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Record W2150549729 · doi:10.1039/c0lc00494d

A μL-scale micromachined microbial fuel cell having high power density

2011· article· en· W2150549729 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLab on a Chip · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Fuel Cells and Bioremediation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMicrobial fuel cellAnodePolydimethylsiloxaneMicroelectromechanical systemsPower densityCathodeMaterials scienceFaraday efficiencyGeobacterInternal resistanceCurrent densityChemical engineeringNanotechnologyChemistryElectrodePower (physics)BiofilmBacteriaBattery (electricity)Physics

Abstract

fetched live from OpenAlex

We report a MEMS (Micro-Electro-Mechanical Systems)-based microbial fuel cell (MFC) that produces a high power density. The MFC features 4.5-μL anode/cathode chambers defined by 20-μm-thick photo-definable polydimethylsiloxane (PDMS) films. The MFC uses a Geobacter-enriched mixed bacterial culture, anode-respiring bacteria (ARB) that produces a conductive biofilm matrix. The MEMS MFC generated a maximum current density of 16,000 μA cm(-3) (33 μA cm(-2)) and power density of 2300 μW cm(-3) (4.7 μW cm(-2)), both of which are substantially greater than achieved by previous MEMS MFCs. The coulombic efficiency of the MEMS MFC was at least 31%, by far the highest value among reported MEMS MFCs. The performance improvements came from using highly efficient ARB, minimizing the impact of oxygen intrusion to the anode chamber, having a large specific surface area that led to low internal resistance.

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.

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 categoriesInsufficient 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 score0.407
Threshold uncertainty score0.998

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)0.0070.003

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 head0.007
GPT teacher head0.172
Teacher spread0.165 · 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