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Modeling biofilms with dual extracellular electron transfer mechanisms

Overview of attention for article published in Physical Chemistry Chemical Physics (PCCP), January 2013
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Article details
Title
Modeling biofilms with dual extracellular electron transfer mechanisms
Published in
Physical Chemistry Chemical Physics (PCCP), January 2013
DOI 10.1039/c3cp53759e
Pubmed ID
Authors
Abstract

Electrochemically active biofilms have a unique form of respiration in which they utilize solid external materials as terminal electron acceptors for their metabolism. Currently, two primary mechanisms have been identified for long-range extracellular electron transfer (EET): a diffusion- and a conduction-based mechanism. Evidence in the literature suggests that some biofilms, particularly Shewanella oneidensis, produce the requisite components for both mechanisms. In this study, a generic model is presented that incorporates the diffusion- and the conduction-based mechanisms and allows electrochemically active biofilms to utilize both simultaneously. The model was applied to S. oneidensis and Geobacter sulfurreducens biofilms using experimentally generated data found in the literature. Our simulation results show that (1) biofilms having both mechanisms available, especially if they can interact, may have a metabolic advantage over biofilms that can use only a single mechanism; (2) the thickness of G. sulfurreducens biofilms is likely not limited by conductivity; (3) accurate intrabiofilm diffusion coefficient values are critical for current generation predictions; and (4) the local biofilm potential and redox potential are two distinct parameters and cannot be assumed to have identical values. Finally, we determined that simulated cyclic and squarewave voltammetry based on our model are currently not capable of determining the specific percentages of extracellular electron transfer mechanisms in a biofilm. The developed model will be a critical tool for designing experiments to explain EET mechanisms.

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 119 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United Kingdom 2 2%
United States 1 <1%
Japan 1 <1%
Spain 1 <1%
Germany 1 <1%
Unknown 113 95%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 28 24%
Researcher 20 17%
Student > Master 18 15%
Student > Doctoral Student 9 8%
Other 6 5%
Other 19 16%
Unknown 19 16%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 22 18%
Engineering 16 13%
Environmental Science 14 12%
Biochemistry, Genetics and Molecular Biology 12 10%
Chemistry 11 9%
Other 14 12%
Unknown 30 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 October 2013.
All research outputs
#28,811,852
of 34,601,305 outputs
Outputs from Physical Chemistry Chemical Physics (PCCP)
#13,788
of 21,171 outputs
Outputs of similar age
#290,103
of 347,055 outputs
Outputs of similar age from Physical Chemistry Chemical Physics (PCCP)
#376
of 442 outputs
Altmetric has tracked 34,601,305 research outputs across all sources so far. This one is in the 9th percentile – i.e., 9% of other outputs scored the same or lower than it.
So far Altmetric has tracked 21,171 research outputs from this source. They receive a mean Attention Score of 2.8. This one is in the 10th percentile – i.e., 10% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 347,055 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 442 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.