Influence of temperature and primer application on setting time and degree of conversion of a dual-cure self-adhesive cement
Bibliographic record
Abstract
OBJECTIVES: To examine the in vitro effect of different temperatures and use of a primer on the setting time (ST) and degree of conversion (DC) of a novel dual-cure self-adhesive cement (Set Maxx, SDI Limited). METHODS: Set Maxx was tested alone or with Stela Primer (SDI), both with light curing (LC) for 20 s with the Valo X (Ultradent), or it was allowed to self-cure (SC). The ST was determined according to ISO 4049 (n = 5). To measure DC, the cement was dispensed onto a temperature-controlled ATR sensor on an FT-IR spectrometer set at 23 °C, 32 °C, or 37 °C. The rates of polymerization and DC were measured for 1800 s (n = 4). The temperature increase was also measured at the bottom using a K-type thermocouple (n = 3). The results were compared using ANOVA and Tukey's multiple comparison test (α=0.05). RESULTS: The setting time was longer for the 23 °C group that used no primer (149 s ± 2.6). The highest DC was observed when using the primer at 37 °C in the SC (75.1 % ± 2.2) and LC (76.5 % ± 1.8) groups. Light exposure had a negligible effect on the final DC; however, it had the most significant impact on the maximum rate of change in the DC during polymerization. This was likely due to heat from the light, with the highest rate for the LC group at 37 °C (7.7 %/s ± 0.4) and a temperature increase of 41.7 °C ± 3.2. CONCLUSIONS: Compared to using no Primer and at a temperature of 23 °C, using 37 °C and Stela Primer enhanced the DC of Set Maxx. Light exposure alone did not substantially increase the final DC, but it did increase the reaction rate and accelerate the polymerization. CLINICAL SIGNIFICANCE: Combining the Stela Primer with light exposure achieved the highest DC in Set Maxx. Laboratory studies conducted at room temperature should be reevaluated and repeated at intraoral temperatures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".