本研究目的在於利用COMSOL Multiphysics 5.4商業軟體建立微生物燃料電池之數學模型，微生物燃料電池為近年來新替代能源解決方案之一，對於微生物燃料電池的研究多數停留於實驗階段，但因為成本高昂、技術難度高，受到阻礙較大，近年來開始有較多的文獻在討論微生物燃料電池數學模型，多數屬於簡易版模型，而大多數值模擬分析停留在一維以及二維階段，並未考慮到實際3D流場對於微生物燃料電池的性能影響，此篇論文的研究目標在於全面性的模擬微生物燃料電池，以利於未來探討各項參數對於微生物燃料電池性能的影響，有效降低實驗時的成本與限制。本論文的數值模型建立在Zeng et al. [1]的模型基礎上，透過使模擬模型與Zeng et al.論文實驗數據一致，證明數值模型的準確性，並且近一步透過模型來探討影響微生物燃料電池性能的因素。透過完整的3D流場模擬，在模型的上下區域皆發現渦流的產生，造成此區域的流動性不佳，降低反應速率；進一步使在渦流區域的微生物濃度分布較低。利用模型對稱面的電流密度積分得到類似2D模擬的結果，與原本3D模型相比，有5%的電流密度成長。改變進出口位置可以減少渦流的產生，進一步改善反應速率，以提升整體微生物燃料電池的表現。

The purpose of this research is to use COMSOL Multiphysics 5.4 commercial software to establish a mathematical model of MFC (microbial fuel cells). MFC are one of the new alternative energy solutions in recent years. However, most research on microbial fuel cells stays in the experimental stage. Because of the high cost and the technical difficulty, the MFC researches encounter a big obstacle. In recent years, there have been more researches discussing the mathematical MFC, but most of them belong to the simple version of the model. Most of the simulation analysis stays in the one-dimensional and two-dimensional stages, and has not considered the actual 3D flow field affects the performance of the MFC. The purpose of this paper is to comprehensively simulate the MFC, so as to discuss the influence of various parameters on MFC’s performance. And effectively reduce the cost and cost of the experiment. The numerical model of this paper is based on the model of Zeng et al. [1]. By fitting the simulation model with the experimental data of the Zeng et al. paper, the accuracy of the numerical model is proved. And further, through the model to explore the impact of other variables of the MFC on the battery performance. Through a complete 3D flow field simulation, vortex is found in the upper and lower areas of the model, which causes poor fluidity in this area and reduces the reaction rate; further reducing the microbial concentration distribution in that area. Using the current density integration of the symmetry plane to obtain a result similar to the 2D simulation. Compared with the original 3D model, the current density is increased by 5%. Changing the position of the inlet and outlet can reduce the generation of vortex, further improve the reaction rate, and enhance the overall performance of the MFC.

參考文獻

[1] Y.Zeng, Y. F.Choo, B. H.Kim, andP.Wu, “Modelling and simulation of two-chamber microbial fuel cell,” J. Power Sources, 2010.
[2] V. M.Ortiz-Martínez, M. J.Salar-García, A. P.delos Ríos, F. J.Hernández-Fernández, J. A.Egea, andL. J.Lozano, “Developments in microbial fuel cell modeling,” Chem. Eng. J., vol. 271, pp. 50–60, 2015.
[3] C.Xia, D.Zhang, W.Pedrycz, Y.Zhu, andY.Guo, “Models for Microbial Fuel Cells: A critical review,” J. Power Sources, vol. 373, no. November 2017, pp. 119–131, 2018.
[4] T.Krieg, J. A.Wood, K. M.Mangold, andD.Holtmann, “Mass transport limitations in microbial fuel cells: Impact of flow configurations,” Biochem. Eng. J., vol. 138, pp. 172–178, 2018.
[5] C. I.Torres, A. K.Marcus, H. S.Lee, P.Parameswaran, R.Krajmalnik-Brown, andB. E.Rittmann, “A kinetic perspective on extracellular electron transfer by anode-respiring bacteria,” FEMS Microbiol. Rev., vol. 34, no. 1, pp. 3–17, 2010.
[6] S.Cheng, H.Liu, andB. E.Logan, “Increased power generation in a continuous flow MFC with advective flow through the porous anode and reduced electrode spacing,” Environ. Sci. Technol., vol. 40, no. 7, pp. 2426–2432, 2006.
[7] C.Picioreanu, K. P.Katuri, I. M.Head, M. C. M.VanLoosdrecht, andK.Scott, “Mathematical model for microbial fuel cells with anodic biofilms and anaerobic digestion,” Water Sci. Technol., vol. 57, no. 7, pp. 965–971, 2008.
[8] X.Zhang, D.Pant, F.Zhang, J.Liu, W.He, andB. E.Logan, “Long-Term Performance of Chemically and Physically Modified Activated Carbons in Air Cathodes of Microbial Fuel Cells,” ChemElectroChem, vol. 1, no. 11, pp. 1859–1866, 2014.
[9] G.Kreysa, D.Sell, andP.Kraemer, “Bioelectrochemical fuel cells,” Berichte der Bunsengesellschaft/Physical Chem. Chem. Phys., vol. 94, no. 9, pp. 1042–1045, 1990.
[10] W. F.Cai et al., “Investigation of a two-dimensional model on microbial fuel cell with different biofilm porosities and external resistances,” Chem. Eng. J., vol. 333, no. June 2017, pp. 572–582, 2018.
[11] W.Bae andB. E.Rittmann, “A structured model of dual-limitation kinetics,” Biotechnol. Bioeng., vol. 49, no. 6, pp. 683–689, 1996.
[12] A. K.Marcus, C. I.Torres, andB. E.Rittmann, “Conduction-based modeling of the biofilm anode of a microbial fuel cell,” Biotechnol. Bioeng., vol. 98, no. 6, pp. 1171–1182, 2007.
[13] B.Sundén, “Transport phenomena in batteries,” Hydrog. Batter. Fuel Cells, pp. 81–91, 2019.
[14] G.Hernández-Flores, H. M.Poggi-Varaldo, O.Solorza-Feria, M. T.Ponce Noyola, T.Romero-Castañón, andN.Rinderknecht-Seijas, “Tafel equation based model for the performance of a microbial fuel cell,” Int. J. Hydrogen Energy, vol. 40, no. 48, pp. 17421–17432, 2015.
[15] Chang; Raymond, Physical Chemistry for the Biosciences. Sansalito, CA: University Sciences, 2005.
[16] J.Atkins, Peter; de Paula, Atkins’ Physical Chemistry (8th ed.). Oxford University Press, 2006.
[17] R. P.Pinto, B.Srinivasan, M. F.Manuel, andB.Tartakovsky, “A two-population bio-electrochemical model of a microbial fuel cell,” Bioresour. Technol., vol. 101, no. 14, pp. 5256–5265, 2010.