Real-Time Cure Monitoring of Unsaturated Polyester Resin from Ultra-Violet Curing
Bibliographic record
Abstract
Real time Fourier transform infrared (RTFT-IR) spectroscopy reveals the influence of the nature of the photoinitiator on the kinetics for the polymerization reaction. Real time cure monitoring was used to determine the polymerization rate of ultra-violet cured unsaturated polyester resins (UPR1:2-1:5) based on palm oil and containing styrene as a cross-linking agent in the presence of IRGACURE 184 photoinitiator. Firstly, variable types of UPR1:2-1:5 were prepared using various ratios of monoglyceride (MG) monomer to maleic anhydride which used as a source of double bond using polycondensation technique. RTFT-IR spectroscopy was used to characterize the ultra-violet curing kinetics for all the systems. This technique offered a powerful approach for monitoring changes in the chemical properties of the system during the ultra-violet curing. Pseudo first order kinetics for all UPR1:2-1:5 curable systems were determined and the rate constant values and regression coefficients were calculated. Furthermore, the thermal behaviour and morphological features for the photo-fabricated UPR1:2-1:5 systems were examined. The thermal analyses for the cured films were evaluated by TGA, DTG and DSC in nitrogen atmosphere at a heating rate of 10°C/min. All the formulations showed similar degradation pattern at 40 % and 50 % weight losses (Td = 40% and Td =50% respectively) except polymer UPR1:5 which had somewhat lower degree in the same range. In addition, the morphological properties for photo-fabricated UPR1:2,1:3,1:5 were investigated by using scanning electron microscopy.
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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 | 0.001 |
| 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".