Electrochemical oxidation of polyethylene glycol in electroplating solution using paraffin composite copper hexacyanoferrate modified (PCCHM) anode.
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".