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Metabolic Modeling of Spatial Heterogeneity of Biofilms in Microbial Fuel Cells

机译:微生物燃料电池中生物膜的空间异质性的代谢模拟

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Microbial fuel cells (MFCs) provide an alternative approach to generate electricity from organic matter. In these MFCs, microorganisms such as the Geobacter species oxidize organic waste and transfer electrons to an electrode. Mathematical models have been used to study and optimize biofilm processes, in developing MFCs into commercial applications. Existing biofilm models are based on Nernst-Monod type expressions, and are restricted to studying extracellular behavior such as electrochemical and microbiological components, separated from the metabolic behavior of microorganisms or vice versa. This paper presents a model that addresses the spatial heterogeneity across the biofilm, while incorporating the metabolic fluxes in each individual cell as extracellular conditions (electron donor and acceptor concentrations) vary across the biofilm. This model shows the effect of different maintenance energy requirements on maximum current production and the thickness of the biofilms, and predicts the variations in biofilm thicknesses in DL; KN400 strains under similar biofilm conditions, successfully.
机译:微生物燃料电池(MFCS)提供一种从有机物产生电力的替代方法。在这些MFC中,微生物如地形杆菌物种氧化有机废物并将电子传递给电极。数学模型已被用于研究和优化生物膜过程,在开发MFC进入商业应用中。现有的生物膜模型基于NERNST-MONOD型表达,仅限于研究诸如电化学和微生物组分的细胞外行为,与微生物的代谢行为分开,反之亦然。本文呈现了一种模型,该模型解决了生物膜上的空间异质性,同时将每个单独的细胞中的代谢助量掺入以作为细胞外条件(电子供体和受体浓度)在生物膜上变化。该模型显示了不同维护能量要求对最大电流生产和生物膜厚度的影响,并预测DL中的生物膜厚度的变化; KN400在类似的生物膜条件下菌株成功。

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