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Record W2887549346 · doi:10.1016/j.btre.2018.e00276

Hydrogen peroxide production in a pilot-scale microbial electrolysis cell

2018· article· en· W2887549346 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

VenueBiotechnology Reports · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Fuel Cells and Bioremediation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMicrobial electrolysis cellElectrolysisHydrogen peroxideChemistryCathodeHydrogen productionMembraneIon exchangeCarbon fibersDecompositionCathodic protectionYield (engineering)Inorganic chemistryHydrogenChemical engineeringNuclear chemistryElectrochemistryIonMaterials scienceElectrodeBiochemistryOrganic chemistryMetallurgy

Abstract

fetched live from OpenAlex

A pilot-scale dual-chamber microbial electrolysis cell (MEC) equipped with a carbon gas-diffusion cathode was evaluated for H2O2 production using acetate medium as the electron donor. To assess the effect of cathodic pH on H2O2 yield, the MEC was tested with an anion exchange membrane (AEM) and a cation exchange membrane (CEM), respectively. The maximum current density reached 0.94–0.96 A/m2 in the MEC at applied voltage of 0.35–1.9 V, regardless of membranes. The highest H2O2 conversion efficiency was only 7.2 ± 0.09% for the CEM-MEC. This low conversion would be due to further H2O2 reduction to H2O on the cathode or H2O2 decomposition in bulk liquid. This low H2O2 conversion indicates that large-scale MECs are not ideal for production of concentrated H2O2 but could be useful for a sustainable in-situ oxidation process in wastewater treatment.

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 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 score0.016
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.184
Teacher spread0.180 · 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