Incorporation of <scp>POSS</scp> to improve thermal stability of <scp>bio‐based</scp> polymethacrylates by <scp>nitroxide‐mediated</scp> polymerization: Polymerization kinetics and characterization
Bibliographic record
Abstract
Abstract Nitroxide‐mediated polymerization (NMP) was used to polymerize methacrylate‐functionalized polyhedral oligomeric silsesquioxane, POSSMA, in a controlled manner with bio‐based C13 methacrylate (C13MA) to improve the thermal stability of the latter by copolymerization (using 10 mol% acrylonitrile controlling comonomer). Kinetic experiments (80–110 °C) revealed the relatively low ceiling temperature of POSSMA (135 °C). Synthesis of poly(POSSMA‐co‐AN) with f AN,0 = 0.10 at 90 °C resulted in low dispersity (1.16) and relatively high conversion (~50%) after 3 hr in 50 wt% toluene. Assuming binary statistical copolymerizations, POSSMA was slightly less reactive than C13MA toward the propagating species (r POSSMA = 0.91 ± 0.07 and r C13MA = 1.94 ± 0.13). Incorporating POSSMA up to 68 mol% improved decomposition temperature of C13MA‐based copolymers from 190 to 262 °C. Chain end fidelity of POSSMA‐rich compositions was confirmed by subsequent chain extensions to make block and gradient copolymers. Differential scanning calorimetry revealed multiple transition temperatures in block copolymers, suggesting microphase separation. Powder X‐ray diffraction confirmed crystalline domains ~30 nm in POSSMA‐rich statistical copolymers while transmission electron microscopy revealed weakly ordered lamellar morphology for poly(C13MA‐co‐AN)‐b‐(POSSMA‐co‐AN) block copolymer at a smaller length scale. Oscillatory shear measurements of block copolymers indicated primarily viscous character below 200 s−1 but crossover above this frequency, indicating POSS–POSS interactions were increasing the elasticity of the block copolymers.
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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".