The effect of pore size on the stiffness of composite scaffold
Bibliographic record
Abstract
Abstract: Low mechanical stiffness is often an issue in the design of implant scaffolds that are required to have moderate porosity. The purpose of our study is to determine the optimal pore size for a given porosity, so that the scaffold has maximum stiffness. The composite scaffold we studied consists of hydroxyapatite (HA) and polylactic acid (PLA). The microstructure-free finite element modeling (MF-FEM), a finite element approach recently developed for the modeling of composite materials, was adopted for this study. We first compared MF-FEM predictions with conventional formulas of stiffness-porosity relation for the purpose of validation. Then, MF-FEM was used to investigate the effect of pore size on scaffold stiffness in single-phase scaffold, because none of the conventional formulas can predict the effective stiffness of two-phase porous composites. The results show that MF-FEM has excellent agreement with well-established analytical formulas, pore size roughly has a linear effect on both Young’s modulus and shear modulus of composite scaffold, i.e. larger pore size leads to higher stiffness.
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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 | 0.000 |
| 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 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".