Effect of Thickness on Light Transmission and Vickers Hardness of Five Bulk-fill Resin-based Composites Using Polywave and Single-peak Light-emitting Diode Curing Lights
Bibliographic record
Abstract
SUMMARY Objectives: This study compared light transmission through different thicknesses of bulk-fill resin-based composites (RBCs) using a polywave and a single-peak light-emitting diode light-curing unit (LCU). The effect on the surface hardness was also evaluated. Methods: Five bulk-fill RBCs were tested. Specimens (n=5) of 1-, 2-, 4-, or 6-mm thickness were photopolymerized for 10 seconds from the top using a polywave (Bluephase Style) or single–peak (Elipar S10) LCU, while a spectrophotometer monitored in real time the transmitted irradiance and radiant exposure reaching the bottom of the specimen. After 24 hours of storage in distilled water at 37°C, the Vickers microhardness (VH) was measured at top and bottom. Results were analyzed using multiple-way analysis of variance, Tukey post hoc tests, and multivariate analysis (α=0.05). Results: The choice of LCU had no significant effect on the total amount of light transmitted through the five bulk-fill RBCs at each thickness. There was a significant decrease in the amount of light transmitted as the thickness increased for all RBCs tested with both LCUs (p<0.001). Effect of LCU on VH was minimal (ηp2=0.010). The 1-, 2-, and 4-mm-thick specimens of SDR, X-tra Fill, and Filtek Bulk Restorative achieved a VHbottom/top ratio of approximately 80% when either LCU was used. Conclusions: The total amount of light transmitted through the five bulk-fill RBCs was similar at the different thicknesses using either LCU. The polywave LCU used in this study did not enhance the polymerization of the tested bulk-fill RBCs when compared with the single-peak LCU.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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".