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Record W2009299263 · doi:10.2166/wst.2012.180

Electro-oxidation of two reactive azo dyes on boron-doped diamond electrode

2012· article· en· W2009299263 on OpenAlexaff
Fares Almomani, Elena A. Baranova

Bibliographic record

VenueWater Science & Technology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsElectrolysisChemistryChemical oxygen demandElectrochemistryElectrodeDiamondDegradation (telecommunications)BoronRedoxReactive dyeNuclear chemistryBulk electrolysisInorganic chemistryEnvironmental engineeringCyclic voltammetryWastewaterDyeingOrganic chemistry

Abstract

fetched live from OpenAlex

Electrochemical oxidation (decolorization/degradation) of blue and red commercial reactive azo dyes was carried out on boron-doped diamond (BDD) electrode. The effect of various quantities of FeSO(4) was investigated in the electro-Fenton reaction on BDD. Progress of dyes degradation during the electrolysis and electro-Fenton reaction was monitored by UV-visible absorption and by estimation of the chemical oxygen demand (COD). Direct electrolysis showed a limiting capacity for red and blue dye removal even at high current densities, e.g. maximum red color and COD removal were 70 and 20%, respectively at 30 mA cm(-2) after 300 min. Higher red and blue color removal efficiencies were achieved by electro-Fenton oxidation. Current density of 30 mA cm(-2) in the presence of 0.05 mmol/L of FeSO(4) resulted in the red color and COD removal of 98 and 96%, respectively. The optimum FeSO(4) concentration for the electro-Fenton reaction was determined to be 0.05 mmol/L. Instantaneous current efficiency (ICE) in the presence of FeSO(4) was almost three times higher than for experiments carried out without FeSO(4).

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 score0.020
Threshold uncertainty score0.861

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.254
Teacher spread0.247 · 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

Citations8
Published2012
Admission routes1
Has abstractyes

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