A parametric study on the processing parameters and properties of a porous poly(DL‐lactide‐<i>co</i>‐glycolide) acid 85/15 bioscaffolds
Bibliographic record
Abstract
Abstract This study presents a comprehensive parametric study on the effects of processing parameters on the poly(DL‐lactide‐co‐glycolide) acid (PLGA) 85/15 scaffold's physical properties. Porous PLGA 85/15 scaffolds were prepared using a gas foaming/salt leaching technique. The processing parameters under examination for the gas foaming/salt leaching method included: gas saturation pressure (SP), gas saturation time, and NaCl/polymer mass ratio (NaCl/PMR). The physical properties considered in this study were the scaffold density, the scaffold porosity, and the average pore size of the scaffold. Young's moduli in compression, as well as the pore density (PD) inside the scaffold, were also studied. The results demonstrated optimum correlations of processing parameters are required to produce a scaffold with a high level of interconnectivity. In general, all scaffolds yielded by this experiment exhibited a porosity more than 90%, a relative density ranging from 0.0534 to 0.149 g/cm3, a PD ranging from 1.51 × 106 to 6.72 × 106 pores/cm3, and a compressive modulus ranging from 0.07 to 0.84 MPa. It was determined that the NaCl/PMR was the parameter that had the most significant effect on the physical properties of the scaffold. The average pore size was affected slightly by the SP only, and it was observed that the pore size was equivalent to the size of the NaCl particles used to make the scaffold. POLYM. ENG. SCI., 2009. © 2009 Society of Plastics Engineers
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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 | 0.001 | 0.001 |
| 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".