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Record W109178291

Electrochemical oxidation of polyethylene glycol in electroplating solution using paraffin composite copper hexacyanoferrate modified (PCCHM) anode.

2004· article· en· W109178291 on OpenAlexaff
Rajesh S Bejankiwar, Abir Basu, Max Cementi

Bibliographic record

VenuePubMed · 2004
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsAnodeEthylene glycolOxalic acidElectrolysisElectrochemistryElectroplatingMaterials scienceFormic acidInorganic chemistryPolyethylene glycolCopperChemistryElectrolyteChemical engineeringNuclear chemistryElectrodeMetallurgyOrganic chemistryComposite material
DOInot available

Abstract

fetched live from OpenAlex

Electrochemical oxidation of polyethylene glycol (PEG) in an acidic (pH 0.18 to 0.42) and high ionic strength electroplating solution was investigated. The electroplating solution is a major source of wastewater in the printing wiring board industry. A paraffin composite copper hexacyanoferrate modified (PCCHM) electrode was used as the anode and a bare graphite electrode was used as the cathode. The changes in PEG and total organic carbon (TOC) concentrations during the course of the reaction were monitored. The efficiency of the PCCHM anode was compared with bare graphite anode and it was found that the former showed significant electrocatalytic property for PEG and TOC removal. Chlorides present in the solution were found to contribute significantly in the overall organic removal process. Short chain organic compounds like acetic acid, oxalic acid, formic acid and ethylene glycol formed during electrolysis were identified by HPLC method. Anode surface area and applied current density were found to influence the electro-oxidation process, in which the former was found to be dominating. Investigations of the kinetics for the present electrochemical reaction suggested that the two stage first-order kinetic model provides a much better representation of the overall mechanism of the process if compared to the generalized kinetic model.

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 score0.007
Threshold uncertainty score0.547

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.038
GPT teacher head0.256
Teacher spread0.218 · 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
Published2004
Admission routes1
Has abstractyes

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