Scratch Resistance and Impact Strength of Semi Interpenetrating Networked PMMA and PU with<i> In Situ</i> Produced Silica
Bibliographic record
Abstract
The scratch damage resistance and impact strength of PMMA sheets are necessary factors that have to be concerned by manufacturers. The aim of this work is to investigate the influences of silica (Si) from tetraethoxysilane on scratch damage resistance of the sheet surfaces for optical applications. The polymeric composites including PMMA, polyurethane (PU) and Si were produced via a bulk polymerization in a casting process. The technique creates semi-interpenetrating polymer networks (IPNs) between PMMA and PU. The percentage of IPNs and surface morphology of the composite sheets were observed. Furthermore, scratch resistance, impact strength, ultraviolet and thermal degradations of PMMA-PU-Si sheets were measured and compared with those of neat PMMA-PU sheets. The results revealed that the optimal Si amount (0.039 phr) provided 2B of the scratch resistance (2B of pencil range). This composite formula gave the highest impact values of 24.27 kJ/m2 for an Izod type and 24.94 kJ/m2 for a Charpy type. Composite sheets showed increases in ultraviolet and heat resistance by increasing the content of Si. However, the PMMA-PU-Si sheets were useable at temperature lower than 180 ⁰C.
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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".