Model-based design and optimization of a microbial fuel cell

微生物燃料电池的基于模型的设计和优化

• 批准号: 341397-2010
• 负责人: Tartakovsky, Boris
• 金额: $ 1.46万
• 依托单位: École Polytechnique de Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2012
• 资助国家: 加拿大
• 起止时间: 2012-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=509780
• 关键词: Model; based; design; optimization; microbial

Energy production in a microbial fuel cell (MFC) is an emerging area of research, which has attracted an increased amount of attention from the scientific community. In a MFC, anodophilic microorganisms degrade organic matter and transfer electrons to the anode via nanowires or self-produced mediators, while releasing protons. Depending on the cathodic reaction, either electricity generation (MFC) or hydrogen production (MEC) can be achieved. Energy production in MFCs and MECs has been demonstrated from a variety of carbon sources, including volatile fatty acids, carbohydrates, and cellulose. Mixed microbial populations of the anodic compartment might include anodophilic, methanogenic, hydrolytic and fermentative microorganisms. MFC and MEC design might benefit from the knowledge of process dynamics, including dynamics of microbial populations. However, the existing mathematical models are focused on process electrochemistry and largely neglect microbial community complexity. The proposed research program is aimed at understanding the dynamics of MFC/MEC microbial populations through the development of a model suitable for simulating a mixed microbial population. To study process dynamics, an array of off-line and on-line experiments will be performed. In particular, on-line monitoring of substrate distribution in the anodic compartment and within the anode will be examined by multi-wavelength (3D) fluorometry. The intended application of this model includes improved design of continuous flow MFCs and MECs (i.e. anodic chamber configuration, electrode size and positioning, operating conditions), MFC stack design, and the development of feedback control algorithms for maximizing power output.

微生物燃料电池（MFC）的能量生产是一个新兴的研究领域，已经吸引了科学界越来越多的关注。 在MFC中，嗜阳极微生物降解有机物质并通过纳米线或自产介质将电子转移到阳极，同时释放质子。根据阴极反应，可以实现发电（MFC）或制氢（MEC）。 MFC和MEC中的能量生产已被证明来自各种碳源，包括挥发性脂肪酸、碳水化合物和纤维素。阳极室的混合微生物种群可能包括嗜阳极微生物、产甲烷微生物、水解微生物和发酵微生物。 MFC和MEC设计可能受益于过程动力学的知识，包括微生物种群的动力学。 然而，现有的数学模型主要集中在过程电化学，在很大程度上忽略了微生物群落的复杂性。 拟议的研究计划的目的是了解MFC/MEC微生物种群的动态，通过开发一个适合模拟混合微生物种群的模型。为了研究过程动力学，将进行一系列离线和在线实验。 特别是，在线监测基板分布在阳极室和阳极内将检查多波长（3D）荧光法。该模型的预期应用包括连续流MFC和MEC的改进设计（即阳极室配置、电极尺寸和定位、操作条件）、MFC堆设计以及用于最大化功率输出的反馈控制算法的开发。