Hybrid Free-Radical/Cationic Phase-Separated UV-Curable System: Impact of Photoinitiator Content and Monomer Fraction on Surface Morphologies and Gloss Appearance
Bibliographic record
Abstract
Simultaneous photopolymerization of radical and cationic systems is one strategy to generate polymer network architectures named interpenetrating polymer networks (IPNs). In these hybrid systems, phase separation and final polymer morphology are ultimately governed by thermodynamic incompatibility and polymerization kinetics. This behavior is quite complex, as numerous factors can affect polymerization kinetics including monomer/oligomer viscosity and structure, light intensity, photoinitiator content and absorbance, cross-linking, vitrification, etc. In this work, the impact of photoinitiator concentration and monomer fraction on surface morphologies in a hybrid radical/cationic phase-separated system was examined. Wrinkles formed on the surface of photopolymerized films depend on the polymerization rate and acrylate/epoxy ratio. This phenomenon is partially explained by the rapid polymerization rate associated with the development of an epoxy matrix and a smaller acrylate domain. The size and shape of the wrinkles can be controlled by varying formulation parameters (mainly, composition) and photoinitiator content. It was possible to create surface roughness and consequently decrease the gloss by controlling the polymerization kinetics and phase-separated morphology. This study demonstrates that the morphology, polymerization kinetics, and film properties (e.g., gloss, transparency) can be manipulated with the ratio of the acrylate/epoxy mixture and the photoinitiator content.
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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".