Development of modified natural zeolites and study of phosphate removal from aqueous solutions
Bibliographic record
Abstract
Lake eutrophication has been an issue in many countries including Canada. Controlling and reducing the level of phosphorus, which is available as a form of phosphate in water, have been studied to manage the lake eutrophication. Natural zeolite-based adsorbents are one of the best candidates for water treatment due to its wide availability, cost-effectiveness, and superior characteristics as an ion exchanger. In this study, the concept of struvite crystallization was employed to develop magnesium-ammonium-modified zeolites (MNZ). Their removal capacity of phosphate was tested with comparison of magnesium-modified zeolites (MZ) based on the design of experiments (DOE) and response surface methodology (RSM). According to RSM, MNZ was found to be more effective in removing phosphates from aqueous solutions up to 92% of removal since MZ was effective up to 46% of removal. Contact time and zeolite dosage were found to be the significant parameters on phosphate removal.
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.
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".