Synthesis of TiO<sub>2</sub>−PMMA Nanocomposite: Using Methacrylic Acid as a Coupling Agent
Bibliographic record
Abstract
Inorganic-polymer nanocomposites are of significant interest for emerging materials due to their improved properties and unique combination of properties. Methacrylic acid (MA), a functionalization agent that can chemically link TiO2 nanomaterials (n-TiO2) and polymer matrix, was used to modify the surface of n-TiO2 using a Ti-carboxylic coordination bond. Then, the double bond in MA was copolymerized with methyl methacrylate (MMA) to form a n-TiO2-PMMA nanocomposite. The resulting n-TiO2-PMMA nanocomposite materials were characterized by using thermal analysis, electron microscopy, and elemental analysis. The dynamic mechanical properties (Young's and shear modulus) were measured using an ultrasonic pulse technique. The electron microscopy results showed a good distribution of the nanofillers in the polymer matrix. The glass transition temperature, thermal degradation temperature, and dynamic elastic moduli of the nanocomposites were shown to increase with an increase in the weight percentage of nanofibers in the composite. The resulting nanocomposites exhibited improved elastic properties and have potential application in dental composites and bone cements.
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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".