Comparing the Structural, Thermal, and Rheological Properties of Poly(<i>meso</i>-lactide) to Poly(<scp>l</scp>-lactide) and Poly(<i>rac</i>-lactide)
Bibliographic record
Abstract
The melt rheological behavior of two highly stereo irregular chain configurations of PLA is compared to stereo regular PLLA using small amplitude dynamic frequency response in parallel plate flow geometry. The degree of heterotactic bonds along the polymer backbone is related to changes in the critical molecular weight, entanglement molecular weight, plateau modulus, and characteristic ratio. The melt rheology of PMLA was further characterized for temperature and frequency response. The mole fraction of syndiotactic lactic acid monomer transitions was estimated to be 0.01, 0.22, and 0.79 for PLLA, PRLA, and PMLA respectively. The highly disrupted stereo configuration of PMLA led to a more flexible chain in the melt than PLLA, with PMLA C ∞ = 5.9 vs that of PLLA where C ∞ = 7.5. PRLA exhibited chain flexibility behavior between that of PMLA and PLLA, with C ∞ = 6.9. The greater chain flexibility of PMLA in the melt resulted in lower flow activation energy temperature dependence, lower zero shear viscosity for a given molecular weight, and lower frequency at the onset of shear thinning than PLLA. The critical molecular weight and entanglement molecular weight of PMLA were estimated to be 1.75× and 2.05× that of PLLA. Plateau moduli of PMLA and PRLA were estimated from the crossover frequency using models of Wu and Nobile–Cocchini to enable direct comparison to PLLA and calculation of entanglement characteristics, packing length, and characteristic ratio. Frequency dependences of the dynamic moduli and complex viscosity were modeled using generalized Maxwell, Bird–Carreau, and Havriliak–Negami models.
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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".