Shrinkage Stress and Temperature Variation in Resin Composites Cured via Different Photoactivation Methods: Insights for Standardisation of the Photopolymerisation
Bibliographic record
Abstract
The literature has shown that there is no consensus regarding the best resin composite photoactivation protocol. This study evaluated the efficiency of the conventional, soft-start, pulse-delay and exponential protocols for photoactivation of resin composites in reducing the shrinkage stress and temperature variation during the photopolymerisation. The photoactivation processes were performed using a photocuring unit and a smartphone app developed to control the irradiance according each photoactivation protocol. These photoactivation methods were evaluated applying photoactivation energies recommended by the resins manufactures. Three brands of resin composites were analysed: Z-250, Charisma and Ultrafill. The cure effectiveness was evaluated through depth of cure experiments. All results were statistically evaluated using one-way and multi-factor analysis of variance (ANOVA). The use of exponential and pulse-delay methods resulted in a significant reduction of the shrinkage stress for all evaluated resins; however, the pulse-delay method required too long a photoactivation time. The increases on the temperature were lower when the exponential photoactivation was applied; however, the temperature variation for all photoactivation protocols was not enough to cause damage in the restoration area. The evaluation of the depth of cure showed that all photoactivation protocols resulted in cured resins with equivalent hardness, indicating that the choice of an alternative photoactivation protocol did not harm the polymerisation. In this way, the results showed the exponential protocol as the best photoactivation technique for practical applications.
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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".