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Record W4393040744 · doi:10.21203/rs.3.rs-4124588/v1

Surfactant-tolerant Cathodes for Electrochemical Generation of Hydrogen Peroxide for Wastewater Treatment

2024· preprint· en· W4393040744 on OpenAlexaff
Dzmitry Malevich, Sreeman Mypati, S. Ray, Cao‐Thang Dinh, Dominik P. J. Barz

Bibliographic record

VenueResearch Square · 2024
Typepreprint
Languageen
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsQueen's University
Fundersnot available
KeywordsHydrogen peroxidePulmonary surfactantElectrochemistryWastewaterCathodeCathodic protectionChemistryWaste managementPulp and paper industryEnvironmental scienceInorganic chemistryMaterials scienceChemical engineeringEnvironmental engineeringOrganic chemistryEngineeringElectrodeBiochemistry

Abstract

fetched live from OpenAlex

Abstract Cathode materials based on carbon substrates are of high interest for the electrochemical generation of hydrogen peroxide (H 2 O 2 ) for wastewater treatment because of their low cost, chemical stability and high selectivity. However, the H 2 O 2 selectivity of carbon materials can be significantly reduced in presence of surfactants, which are frequent contaminants in wastewater. Therefore, the development of surfactant-tolerant cathode materials is highly important. In this paper, composite electrodes comprising of polytetrafluoroethylene and carbon black on a carbon felt substrate were prepared. The effect of sodium dodecyl sulphate on the electrode activity was investigated. It was found that the electrodes prepared with high bulk density carbon black featured a high H 2 O 2 Faradaic efficiency of 95% in surfactant-free solutions. These electrodes also showed significant surfactant tolerance having a 70% Faradaic efficiency in the presence of 1mM sodium dodecyl sulphate. The enhanced surfactant tolerance is attributed to the hydrophobic properties of the electrode surface.

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)
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 score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.001
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 head0.096
GPT teacher head0.388
Teacher spread0.292 · 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.

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
Published2024
Admission routes1
Has abstractyes

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