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Record W2257836161 · doi:10.3390/en9020078

A Systematic Study of Separators in Air-Breathing Flat-Plate Microbial Fuel Cells—Part 1: Structure, Properties, and Performance Correlations

2016· article· en· W2257836161 on OpenAlexafffund
Sona Kazemi, Madjid Mohseni, Khalid Fatih

Bibliographic record

VenueEnergies · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Fuel Cells and Bioremediation
Canadian institutionsNational Research Council CanadaUniversity of British Columbia
FundersNational Research Council CanadaAgriculture and Agri-Food CanadaNatural Sciences and Engineering Research Council of CanadaUniversity of British Columbia
KeywordsMicrobial fuel cellSeparator (oil production)ElectrodeCathodeAnodePower densityMaterials scienceNafionAnalytical Chemistry (journal)Composite materialChemistryChemical engineeringPower (physics)ChromatographyThermodynamicsEngineering

Abstract

fetched live from OpenAlex

Passive air-breathing microbial fuel cells (MFCs) are a promising technology for energy recovery from wastewater and their performance is highly dependent on characteristics of the separator that isolates the anaerobic anode from the air-breathing cathode. The goal of the present work is to systematically study the separator characteristics and its effect on the performance of passive air-breathing flat-plate MFCs (FPMFCs). This was performed through characterization of structure, properties, and performance correlations of eight separators in Part 1 of this work. Eight commercial separators were characterized, in non-inoculated and inoculated setups, and were examined in passive air-breathing FPMFCs with different electrode spacing. The results showed a decrease in the peak power density as the oxygen and ethanol mass transfer coefficients in the separators increased, due to the increase of mixed potentials especially at smaller electrode spacing. Increasing the electrode spacing was therefore desirable for the application of diaphragms. The highest peak power density was measured using Nafion®117 with minimal electrode spacing, whereas using Nafion®117 or Celgard® with larger electrode spacing resulted in similar peak powers. Part 2 of this work focuses on numerical modelling of the FPMFCs based on mixed potential theory, implementing the experimental data from Part 1.

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 score0.145
Threshold uncertainty score0.282

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 head0.009
GPT teacher head0.177
Teacher spread0.168 · 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

Citations13
Published2016
Admission routes2
Has abstractyes

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