Control of thermal properties and hydrolytic degradation in poly(lactic acid) polymer stars through control of isospecificity of polymer arms
Bibliographic record
Abstract
Abstract The synthesis of a family of polymer stars with arms of varied tacticities is discussed. The effect of polymer tacticity on the physical properties of these polymer stars is dramatic. Dipentaerythritol cores support six poly(lactic acid) arms. Lewis acidic tin and/or aluminum catalysts control the polymerization to afford polymer stars of variable tacticity. Analysis of these polymers by 1H NMR spectroscopy, thermogravimetric analysis, powder X‐ray diffraction, and differential scanning calorimetry reveals the effects of tacticity control on the physical properties of the polymer stars. Hydrolytic decomposition studies suggest that the degradation profile of a polymer star may also be tuned by stereochemical control. Differences between isotactic samples derived from rac‐lactide and L‐lactide are heightened by longer arms of 50 and 100 monomer units. Control of polymer isospecificity shows that a ∼70% isotacticity bias is necessary to induce crystallinity and alter the thermal and degradation properties of the material. Above 70% isotacticity, the degradation properties and thermal transitions can be further tuned across a relatively wide range. This technique allows for significant tunability to the physical properties of aliphatic polyester polymer stars. © 2012 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem, 2012
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".