Characterization of the viscoelastic properties of poly(ε‐caprolactone)–hydroxyapatite microcomposite and nanocomposite scaffolds
Bibliographic record
Abstract
Abstract In bone tissue engineering, the mechanical properties of the scaffolds need to be sufficiently high to prevent material failure when bearing loads. To strengthen the scaffold, various composites have been proposed in the literature, including poly(ε‐caprolactone) with hydroxyapatite (HA). In this study, the processing of this composite using the gas foaming/salt leaching technique is examined. The control of scaffold properties by varying the processing parameters was first investigated. Then, the change in properties, with a focus on the viscoelastic properties, from the varying morphology was examined. Although an increase in scaffold density and pore size increased the scaffold modulus, it did not significantly affect the viscoelastic properties. Furthermore, the addition of HA decreased the scaffold modulus and increased the loss factor of the composite scaffolds. The more viscoelastic behavior is believed to be due to the more open structure that was created. When tested in a water bath to better simulate the physiological environment, the mechanical properties decreased by up to 85%, and the scaffolds also behaved more viscoelastically. The comparison of the scaffold properties shows the differing behavior of the scaffolds in dry and wet conditions. Hence, the environment of testing should be more carefully considered when designing experiments. POLYM. ENG. SCI., 2012. © 2012 Society of Plastics Engineers
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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".