Synthesis of Porous Polymers by Nucleophilic Substitution Reaction of Polyamines and Monochlorotriazinyl-β-Cyclodextrin and Application to Dye Adsorption
Bibliographic record
Abstract
Network polymers with β-cyclodextrin moieties were prepared by nucleophilic substitution reactions between polyamines, linear polyethyleneimine (LPEI), polyallylamine (PAA), (ε-poly-L-lysine) (EPL), and monochlorotriazinyl-β-cyclodextrin (MCTCD) in methanol/water mixed solvent or water. The reactions under conditions of high material concentration (30 wt%) and a feed ratio of [MCT]/[NH] = 0.5 (mol/mol) successfully yield porous polymers via reaction-induced phase separation. The molecular structure of the polyamines and reaction conditions strongly affected the morphology of the resulting porous polymers. The porous polymers were composed of connected particles, gathered (slightly connected) particles, and/or disordered bulky structures, with sizes of 10−9 m–10−8 m. An increase in the molecular weight of LPEI and PAA and the feed molar ratio of [MCT]/[NH] tended to decrease the particle size. Young’s moduli of the LPEI-MCTCD and PAA-MCTCD porous polymers increased with an increase in bulk density, which was derived from small particle sizes. The wide particle size distribution and disordered structure caused collapse by the compression under 50 N of pressure. An LPEI-MCTCD adsorbed methyl orange, methylene blue, and phenolphthalein through ionic interactions, π–π interaction, and/or β-cyclodextrin inclusion.
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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".