Evaluation of X-3B Dye Removal and COD Reduction from Dyeing Wastewater Using Iron Wastes and Coagulation Process
Bibliographic record
Abstract
This study was conducted to investigate the ability of zero valent iron (ZVI) available in iron solid wastes with coagulation processes to reduce (COD) content and remove the color from dyeing wastewater, and the mechanism of iron particles process for color degradation and COD reduction was inquired.(X-3B) dye was synthesized for dyeing wastewater.Using 440 L/hr of air flow and mixing at 500 rpm for 20 minutes, then 200 rpm for 10 minutes, while using 70g/L of iron shreds, (ZVI) showed that (COD) the content was reduced by 33% and color by 45% had been eliminated.FeCl3.6H2O,FeSO4.7H2O, and PAC were used in the coagulation process to determine which was best compatible with the ZVI process.The results showed that (PAC) tests with optimal dosages of 1200 mg/L had peak (COD) and color removal efficiency.(PAC) provided a 97% reduction in (COD) and a 98% elimination of color.The ideal mixing speed was 200 rpm of quick mixing followed by 40 rpm of gentle mixing.The findings showed that a 90-minute settling time produced the smallest volume of settled sludge.
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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 | 0.001 | 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".