Optimization of phosphorus recovery using electrochemical struvite precipitation and comparison with iron electrocoagulation system
Bibliographic record
Abstract
Abstract A batch monopolar reactor was developed for total phosphorus (TP) recovery using electrochemical struvite precipitation. This study involves the optimization of factors using response surface methodology to maximize the TP recovery. The optimal parameters for this study were found to be a pH of 8.40, a retention time of 35 min, a current density of 300 A/m 2 , and an interelectrode distance of 0.5 cm, resulting in 97.3% of TP recovery and energy consumption of 2.35 kWh/m 3 . A kinetic study for TP removal revealed that at optimum operating conditions, TP removal follows second‐order kinetics (removal rate constant(K) = 0.0117 mg/(m 2 ·min)). The system performance was compared to the performance of an iron electrocoagulation system. The composition of the precipitate obtained during the optimal runs were analyzed using X‐ray diffraction and EDS analysis. X‐ray diffraction analysis of the magnesium precipitate revealed the presence of struvite as the only crystalline compound. Practitioner Points Electrochemical struvite precipitation has the potential to recover total phosphorus from anaerobic bioreactor effluent. Optimum conditions for phosphorus recovery was found at a pH of 8.4, retention time of 35 min, current density of 300 A/m2, and interelectrode distance of 0.5 cm. The quadratic model predicted complete (100 %) TP recovery under optimized conditions, whereas 97.3 % recovery was observed under experimental conditions. TP removal under optimum conditions followed second‐order rate equation (removal rate constant(K) = 0.0117 mg/(m 2 ·min)). XRD analysis of the precipitate revealed struvite as the only crystalline compound.
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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".