Molecular Simulations of Low-Shrinkage Dental Resins Containing Methacryl-Based Polyhedral Oligomeric Silsesquioxane (POSS)
Bibliographic record
Abstract
Nanocomposites of methacrylate-based polyhedral oligomeric silsesquioxane (POSS) are used as resins in dentistry to fill dental cavities. In this article, molecular dynamics simulations (MDS) are used to study and understand the interactions of monofunctional and multifunctional methacrylate groups on hybrid resins containing POSS additives for dental applications. These interactions are further related to the structural properties of the nanocomposites, which in turn affect their macro-properties that are important, especially when used for specific uses such as dental resins. For monofunctional methacrylate, nanocomposite of methacryl isobutyl POSS (MIPOSS) and for multifunctional methacrylate, methacryl POSS (MAPOSS) are used in this study. Molecular dynamic simulations (MDS) are performed on both MIPOSS and MAPOSS systems by varying the amount of POSS. On a weight percent basis, 1%, 3%, 5%, and 10% POSS are added to the resin. Density calculations, stress-strain, and powder diffraction simulations are used to evaluate the macro-properties of these nanocomposites and compare them with the experimental findings reported in the literature. The observations from the simulation results when compared to the experimental results show that MDS can be efficiently used to design, analyze, and simulate new nanocomposites of POSS.
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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 | 0.001 |
| 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 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".