Partial and Complete Wetting in Ultralow Interfacial Tension Multiphase Blends with Polylactide
Bibliographic record
Abstract
The control of phase structuring in multiphase blends of polylactide (PLA) with other polymers is a viable approach to promote its broader implementation. In this article, ternary and quaternary blends of PLA with poly(butylene succinate) (PBS), poly(butylene adipate-co-terephthalate) (PBAT), and poly(3-hydroxybutyrate-co-hydroxyvalerate) (PHBV) are prepared by melt blending. The interfacial tensions between components are measured using three different techniques, and a Fourier transform infrared imaging technique is developed for the purpose of unambiguous phase identification. A tricontinuous complete wetting behavior is observed for the ternary 33PLA/33PBS/33PBAT blend before and after quiescent annealing, which correlates closely with spreading theory analysis. In the quaternary PLA/PBS/PBAT/PHBV blend, a concentration-dependent wetting behavior is found. At 10 vol % PBAT, self-assembled partially wet droplets of PBAT are observed at the interface of PBS and PHBV, and they remain stable after quiescent annealing as predicted by spreading theory. In contrast, at 25 vol % PBAT, a quadruple continuous system is observed after mixing, which only transforms to partially wet PBAT droplets after subsequent annealing. These results clearly indicate the potential of composition control during the mixing of multiphase systems to result in a complete change of spreading behavior.
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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".