Designing Green Plasticizers: Linear Alkyl Diol Dibenzoate Plasticizers and a Thermally Reversible Plasticizer
Bibliographic record
Abstract
Several linear alkyl diol dibenzoate compounds, ranging from C3 to C6 in central diol length, were evaluated for their plasticizing effectiveness in blends with poly(vinyl chloride) (PVC). The results were compared to blends of PVC/di(2-ethylhexyl) phthalate (DEHP), the most commonly used commercial plasticizer. DEHP has come under scrutiny, due to its suspected endocrine-disrupting behaviour, and the proposed diol dibenzoates have previously been shown to have the potential to be green, safe candidates for DEHP replacement. The thermal and mechanical properties of PVC/dibenzoate blends were determined, and include glass transition temperature (Tg), the elongation at break, maximum stress, apparent moduli, torsional modulus, and surface hardness. The C3, C5, and C6 dibenzoates performed as well as or better than DEHP, with the exception of torsional modulus, further supporting their use as green plasticizers. For blends with 1,4-butanediol dibenzoate, differential scanning calorimetry and torsional temperature sweeps suggested that the compound partly crystallizes within PVC blends over the course of two days, thereby losing the ability to effectively plasticize PVC. However, upon heating to temperatures above 60 °C, effective plasticization was again observed. 1,4-Butanediol dibenzoate is thereby a reversible heat-activated plasticizer or processing aid with excellent plasticizer properties at mildly elevated temperatures.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".