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A novel model for predicting bioelectrochemical performance of microsized-MFCs by incorporating bacterial chemotaxis parameters and simulation of biofilm formation

Kalantar, M ; Sharif University of Technology | 2018

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  1. Type of Document: Article
  2. DOI: 10.1016/j.bioelechem.2018.03.002
  3. Publisher: Elsevier B.V , 2018
  4. Abstract:
  5. Bacterial transport parameters play a fundamental role in microbial population dynamics, biofilm formation and bacteria dispersion. In this study, the novel model was extended based on the capability of microsized microbial fuel cells (MFCs) as amperometric biosensors to predict the cells' chemotactic and bioelectrochemical properties. The model prediction results coincide with the experimental data of Shewanella oneidensis and chemotaxis mutant of P. aeruginosa bdlA and pilT strains, indicating the complementary role of numerical predictions for bioscreening applications of microsized MFCs. Considering the general mechanisms for electron transfer, substrate biodegradation, microbial growth and bacterial dispersion are the main features of the presented model. In addition, the genetic algorithm method was implemented by minimizing the objective function to estimate chemotaxis properties of the different strains. Microsized MFC performance was assessed by analyzing the microbial activity in the biofilm and the anolyte. © 2018
  6. Keywords:
  7. Genetic algorithm ; Microsized microbial fuel cell ; Modeling ; P. aeruginosa ; Bacteria ; Biochemistry ; Biodegradation ; Biofilms ; Dispersions ; Forecasting ; Genetic algorithms ; Models ; Amperometric biosensors ; Bioelectrochemical properties ; Microbial fuel cells (MFCs) ; Microbial population dynamics ; Numerical predictions ; P.aeruginosa ; Microbial fuel cells ; Potassium ferricyanide ; Article ; Bacterial growth ; Biocatalyst ; Biomass ; Controlled study ; Current density ; Diffusion coefficient ; Dispersion ; Electric potential ; Electrochemistry ; Electron transport ; Microbial fuel cell ; Nonhuman ; Oxidation ; Pseudomonas aeruginosa ; Shewanella oneidensis ; Simulation ; Stoichiometry ; Substrate concentration ; Algorithm ; Bioenergy ; Biofilm ; Biological model ; Genetic procedures ; Growth, development and aging ; Microbiology ; Physiology ; Shewanella ; Algorithms ; Bioelectric Energy Sources ; Biosensing Techniques ; Chemotaxis ; Computer Simulation ; Models, Biological
  8. Source: Bioelectrochemistry ; Volume 122 , 2018 , Pages 51-60 ; 15675394 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/pii/S1567539417304930?via%3Dihub