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A 4-Electrode Microfluidic Microbial Fuel Cell Doubles Power Output and Conversion Efficiency, but Gravitational Effects must Be Overcome

2024· preprint· en· W4400469882 on OpenAlexafffund
Linlin Liu, Haleh Baghernavehsi, Jesse Greener

Bibliographic record

VenuePreprints.org · 2024
Typepreprint
Languageen
FieldEnvironmental Science
TopicMicrobial Fuel Cells and Bioremediation
Canadian institutionsCentre hospitalier de l'Université LavalUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaUniversité Laval
KeywordsGeobacter sulfurreducensMicrobial fuel cellElectrodeAnodeMicrofluidicsMaterials sciencePower densityMicrochannelSettlingGeobacterNanotechnologyOptoelectronicsChemistryChemical engineeringPower (physics)BiofilmEnvironmental scienceEnvironmental engineeringPhysicsBiology

Abstract

fetched live from OpenAlex

High-power output and high conversion efficiency are crucial in the study of microfluidic microbial fuel cells (MFCs). In our previous work, we attempted various methods to increase the power density of the MFCs, but nutrient consumption was limited to the bottom (electrode) layer of the microfluidic channel due to the diffusion limitations. In this work, long-term experiments were conducted on a new 4-electrode microfluidic MFC design, which grew Geobacter sulfurreducens biofilms on upward- and downward-facing electrodes in the microchannel. It was discovered that inoculation and growth of the electroactive biofilm did not proceed as fast as the downward facing anode, which we hypothesize is due to gravity effects that negatively impacted bacterial settling on that surface. Rotating the device during the growth phase resulted in uniform and strong outputs from both sides, yielding individual power densities of 4.03 and 4.13 W m-2, which was increased to nearly double when the top- and bottom-side electrodes were operated in parallel as a single 4-electrode MFC. Similarly, acetate consumption could be doubled with the 4-electrodes operated in parallel.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.254
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes2
Has abstractyes

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