SYNTHESES OF UV-CURABLE HYPERBRANCHED POLYSILOXANES AND STUDIES ON THEIR PHOTO-CURING BEHAVIOR
Bibliographic record
Abstract
UV-curable hyperbranched polysiloxanes were synthesized via hydrolysis of γ-methacryloxyprop-yltrimethyloxysilane (A-174) by controlling the amount of water.Macromolecular structures of the polymers obtained were characterized and confirmed by FT-IR, ~1H-NMR spectra and multi-angle laser light scattering technology(MALLS).The results indicated that the hyperbranched polysiloxanes carrying a large amount of functional vinyl groups could be cured under UV-irradiation.Their photo-initiated curing kinetics were studied by isothermal differential photo calorimeter (DPC) test.It was found that both the polymerization rate and the ultimate conversion first increased and then decreased with the increase in the molecular weight of the polymer and the photoinitiator concentration.The increase in UV-light intensity can lead to increase of both the polymerization rate and the ultimate conversion,and particularly, the polymerization rate is proportional to the square root of light intensity.Although elevated temperature can indeed improve the polymerization rate and the ultimate conversion,the effect of temperature on polymerization rate is not prominent.The total exponent of the photo-polymerization of the polymer 3# is about 3,and the apparent activation energy is 16.9 kJ/mol,calculated from an autocatalytic model.
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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 | 0.001 |
| 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".