Elastomeric biodegradable polyurethane blends for soft tissue applications
Bibliographic record
Abstract
Four biodegradable polyurethane blends were made from segmented polyurethanes that contain amino acid-based chain extender and diisocyanate groups. The soft segments of these parent polyurethanes were either polyethylene oxide (PEO) or polycaprolactone (PCL) diols. The blends were developed to investigate the effect of varying soft segment compositions on the overall morphological, mechanical, and degradative properties of the materials, with a view to producing a family of materials with a wide range of properties. The highly hydrophilic PEO material was incorporated to increase the blend's susceptibility to degradation, while the PCL polyurethane was selected to provide higher moduli and percent elongations (strains) than the PEO parent materials can achieve. All four blends were determined to be semi-crystalline, elastomeric materials that possess similarly shaped stress-strain curves to that of the PCL-based parent polyurethane. As the percent composition of PEO polyurethane within the blend increased, the material became weaker and less extensible. The blends demonstrated rapid initial degradation in buffer followed by significantly slower, prolonged degradation, likely corresponding to an initial loss of primarily PEO-containing polymer, followed by the slower degradation of the PCL polyurethane. All four blends were successfully formed into three-dimensional porous scaffolds utilizing solvent casting/particulate leaching methods. Since these new blends possess a range of mechanical and degradation properties and can be shaped into three-dimensional objects, these materials may hold potential for use in soft tissue engineering scaffold applications.
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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 | 0.000 |
| 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".