Adsorptive Removal of Phosphate and Nitrate Anions from Aqueous Solutions Using Ammonium-Functionalized Mesoporous Silica
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Adsorption of nitrate and monovalent phosphate anions from aqueous solutions on ammonium-functionalized mesoporous MCM-48 silica was investigated. The adsorbent was prepared via a post-synthesis grafting method, using aminopropyltriethoxysilane, followed by acidification in HCl solution to convert the attached surface amino groups to ammonium moieties. The adsorbent was determined to be effective for the removal of both anions. The effects of pH, temperature, initial concentration of anions, and adsorbent loading on both anions adsorption were examined. At ambient temperature, the removal of nitrate was maximum at pH <8, whereas phosphate removal was maximized at 4 < pH < 6. At a given initial concentration, the percentage anions removal increased as the adsorbent loading increased. For instance, maximum removals of 71% and 88% were obtained for nitrate and phosphate solutions, respectively, using an adsorbent loading of 10 g/L. The results also showed that the adsorption capacity decreased as the temperature increased. The adsorption isotherms were approached by the standard adsorption model equations. Based on a model discrimination study, only the Freundlich model resulted in physicochemically sound adsorption enthalpies and entropies for both anions. Desorption of both anions was rapidly achieved within 10 min, using 0.01 M NaOH. Regeneration tests showed that the adsorbent retained its capacity after five adsorption−desorption cycles.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it