Abstract
A mathematical model for the theoretical evaluation of microbial electrochemical technologies (METs) is presented that incorporates a detailed physico-chemical framework, includes multiple reactions (both at the electrodes and in the bulk phase) and involves a variety of microbial functional groups. The model is applied to two theoretical case studies: (i) A microbial electrolysis cell (MEC) for continuous anodic volatile fatty acids (VFA) oxidation and cathodic VFA reduction to alcohols, for which the theoretical system response to changes in applied voltage and VFA feed ratio (anode-to-cathode) as well as membrane type are investigated. This case involves multiple parallel electrode reactions in both anode and cathode compartments; (ii) A microbial fuel cell (MFC) for cathodic perchlorate reduction, in which the theoretical impact of feed flow rates and concentrations on the overall system performance are investigated. This case involves multiple electrode reactions in series in the cathode compartment. The model structure captures interactions between important system variables based on first principles and provides a platform for the dynamic description of METs involving electrode reactions both in parallel and in series and in both MFC and MEC configurations. Such a theoretical modelling approach, largely based on first principles, appears promising in the development and testing of MET control and optimization strategies.
Highlights
Environmental biotechnology relies largely on the use of mathematical models for process design, operation, optimization, and control [1]
microbial electrochemical technologies (METs) modeling has been receiving attention and several MET models have been published in literature over the past decade [2,3,4,5,6,7,8]
The anode potential is predicted higher than the cathode potential due to the external power source in this microbial electrolysis cell (MEC) configuration (Figure 1A)
Summary
Environmental biotechnology relies largely on the use of mathematical models for process design, operation, optimization, and control [1]. MET models whose main purpose is to uncover nontrivial interactions between biological, chemical, and electrical phenomena contain too many parameters and are usually computationally intensive [2,4,7,8,19] Limiting their application for scanning different possible configurations of METs for varied applications. With renewed interest in prospective microbial electrosynthesis processes for biofuels/chemical production from diverse substrates, there is a need for models capable of accurately describing the chemistry of multiple reactions at the electrodes and using the current as input instead of focusing on its prediction This would enable the evaluation of prospective METs in terms of their detailed chemical changes, including pH and accumulation of products. Such models would help as selection tools for interesting applications and lend themselves to calibration by well-established electrochemical techniques
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