Poly(d,l-Lactic acid) Composite Foams Containing Phosphate Glass Particles Produced via Solid-State Foaming Using CO2 for Bone Tissue Engineering Applications
Bibliographic record
Abstract
mol.%, was incorporated into biodegradable poly(d,l-lactic acid) (PDLLA) at 5, 10, 20, and 30 vol.%. The composites were fabricated by melt compounding (extrusion) and compression molding, and converted into porous structures through solid-state foaming (SSF) using high-pressure gaseous carbon dioxide. The morphological and mechanical properties of neat PDLLA and composites in both nonporous and porous states were examined. Scanning electron microscopy micrographs showed that the PGPs were well dispersed throughout the matrices. The highly porous composite systems exhibited improved compressive strength and Young's modulus (up to >2-fold) and well-interconnected macropores (up to ~78% open pores at 30 vol.% PGP) compared to those of the neat PDLLA foam. The pore size of the composite foams decreased with increasing PGPs content from an average of 920 µm for neat PDLLA foam to 190 µm for PDLLA-30PGP. Furthermore, the experimental data was in line with the Gibson and Ashby model, and effective microstructural changes were confirmed to occur upon 30 vol.% PGP incorporation. Interestingly, the SSF technique allowed for a high incorporation of bioactive particles (up to 30 vol.%-equivalent to ~46 wt.%) while maintaining the morphological and mechanical criteria required for BTE scaffolds. Based on the results, the SSF technique can offer more advantages and flexibility for designing composite foams with tunable characteristics compared to other methods used for the fabrication of BTE scaffolds.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".