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Record W2088544305 · doi:10.1139/v10-081

Electrochemical oxidation of sulfide ion in synthetic sour brines using periodic polarity reversal at Ebonex<sup>®</sup> electrodes

2010· article· en· W2088544305 on OpenAlexaffvenue
Shaimaa El-Sherif, Dorin Bejan, Nigel J. Bunce

Bibliographic record

VenueCanadian Journal of Chemistry · 2010
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsChemistryInorganic chemistryElectrochemistrySulfideOxideChlorideAnodeHypochloriteLead dioxideElectrodeOrganic chemistry

Abstract

fetched live from OpenAlex

The Magneli phase Ti4O7 (Ebonex®) was used as both anode and cathode in the electrochemical oxidation of sulfide ion in alkaline solution in the absence and presence of chloride and naphthenate ions. Ebonex anodes gradually lost their activity through the formation of an over-oxidized surface layer, but their activity could be maintained by periodic polarity reversal. In the context of the current paradigm for the mechanistic behaviour of oxide-based anodes, Ti4O7 has properties that combine those of “inactive” anodes (formation of hydroxyl radicals) and “active” anodes (formation of a higher oxide at the surface), with the exception that the higher oxide in the case of Ti4O7 is TiO2, which is incapable of substrate oxidation. Sulfate is the major oxidation product, especially in the presence of chloride, an ubiquitous component of sour brines, via mediated electro-oxidation to hypochlorite. Unlike at boron-doped diamond anodes, at which sulfide is oxidized with near-quantitative current efficiency, significant parasitic oxidation of water to O2 occurs at Ebonex, and oxidation of sulfide requires ~16 F mol–1, corresponding to a 50% current efficiency.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.006
GPT teacher head0.211
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), 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

Citations31
Published2010
Admission routes2
Has abstractyes

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