Preparation and sorption studies of microsphere copolymers containing β‐cyclodextrin and poly(acrylic acid)
Bibliographic record
Abstract
Abstract Microsphere polymeric materials containing β‐cyclodextrin (β‐CD) and poly(acrylic acid) (PAA) with tunable morphologies were prepared in order to improve their sorption characteristics in aqueous solution. The microsphere polymeric materials were prepared using a (water/oil) micro‐emulsion‐evaporation technique to condense β‐cyclodextrin (β‐CD) with PAA at various comonomer ratios and mixing speeds. The β‐CD microsphere copolymers were characterized using FTIR, TGA, DSC, SEM, elemental (C and H) microanalyses, and solid state 13C‐NMR spectroscopy. The sorption properties of the polymeric materials at 295 K in aqueous solution containing p‐nitrophenol (PNP) were studied using a dye‐based method with UV–Vis spectrophotometry at pH 4.6 and 10.3. The sorption isotherms of copolymer/PNP systems were evaluated with various isotherm models (e.g., Langmuir, BET, Freundlich, and Sips). The Sips isotherm showed the best overall agreement with the experimental results and the sorption parameters provided estimates of the sorbent surface area (12.0–331 m2/g) and the sorption capacity (Qm = 0.359–2.20 mmol/g at pH = 4.6; Qm = 0.070–0.191 mmol/g at pH = 10.3) for the microsphere copolymer/PNP systems in aqueous solution. The nitrogen adsorption properties of the microporous copolymers in the solid state were obtained at 77K with BET surface areas ranging from 0.275 to 4.47 m2/g. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012
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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) | 0.001 | 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 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".