MétaCan
Menu
Back to cohort

Modular microbial fuel cells with all graphite microchannels for low internal resistance and high conversion efficiency

2025· article· en· W4416038167 on OpenAlexafffund
Linlin Liu, William Varroy, Friday James Amaku, Marc-Antoine Bansept, Changhong Cao, Denis Boudreau, Jesse Greener

Bibliographic record

VenueJournal of Power Sources · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Fuel Cells and Bioremediation
Canadian institutionsCentre hospitalier de l'Université LavalCentre hospitalier universitaire de QuébecMcGill UniversityUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaGénome QuébecSentinelle Nord, Université LavalGenome CanadaUniversité Laval
KeywordsInternal resistanceMicrofluidicsMicrobial fuel cellModular designMicroscale chemistryGeobacter sulfurreducensGraphiteStack (abstract data type)Current (fluid)

Abstract

fetched live from OpenAlex

We present a new microbial fuel cell (MFC) design in which the microchannels are fabricated entirely from graphite. The microfluidic all-graphite MFC (μG-MFC) supports pure-culture Geobacter sulfurreducens electroactive biofilms (EABs). Iterative design reduced internal resistance and produced architecture-dependent performance gains. Narrow, unstructured channels yielded relatively high power and current densities, whereas a wide, micropillar-structured channel achieved the highest raw outputs, enabled by one of the lowest internal resistances reported for any microfluidic MFC (1.2 kΩ). This low resistance also produced record acetate conversion efficiency (82 %) and normalized energy recovery (0.83 kWh m −3 ), among microscale MFCs. To demonstrate modularity and system-level benefits, we ran multiple modules as stacks. This further reduced internal resistance to 480 Ω and enabled power and current increases to 700 μW and 1.5 mA, sufficient to power an environmental multi-sensor. We discuss scaling stacks up to thousands of modules as a means to provide a viable platform for low-cost remediation, with projected operating costs that are competitive with state-of-the-art wastewater treatment systems.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
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 score0.176
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

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

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 head0.002
GPT teacher head0.176
Teacher spread0.174 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Power SourcesSame topicMicrobial Fuel Cells and BioremediationFrench-language works237,207