Soluble–Insoluble–Soluble Transitions of Thermoresponsive Cryptand-Containing Graft Copolymers
Bibliographic record
Abstract
Abstract Cryptand-containing alternative copolymers were first made from copolymerization of styrenic derivatives and maleic anhydride and then chemically modified in this work by grafting methoxy poly(ethylene glycol) (MPEG) onto the maleic functional groups. These graft copolymers show interesting multistep soluble–insoluble–soluble (S–I–S) transitions in acidic aqueous media at a cloud point (Tcp) and a subsequent mixing temperature (Tmix). Turbidity measurements and dynamic light scattering studies indicate that such complex transitions may be attributed to the entropic contribution associated with the dehydration and aggregation of the MPEG groups and then the enthalpic contribution associated with the hydrogen bonding between ethylene glycol and carboxylic acid groups. More importantly, the phase transition temperatures and insoluble temperature ranges are very sensitive to changes in subtle hydrophobic–hydrophilic balance of the copolymers, such as the variation of pH, the cryptand size, and the length of the MPEG graft. The understanding of the S–I–S transition in relation to the structure of the copolymers and the external conditions may be useful in the design of smart materials and sensors.
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 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) | 0.002 | 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".