CO<sub>2</sub>/N<sub>2</sub>-Switchable Thermoresponsive Ionic Liquid Copolymer
Bibliographic record
Abstract
Thermoresponsive random copolymers consisting of poly( N -isopropylacrylamide) (PNIPAM) and polymerized ionic liquid (IL) poly(1,1,3,3-tetramethylguanidine acrylate) (PTMGA) were synthesized via reversible addition–fragmentation chain transfer radical polymerization (RAFT). The reactivity ratios of NIPAM ( r NIPAM = 2.11) and TMGA ( r TMGA = 0.56) were determined by the extended Kelen–Tödüs method. Glass transition temperatures ( T g ) of the copolymers were analyzed, which followed the Fox equation very well. The phase transition behaviors of the copolymers in aqueous solution were studied through UV–vis transmission measurements. Their lower critical solution temperature (LCST) ranged from 30.5 to 73.2 °C, depending on the hydrophilic IL content. The apparent p K a related to LCST was determined, and thus the protonation degree was calculated. The hydrophilicity of the copolymers could be regulated by gas treatments. Bubbling CO 2 led to lowering the transition temperature while bubbling N 2 resulted in its recovery. This CO 2 /N 2 switchability became more profound with higher IL content. With the ability to undergo reversible protonation caused by the change of pH, the system showed good reversibility in LCST when bubbled with CO 2 and N 2 . SO 2 could also be used to lower LCST. However, a basic compound (e.g., NaOH) was required for its recovery. The pH-dependent solution phase transition behavior provided great insight into the LCST regulation mechanism. The widest LCST shifting window (∼12 °C) was found between pH 5.16 and 5.96, which could be fulfilled by the CO 2 regulation approach. This work provides guidance for the design and synthesis of gas-switchable thermoresponsive polymers based on ionic liquids.
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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) | 0.001 | 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".