Phosphate Removal from Wastewater by Magnetic Amorphous Lanthanum Silicate Alginate Hydrogel Beads
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Bibliographic record
Abstract
It is of both fundamental and practical importance to develop effective adsorbents for removing phosphate from aqueous solutions continuously. In this study, magnetic amorphous lanthanum silicate alginate hydrogel beads (MALS-B) were prepared and used for phosphate removal. Mesoporous silica materials with highly ordered and hexagonal channel structures were synthesized from natural mineral rectorite (REC) at room temperature. On this basis, amorphous lanthanum silicate (ALS) was synthesized by theone-pot method using a silicon source from REC and a commercial lanthanum source. Further, MALS-B were synthesized from sodium alginate (SA) with ALS and Fe3O4 as the incorporated adsorbable and magnetic nanoparticles via a simple cross-linking method in CaCl2 solution. The synthesized hydrogel beads were characterized by various techniques. ALS and Fe3O4 existed relatively independently in MALS-B, where ALS provided adsorption sites and Fe3O4 provided magnetism. They played a synergistic role in phosphate removal. The saturation magnetization value of MALS-B was 17.38 emu/g, enabling theirfacile separation from aqueous solutions after phosphate adsorption. MALS-B exhibited a preferable adsorption capacity of 40.14 mg P/g for phosphorus compared to other hydrogel beads based on adsorption experiments. More significantly, MALS-B exhibited excellent selectivity for phosphate in aqueous solutions with various interfering ions and possessed a high affinity to phosphate in a wide pH range. MALS-B showed the treatment volume of 480 BV when effluent phosphate concentration was below 0.5 mg/L in fixed-bed column adsorption. The adsorption mechanism was also revealed. Our work demonstrates that MALS-B can serve as a promising adsorbent for continuous phosphate adsorption.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.019 | 0.001 |
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 it