Synthesis and properties of bio-based polyesters from a 2,4-dihydroxyacetophenone derivative
Bibliographic record
Abstract
A novel diphenyl monomer, dimethyl 2,2'-(((ethane-1,2-diylbis(oxy))bis(4-acetyl-3,1-phenylene))bis(oxy))diacetate (EDPD), was synthesized from methyl 2-(4-acetyl-3-hydroxyphenoxy)acetate (MAHA), a 2,4-dihydroxyacetophenonederivative, and combined with 1,4-butanediol, 1,6-hexanediol, 1,4-cyclohexanedimethanol or p-phenylenedimethanolto afford a series of biodegradable polyesters via melt polymerization. The polyesters were characterized by Fourier transform infrared and proton nuclear magnetic resonance spectroscopy, gel permeation chromatography, differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). The weight-average molecular weight (Mw) of the polyesters varied from 3.2–4.4 × 104 g/mol, the glass transition temperature (Tg) from 52 to 80 °C, and the 5% decomposition temperature (Td,5%) was in the 334–362 °C range. All the samples exhibited high yield strength (53–68 MPa) and elongation at break (230–330%) values, comparable with poly(ethylene terephthalate) (PET), owing to their aromatic character. Degradability testing of the polyesters in soil yielded mass losses reaching up to 7% after 32 weeks. In ecotoxicity testing, earthworms had a survival rate of more than 80% after 14 d of incubation, indicating relatively low toxicity. Overall, the good thermal and mechanical properties, biodegradability and low ecotoxicity of the polyesters make them promising materials for packaging applications, in replacement for PET, thereby promoting carbon neutrality and sustainable development.
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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) | 0.000 | 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".