectrochemical systems. Energy & Environmental Science; 2015, 8(7), 2048-2055.

[35]Kiely, P. D., Cusick, R., Call, D. F., Selembo, P. A., Regan, J. M., & Logan, B. E. Anode microbial communities produced by changing from microbial fuel cell to microbial electrolysis cell operation using two different wastewaters. Bioresource technology; 2011, 102(1), 388-394.

[36]Du, Z., Li, H., & Gu, T.. A state of the art review on microbial fuel cells: a promising technology for wastewater treatment and bioenergy. Biotechnology advances; 2007, 25(5), 464-482.

[37]Sonawane, J. M., Yadav, A., Ghosh, P. C., & Adeloju, S. B. Recent advances in the development and utilization of modern anode materials for high performance microbial fuel cells. Biosensors and Bioelectronics; 2017, 90, 558-576.

[38]Rittmann, B. E. Opportunities for renewable bioenergy using microorganisms. Biotechnology and Bioengineering; 2008, 100(2), 203-212.

[39]ZHANG, Y.-C., JIANG, Z.-H., & Ying, L. Application of electrochemically active bacteria as anodic biocatalyst in microbial fuel cells. Chinese Journal of Analytical Chemistry; 2015, 43(1), 155-163.

[40]Cameron, Kimberlynn Dawn. Microbial Fuel Cell Possibilities on American Indian Tribal Lands. No. SAND2016-7820PE. Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2016.

[41]Niessen, J., Schröder, U., & Scholz, F. Exploiting complex carbohydrates for microbial electricity generation–a bacterial fuel cell operating on starch. Electrochemistry Communications; 2004, 6(9), 955-958.

[42]Munawar, H. S., Khalid, U., & Maqsood, A. Fire detection through Image Processing; A brief overview.

[43]Munawar, H. S., Khalid, U., & Maqsood, A. Modern day detection of Mines; Using the Vehicle Based Detection Robot.

[44]Munawar, H. S., Qayyum, S., Ullah, F., & Sepasgozar, S. (2020). Big Data and Its Applications in Smart Real Estate and the Disaster Management Life Cycle: A Systematic Analysis. Big Data and Cognitive Computing, 4(2), 4.

[45]Munawar HS, Awan AA, Maqsood A, Khalid U. REINVENTING RADIOLOGY IN MODERN ERA.

[46]Mohammed Awad, Mohammed Zaid-Alkelani, "Prediction of Water Demand Using Artificial Neural Networks Models and Statistical Model", International Journal of Intelligent Systems and Applications(IJISA), Vol.11, No.9, pp.40-55, 2019. DOI: 10.5815/ijisa.2019.09.05.

[47]Watanabe, K. Recent developments in microbial fuel cell technologies for sustainable bioenergy. Journal of bioscience and bioengineering; 2008, 106(6), 528-536.

[48]Munawar HS, Hammad A, Ullah F, Ali TH. After the flood: A novel application of image processing and machine learning for post-flood disaster management. InProceedings of the 2nd International Conference on Sustainable Development in Civil Engineering (ICSDC 2019), Jamshoro Pakistan 2019 Dec (pp. 5-7).

[49]Munawar, H. S., Zhang, J., Li, H., Mo, D., & Chang, L. (2019, April). Mining multispectral aerial images for automatic detection of strategic bridge locations for disaster relief missions. In Pacific-Asia Conference on Knowledge Discovery and Data Mining (pp. 189-200). Springer, Cham.

[50]Munawar, H. S. (2020). Flood Disaster Management: Risks, Technologies, and Future Directions. Machine Vision Inspection Systems: Image Processing, Concepts, Methodologies and Applications, 1, 115-146.

[51]Munawar, H. S. (2020). Image and Video Processing for Defect Detection in Key Infrastructure. Machine Vision Inspection Systems: Image Processing, Concepts, Methodologies and Applications, 1, 159-177.

[52]Rabaey, K., & Rozendal, R. A. Microbial electrosynthesis—revisiting the electrical route for microbial production. Nature Reviews Microbiology; 2010, 8(10), 706.

[53]Baisakhi Chatterjee, Himadri Nath Saha, "Parameter Training in MANET using Artificial Neural Network", International Journal of Computer Network and Information Security(IJCNIS), Vol.11, No.9, pp.1-8, 2019.DOI: 10.5815/ijcnis.2019.09.01.

[54]Ahmed S. Mahedy, Abdelazeem A. Abdelsalam, Reham H. Mohamed, Ibrahim F. El-Nahry, "Utilizing Neural Networks for Stocks Prices Prediction in Stocks Markets", International Journal of Information Technology and Computer Science(IJITCS), Vol.12, No.3, pp.1-7, 2020. DOI: 10.5815/ijitcs.2020.03.01.

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