Dental Resin Composites Reinforced by Rough Core–Shell SiO<sub>2</sub> Nanoparticles with a Controllable Mesoporous Structure
Why this work is in the frame
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Bibliographic record
Abstract
A porous structure within filler particles may improve interfacial bonding between the resin matrix and fillers for the preparation of dental resin composites (DRCs). In this study, rough core–shell SiO2 (rSiO2) nanoparticles with controllable mesoporous structures were synthesized via an oil–water biphase reaction system and characterized by transmission electron microscopy (TEM), scanning electron microscopy (SEM), and N2 adsorption–desorption measurements. The influence of the mesoporous shell thickness of rSiO2 and mass ratio between rSiO2 and smooth SiO2 (sSiO2) on the physical and mechanical properties of DRCs was studied. The rSiO2 with a thin mesoporous shell could form a strong physical interlocking with the resin matrix, which improved the mechanical properties with the exception of flexural modulus. The mechanical properties were further optimized by mixing rSiO2 and sSiO2. The flexural strength and compressive strength of the DRC at a mass ratio of 5:5 increased by 24.3% and 16.8%, respectively, compared with the DRC filled with sSiO2 alone. There is no statistically significant difference in the flexural modulus between these two DRCs (p > 0.05). The DRCs in this study showed excellent biocompatibility on the human dental pulp cells (HDPCs) as demonstrated by the cytotoxicity tests. The use of rSiO2 provides a promising approach to develop strong, durable, and biocompatible DRCs.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it