Water sorption of CH3- and CF3-Bis-GMA based resins with additives
Bibliographic record
Abstract
OBJECTIVES: To evaluate the effect of additives on the water sorption characteristics of Bis-GMA based copolymers and composites containing TEGDMA, CH3Bis-GMA or CF3Bis-GMA. MATERIAL AND METHODS: Fifteen experimental copolymers and corresponding composites were prepared combining Bis-GMA and TEGDMA, CH3Bis-GMA or CF3Bis-GMA, with aldehyde or diketone (24 and 32 mol%) totaling 30 groups. For composites, barium aluminosilicate glass and pyrogenic silica was added to comonomer mixtures. Photopolymerization was effected by 0.2 wt% each of camphorquinone and N,N-dimethyl-p-toluidine. Specimen densities in dry and water saturated conditions were obtained by Archimedes' method. Water sorption and desorption were evaluated in a desorption-sorption-desorption cycle. Water uptake (%WU), water desorption (%WD), equilibrium solubility (ES; µg/mm³), swelling (f) and volume increase (%V) were calculated using appropriate equations. RESULTS: All resins with additives had increased %WU and ES. TEGDMA-containing systems presented higher %WU, %WD, ES, f and %V values, followed by resins based on CH3Bis-GMA and CF3Bis-GMA. CONCLUSIONS: Aldehyde and diketone led to increases in the water sorption characteristics of experimental resins.
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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".