Synthesis and characterization of polyimide/polyhedral oligomeric silsesquioxane nanocomposites containing quinolyl moiety
Bibliographic record
Abstract
Abstract A series of functional polyhedral oligomeric silsesquioxane (POSS)/polyimide (PI) nanocomposites were prepared using a two‐step approach. First, octa(aminophenyl)silsesquioxane (OAPS) was mixed with poly(amic acid) (PAA) prepared by reacting bis(4‐amino‐3,5‐dimethylphenyl)‐3‐quinolylmethane and 3,3′,4,4′‐benzophenonetetracarboxylic dianhydride. Second, the resulting solution was subjected to thermal imidization. The well‐defined ‘hard particles’ (POSS) and the strong covalent bonds in the amide linkage between the carbon atom of the carboxyl side group in PAA and the nitrogen atom of the amino group in POSS lead to a significant improvement in the thermal and mechanical properties. Homogeneous dispersion of POSS cages in the PI is evident from scanning electron microscopy, which further confirms that the POSS molecule becomes an integral part of the organic‐inorganic inter‐crosslinked network system. Differential scanning calorimetry and dynamic mechanical analysis show that the glass transition temperatures of the POSS‐containing nanocomposites are higher than that of the corresponding neat PI system, owing to the significant increase of the crosslinking density in the PI/POSS nanocomposites. Increasing the concentration of OAPS in the PI networks decreases the dielectric constant. Pure PI and PI/POSS systems have good antimicrobial activity. Copyright © 2011 Society of Chemical Industry
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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".