A simple microbial fuel cell model for improvement of biomedical device powering times

Roxby, DN; Tran, N; Nguyen, HT

A simple microbial fuel cell model for improvement of biomedical device powering times

Roxby, DN Tran, N

Nguyen, HT

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Publication Type:: Conference Proceeding
Citation:: 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014, 2014, pp. 634 - 637
Issue Date:: 2014-11-02

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Field	Value	Language
dc.contributor.author	Roxby, DN	en_US
dc.contributor.author	Tran, N https://orcid.org/0000-0001-7747-2530	en_US
dc.contributor.author	Nguyen, HT https://orcid.org/0000-0003-3373-8178	en_US
dc.date.issued	2014-11-02	en_US
dc.identifier.citation	2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014, 2014, pp. 634 - 637	en_US
dc.identifier.isbn	9781424479290	en_US
dc.identifier.uri	http://hdl.handle.net/10453/32644
dc.description.abstract	© 2014 IEEE. This study describes a Matlab based Microbial Fuel Cell (MFC) model for a suspended microbial population, in the anode chamber for the use of the MFC in powering biomedical devices. The model contains three main sections including microbial growth, microbial chemical uptake and secretion and electrochemical modeling. The microbial growth portion is based on a Continuously Stirred Tank Reactor (CSTR) model for the microbial growth with substrate and electron acceptors. Microbial stoichiometry is used to determine chemical concentrations and their rates of change and transfer within the MFC. These parameters are then used in the electrochemical modeling for calculating current, voltage and power. The model was tested for typically exhibited MFC characteristics including increased electrode distances and surface areas, overpotentials and operating temperatures. Implantable biomedical devices require long term powering which is the main objective for MFCs. Towards this end, our model was tested with different initial substrate and electron acceptor concentrations, revealing a four-fold increase in concentrations decreased the power output time by 50%. Additionally, the model also predicts that for a 35.7% decrease in specific growth rate, a 50% increase in power longevity is possible.	en_US
dc.relation.ispartof	2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014	en_US
dc.relation.isbasedon	10.1109/EMBC.2014.6943671	en_US
dc.subject.mesh	Monitoring, Physiologic	en_US
dc.subject.mesh	Electrodes	en_US
dc.subject.mesh	Bioelectric Energy Sources	en_US
dc.subject.mesh	Prostheses and Implants	en_US
dc.subject.mesh	Models, Chemical	en_US
dc.title	A simple microbial fuel cell model for improvement of biomedical device powering times	en_US
dc.type	Conference Proceeding
utslib.for	0903 Biomedical Engineering	en_US
dc.location.activity	Sheraton Chicago Towers and Hotel, Chicago, United States of America
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2014 IEEE. This study describes a Matlab based Microbial Fuel Cell (MFC) model for a suspended microbial population, in the anode chamber for the use of the MFC in powering biomedical devices. The model contains three main sections including microbial growth, microbial chemical uptake and secretion and electrochemical modeling. The microbial growth portion is based on a Continuously Stirred Tank Reactor (CSTR) model for the microbial growth with substrate and electron acceptors. Microbial stoichiometry is used to determine chemical concentrations and their rates of change and transfer within the MFC. These parameters are then used in the electrochemical modeling for calculating current, voltage and power. The model was tested for typically exhibited MFC characteristics including increased electrode distances and surface areas, overpotentials and operating temperatures. Implantable biomedical devices require long term powering which is the main objective for MFCs. Towards this end, our model was tested with different initial substrate and electron acceptor concentrations, revealing a four-fold increase in concentrations decreased the power output time by 50%. Additionally, the model also predicts that for a 35.7% decrease in specific growth rate, a 50% increase in power longevity is possible.

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http://hdl.handle.net/10453/32644