Kinetic and parametric studies of refinery effluent treatment in electrochemical reactor
Bibliographic record
Abstract
Treatment of refinery effluent using an electrocoagulation reactor assisted with a natural coagulant, from Acacia tortilis, was investigated under controlled operating conditions. The influence of process variables – namely, type of electrode (copper (Cu), steel and aluminium (Al)), effluent pH (3·5–11·5), influent chemical oxygen (O 2 ) demand (COD) of the effluent (605–2420 mg/l), coagulant dosage (1·0–6·0 g/l), voltage (15–45 V) and current (1·5–2·5 A) – on the COD removal efficiency was investigated. Among the different electrodes tested, the aluminium electrode performed well and could remove 74·2% at an equilibrium time of 90 min. Formation of the aluminium hydroxide (Al(OH) 3 ) complex was identified as the working mechanism. The optimal conditions for better COD removal efficiency were identified as pH 5·5, coagulant dose of 4·0 g/l, voltage of 45 V and current of 2·5 A. The empirical relationship between the coagulant dose and the COD removal percentage was found to be exponential in nature. A pseudo-second-order kinetic model was found to represent the experimental data very well (coefficient of determination > 0·900) and the kinetic constant (k 2 ) was estimated as 0·20 × 10 −3 (g/mg)/min at an initial effluent COD of 2420 mg/l.
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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".