SYNTHESIS AND CHARACTERIZATION OF SIDE CHAIN LIQUID CRYSTALLINE POLYACRYLATES AND THEIR EFFECT ON THE CRYSTALLIZATION OF POLYETHYLENE USING AS A NUCLEATING AGENT
Bibliographic record
Abstract
The present work was focused on investigating the potential of using side chain liquid crystalline polymers(SCLCP) as nucleating agents for semicrystalline polymers.For this purpose,two vinyl monomers with liquid crystalline properties were designed and prepared.By means of homopolymerization two side chain liquid crystalline polymers having different architectures were synthesized.The monomers and the polymers obtained were characterized by elemental analysis,FTIR and()~1H-NMR measurements.DSC and HS-POM were employed to study the phase-transition temperatures and mesophase textures for the polymers.The thermal stability of the polymers was measured by TGA.The results showed that the polymers were all thermotropic side chain liquid crystalline polymers with wide liquid crystalline phase temperature range and excellent thermal stability.The effect of one of the SCLCPs used as a nucleating agent in the crystallization of high density polyethylene(HDPE) was investigated by DSC and HS-POM.The results indicated that SCLCP could effectively increase the crystallization temperature,crystallization speed and the crystallinity for HDPE.It was found that the synthesized SCLCP could be an effective nucleating agent for HDPE.
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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".