Assessment of denitrification using electrocoagulation process
Bibliographic record
Abstract
Abstract The objectives were to study the applicability of electrocoagulation (EC) for the denitrification of drinking water and to determine the main mechanisms of pollution removal. Electrolysis in the intensiostatic mode was applied to a synthetic water representative of potable water in which the concentration of nitrate ions was varied up to 200 mg/L. The respective influences of process parameters, initial concentration of nitrates, and initial pH were investigated. Experimental results show that EC removes efficiently nitrates, following first‐order kinetics. A two‐step mechanism was established: it consisted of the electroreduction of nitrates into ammonium on the cathode, followed by the adsorption of ammonium on the precipitated oxyhydroxides. Adsorption exhibited a zero‐order mechanism. The rates of the two mechanisms were proportional to electrical charge loading and to the total amount of aluminum released in water, as current did not modify significantly the surface area of precipitates. However, adsorption was impaired by the increase of pH resulting from the electroreduction of nitrates, whereas the electrochemical step was insensitive to pH. While the electroreduction of nitrates is known to be far more expensive than biological denitrification, aluminum hydroxides formed during EC present interesting adsorption properties for ammonium removal.
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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".