A computational model for biofilm-based microbial fuel cells

Picioreanu, Cristian; Head, Ian M.; Katuri, Krishna P.; Loosdrecht, M.C.M. van; Scott, Keith

doi:10.1016/j.watres.2007.04.009

Cited by 388 publications

(258 citation statements)

References 25 publications

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“…This value for V biomass / Q ( Q is the accumulated charge) was then inserted into Equations (6) and (7) (see Experimental Section), yielding 42.15 mg

_{COD_{biomass}}

_{COD_{acetate}}

−1 (coulombic efficiency (CE)=0.958). This obtained yield is a feasible value, being within range of earlier reported biomass yields27 and lower but comparable to the theoretical maximum biomass yield of 109 mg

_{COD_{biomass}}

_{COD_{acetate}}

−1 (CE=0.891) calculated at the used anode potential of −0.35 V by using the thermodynamic approach from Picioreanu et al 32. Thus, we show that by using a combination of OCT and chronoamperometric data—both noninvasive measurements—we can derive valid biomass growth yields from the tested systems.…”

Section: Resultssupporting

confidence: 88%

“…For a systematic exploration of the effects of operational parameters on biomass development and, ultimately, system performance,31 mathematical modeling and model validation provide useful tools 32, 33, 34. A major threshold, however, hindering further calibration and validation of currently available models, concerns adequate monitoring of the catalyst loading.…”

Section: Introductionmentioning

confidence: 99%

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In situ Biofilm Quantification in Bioelectrochemical Systems by using Optical Coherence Tomography

Molenaar

Sleutels²,

Pereirã³

et al. 2018

ChemSusChem

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Detailed studies of microbial growth in bioelectrochemical systems (BESs) are required for their suitable design and operation. Here, we report the use of optical coherence tomography (OCT) as a tool for in situ and noninvasive quantification of biofilm growth on electrodes (bioanodes). An experimental platform is designed and described in which transparent electrodes are used to allow real‐time, 3D biofilm imaging. The accuracy and precision of the developed method is assessed by relating the OCT results to well‐established standards for biofilm quantification (chemical oxygen demand (COD) and total N content) and show high correspondence to these standards. Biofilm thickness observed by OCT ranged between 3 and 90 μm for experimental durations ranging from 1 to 24 days. This translated to growth yields between 38 and 42 mgCODbiomass gCODacetate −1 at an anode potential of −0.35 V versus Ag/AgCl. Time‐lapse observations of an experimental run performed in duplicate show high reproducibility in obtained microbial growth yield by the developed method. As such, we identify OCT as a powerful tool for conducting in‐depth characterizations of microbial growth dynamics in BESs. Additionally, the presented platform allows concomitant application of this method with various optical and electrochemical techniques.

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“…This value for V biomass / Q ( Q is the accumulated charge) was then inserted into Equations (6) and (7) (see Experimental Section), yielding 42.15 mg

_{COD_{biomass}}

_{COD_{acetate}}

_{COD_{biomass}}

_{COD_{acetate}}

Section: Resultssupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

In situ Biofilm Quantification in Bioelectrochemical Systems by using Optical Coherence Tomography

Molenaar

Sleutels²,

Pereirã³

et al. 2018

ChemSusChem

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“…An MBER model consists of two parts, MFCs and MBR, linked by some key factors such as organic loading rates (OLR), aeration intensity, and reactor configuration. The available MFC/MEC models are based on Nernst-Monod type of equations to calculate substrate consumption and bacteria growth in the anodic compartment, but the mass transfer equations vary depending on the spatial distribution of substrates and microbial activities (Kato Marcus et al 2007;Picioreanu et al 2007;Ping et al 2014;Pinto et al 2010). The existing MBR models are derived from activated sludge model (ASM) with a physical membrane filtration process (Ng and Kim 2007).…”

Section: Responsible Editor: Marcus Schulzmentioning

confidence: 99%

Development of a dynamic mathematical model for membrane bioelectrochemical reactors with different configurations

2015

Environ Sci Pollut Res

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Membrane bioelectrochemical reactors (MBERs) integrate membrane filtration into bioelectrochemical systems for sustainable wastewater treatment and recovery of bioenergy and other resource. Mathematical models for MBERs will advance the understanding of this technology towards further development. In the present study, a mathematical model was implemented for predicting current generation, membrane fouling, and organic removal within MBERs. The relative root-mean-square error was used to examine the model fit to the experimental data. It was found that a constant to determine how fast the internal resistance responds to the change of the anodophillic microorganism concentration could have a dominant impact on current generation. Hydraulic cross-flow exhibited a minor effect on membrane fouling unless it was reduced below 0.5 m s −1 . This MBER model encourages further optimization and eventually can be used to guide MBER development.

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“…For example, Sirinutsomboon [6] includes into the mass balance Fick's second law to describe the substrate profile evolution into the biofilm in one dimension. Picioreanu et al [7] propose spatial concentration gradients in one-, two-, or three-dimensional setups. Picioreanu et al [8] consider that solutes move not only by diffusion, but also by convection and electromigration in a two-dimensional biofilm model.…”

Section: Introductionmentioning

confidence: 99%

“…Involvement of soluble mediators, which has already been modeled by [7,8], justifies the existence of an oxidation and reduction reaction in the anode surface, which always occurs in any electrode-electrolyte interface [16].…”

Section: Introductionmentioning

confidence: 99%

A biofilm model of microbial fuel cells for engineering applications

Gatti

Milocco

2017

Int J Energy Environ Eng

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A generalized low-order model of the biofilm in a microbial fuel cell (MFC), suitable for use in real-time engineering applications, is presented. It is based on the description of the charge transfer, diffusion process, and charge accumulation in the biofilm. Since the dynamic processes in an MFC are ruled mainly by the biofilm, it can be used for many different diffusion-based MFC types by just changing the boundary conditions. Different mode operations like batch, fed-batch, continuous, etc., are also possible. The time-responses of voltage, substrate concentration on the surface of the electrode, and Faradaic and capacitive currents have been tested under several experimental conditions.

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A computational model for biofilm-based microbial fuel cells

Cited by 388 publications

References 25 publications

In situ Biofilm Quantification in Bioelectrochemical Systems by using Optical Coherence Tomography

In situ Biofilm Quantification in Bioelectrochemical Systems by using Optical Coherence Tomography

Development of a dynamic mathematical model for membrane bioelectrochemical reactors with different configurations

A biofilm model of microbial fuel cells for engineering applications

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