Synthesis of High Performance Thiophene–Aromatic Polyesters from Bio-Sourced Organic Acids and Polysaccharide-Derived Diol: Characterization and Degradability Studies
Bibliographic record
Abstract
In this work, the feasibility of replacing petroleum-based poly(ethylene terephthalate) (PET) with fully bio-based copolyesters derived from dimethyl 2,5-thiophenedicarboxylate (DMTD), dimethyl 2,5-dimethoxyterephthalate (DMDMT), and polysaccharide-derived 1,6-hexanediol (HDO) was investigated. A systematic study of structure-property relationship revealed that the properties of these poly(thiophene–aromatic) copolyesters (PHS(20–90)) can be tailored by varying the ratio of diester monomers in the reaction, whereby an increase in DMTD content noticeably shortened the reaction time in the transesterification step due to its higher reactivity as compared with DMDMT. The copolyesters had weight-average molar masses (Mw) between 27,500 and 38,800 g/mol, and dispersity Đ of 2.0–2.5. The different polarity and stability of heterocyclic DMTD provided an efficient mean to tailor the crystallization ability of the copolyesters, which in turn affected the thermal and mechanical performance. The glass transition temperature (Tg) could be tuned from 70–100 °C, while the tensile strength was in a range of 23–80 MPa. The obtained results confirmed that the co-monomers were successfully inserted into the copolyester chains. As compared with commercial poly(ethylene terephthalate), the copolyesters displayed not only enhanced susceptibility to hydrolysis, but also appreciable biodegradability by lipases, with weight losses of up to 16% by weight after 28 weeks of incubation.
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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".