Evaluation of Non-Imprinted Polymer Particles for Advanced Treatment of Water and Wastewater
Bibliographic record
Abstract
This research evaluated the use of non-imprinted polymers (NIP) for treatment of micropollutants and heavy metals.NIP were also compared to powdered activated carbon in competition with humic acid and wastewater.Lastly, conventional separation methods for suspended solids such as centrifugation, filtration, and ballasted sand flocculation were evaluated for removal of NIP particles following treatment.In Chapter 5, NIP were evaluated for removal of EDCs and pharmaceuticals from water and wastewater.NIP were highly effective at removing EDCs from single solute solutions, and were also able to remove EDCs from a 0.5 ppm mixture of five EDCs.They were able to remove 9 out of 12 of the pharmaceuticals to some degree from deionized water and 3 out of 7 of the pharmaceuticals measured in wastewater.Overall, NIP were effective for removal of EDCs, but further study is required to determine whether they can remove pharmaceuticals.In Chapter 6, NIP were shown to be very effective for removal of lead from both river water and wastewater, but less effective for other heavy metal ions.Chapter 7 investigated mechanisms of competition for non-imprinted polymers (NIP) and activated carbon with humic acid and wastewater.Experiments were conducted for single-solute adsorption of methylene blue dye, simultaneous adsorption with humic acid and wastewater, and pre-loading with humic acid and wastewater followed by adsorption of the dye.The only decrease observed was for simultaneous adsorption with humic acid for NIP (for a 90% confidence limit).Humic acid and wastewater increased adsorption for the activated carbon, Norit PAC 200, for pre-loading with humic acid and simultaneous 1 exposure to wastewater.Adsorbed humic acid or NOM from wastewater may have increased the negative surface charge of the activated carbon and increased adsorption, cancelling out decreases due to competition.In Chapter 8, removal of NIP following treatment was investigated using conventional separation methods for suspended solids such as filtration, centrifugation, and ballasted flocculation.Centrifugation was the most effective, followed by filtration, and ballasted flocculation, but all three separation methods effectively removed NIP particles.The results of this thesis showed that NIP have strong potential for water and wastewater treatment.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".