MétaCan
Menu
Back to cohort
Record W2783991394 · doi:10.14447/jnmes.v17i2.426

Effective Electro-Fenton Degradation of Reactive Black 5 Dye using Modified Electrode with Cu-Zeolites

2014· article· en· W2783991394 on OpenAlexvenueno aff
Miguel A. Oliver‐Tolentino, Elmer Jiménez-Álvarez, Marı́a de Jesús Martı́nez-Ortiz, Efrén V. Garcı́a-Báez, Marina Olivia Franco-Hernández, Ariel Guzmán‐Vargas

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryCatalysisRedoxInorganic chemistryElectrodeZeoliteHydroxyl radicalCopperIonic bondingDegradation (telecommunications)Ion exchangePhotochemistryRadicalIonOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

The electrocatalytic production of hydroxyl radical (HO•) on the surface of zeolite modified electrode (ME) employing Cu-Zeolites (ZSM5 and β) with different theoretical ionic exchange (15 and 100%) was investigated (ME/Cu-Zeolites). The i-E characteristic of ME/Cu-ZSM-5 presented the faradic process associated to redox couple Cu2+/Cu+. On the other hand, voltammetric studies showed that in presence of H2O2, the cathodic peak current of ME/Cu-Zeolites increases followed by a decrease in the corresponding anodic current. This suggested that hydroxyl radical was produced by a cooperative effect of the acidic properties of zeolite and copper that acts as a redox mediator on the electrode surface via an electrocatalytic mechanism. Experiments of degradation using azo dye Reactive Black 5 as probe molecule exhibited that the concentration of azo dye decreased in the time, this confirms the formation of hydroxyl radical on the surface of modified electrode; kinetics parameters demonstrated that the ME/Cu- β with 15% of ionic exchange presented the highest catalytic activity.

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 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 score0.132
Threshold uncertainty score0.735

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.010
GPT teacher head0.244
Teacher spread0.234 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of New Materials for Electrochemical SystemsSame topicAdvanced oxidation water treatmentFrench-language works237,207