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  • 标题:MODELO BIOQUÍMICAMENTE ESTRUCTURADO PARA LA ESTIMACIÓN DE LA EFICIENCIA DE UNA CELDA DE COMBUSTIBLE MICROBIANA
  • 本地全文:下载
  • 作者:Maxvell Gustavo Jiménez Escamilla ; Claudio Garibay Orijel ; Manuel Antonio Borja Salin
  • 期刊名称:Revista Internacional de Contaminación Ambiental
  • 印刷版ISSN:0188-4999
  • 出版年度:2018
  • 卷号:34
  • 期号:2
  • 页码:331-345
  • 语种:Spanish
  • 出版社:Centro de Ciencias de la Atmósfera
  • 摘要:A preliminary study focused on modeling microbial fuel cells through microbial yields was performed. A mathematical model to determine the quantity of charge generated over time in the anodic chamber of a microbial fuel cell, using Escherichia coli as the electrogenic organism, was designed. This model was used in order to estimate the electrical efficiency of microbial yields such as biomass, substrate, and product, and the stoichiometric coefficients of the species aforementioned. The mathematical model constructed described microbial growth using a logistical population model, giving a coefficient of determination of R 2 = 0.960 between the model and the experimental data for the substrate, and R 2 = 0.982 for the biomass. Using this electrical charge prediction model, future studies will focus primarily on measuring the experimental microbial yields and stoichiometric coefficients of electrogenic organisms in order to test the viability of this cell implementation.
  • 其他摘要:A preliminary study focused on modeling microbial fuel cells through microbial yields was performed. A mathematical model to determine the quantity of charge generated over time in the anodic chamber of a microbial fuel cell, using Escherichia coli as the electrogenic organism, was designed. This model was used in order to estimate the electrical efficiency of microbial yields such as biomass, substrate, and product, and the stoichiometric coefficients of the species aforementioned. The mathematical model constructed described microbial growth using a logistical population model, giving a coefficient of determination of R 2 = 0.960 between the model and the experimental data for the substrate, and R 2 = 0.982 for the biomass. Using this electrical charge prediction model, future studies will focus primarily on measuring the experimental microbial yields and stoichiometric coefficients of electrogenic organisms in order to test the viability of this cell implementation.
  • 其他关键词:microbial growth;modeling;bioenergy;renewable energy;crecimiento microbiano;modelación;bioenergía;energía renovable
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