Simultaneous removal of phosphate and ammonium using salt–thermal-activated and lanthanum-doped zeolite: fixed-bed column and mechanism study
Bibliographic record
Abstract
Assessment of breakthrough performance of NaCl–Thermal–LaCl3 synthetic modified zeolite continuous flow fixed-bed column on the simultaneous removal of phosphate and ammonium from simulated municipal wastewater was conducted. Variable parameters, including solution pH, bed depth, effluent flow rate, and input concentration, were examined for this study. The results indicated that the adsorption capacity increased with the increase in bed depth and input concentration and decrease of effluent flow rate for both phosphate and ammonium. Thomas and Yoon–Nelson models were found to give the better fitness to experiment data of the whole breakthrough curves, whereas Adams–Bohart model could only predict the initial part of the breakthrough using linear regression analysis. The bed depth service time model of breakthrough data showed that the time for the movement of the mass transfer zone increased with the increase in bed height and flow rate and decrease in initial concentration. Best fixed-bed column performance was obtained at high fixed bed depth, low effluent flow rate, and low initial concentration. Successful desorption and regeneration were achieved with 0.2 M HCl and 0.1 M NaOH. BET, scanning electron microscopy, energy dispersive X-ray spectroscopy, and FTIR and X-ray photoelectron spectra analyses confirmed that ammonium removal was mainly ascribed to exchanging with sodium in the adsorbent, and phosphate adsorption mainly followed the surface complexion mechanism; the surface hydroxyl groups played the key role. All the results proved that the column could be promising option for the simultaneous removal of phosphate and ammonium at lower concentrations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 source (direct Gemma or distilled Codex), 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".