Simultaneous Removal of Cyanide and Heavy Metals Using Photoelectrocoagulation
Bibliographic record
Abstract
One of the new methods used to remove the contaminants from effluent is the electrocoagulation method, which is sometimes combined with other methods to increase the removal efficiency of contaminants. To simultaneously remove nickel, cyanide, zinc, and copper, the combined method of photo-electrocoagulation was used along with an oxidizing agent, namely hydrogen peroxide (Hp). In addition, the effects of factors affecting the removal efficiency were studied, including pH, electrode arrangement, and current intensity. An electric current of 300 mA at a pH of 10 for 60 min, Fe-SS electrodes with a distance between them of 5 cm, and hydrogen peroxide at a rate of 4 mg/L were the ideal conditions needed to accomplish the photo-electrocoagulation-oxidation process. According to these study findings, when the combined method of photocatalyst-electrocoagulation-oxidation (Hp) was used, the highest removal efficiencies of nickel, cyanide, zinc, and copper were 85, 96, 94, and 98%, respectively. The results showed that using the combined photo-electrocoagulation-oxidation method increased the efficiency of simultaneous removal of pollutants by 10% compared to conventional electrocoagulation method. The reason for the increase in removal efficiency is the production of hydroxyl radicals simultaneously with the formation of coagulants produced by electrocoagulation process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 teacher head, 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".