Poly (<i>N</i>-Isopropylacrylamide) Microgels for Organic Dye Removal from Water
Bibliographic record
Abstract
The ability of poly (N-isopropylacrylamide) (pNIPAm), and pNIPAm-co-acrylic acid (pNIPAm-co-AAc) microgels to remove an organic azo dye molecule, 4-(2-Hydroxy-1-naphthylazo) benzenesulfonic acid sodium salt (Orange II) from aqueous solutions at both room and elevated temperature was assessed. At room temperature, we found that the amount of Orange II removed from water (removal efficiency) increased with increasing AAc and microgel concentration. The removal of Orange II from water was also fit by a Langmuir sorption isotherm model. Furthermore, we found the extent of Orange II removal depended on solution temperature; more Orange II was removed from water at elevated temperature and as the microgels were held at that temperature for longer durations of time. Additionally, by increasing the cycles between high and ambient temperature, the removal of Orange II was enhanced, although this was only true for two temperature cycles. We hypothesize that this is a result of the thermoresponsive nature of pNIPAm-based microgels which deswell at elevated temperature expelling their solvating water and when the microgels are cooled back down they reswell with the Orange II containing water. We also hypothesize that the microgels become saturated after the second heating cycle and so the efficiency of removal did not increase further. Finally, we assessed the ability of the microgels to retain the Orange II after it is removed from the aqueous solution. We determined that the microgels "leak" 25.6% of the Orange II that was originally removed from the water.
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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 | 0.000 | 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".