Fabrication of porous calcium polyphosphate implants by solid freeform fabrication: A study of processing parameters andin vitro degradation characteristics
Bibliographic record
Abstract
Solid freeform fabrication (SFF) involves the creation of a solid 3-D object of desired shape by successively adding raw materials in particles or layers. Its use in fabricating surgical implants is being explored. The objective of this study was to determine the feasibility of using SFF to build porous parts of calcium polyphosphate (CPP), a linear condensed phosphate that has been suggested as a material for forming bioresorbable skeletal replacement implants. CPP powders (<25 microm in particle size) were added to an UV curable monomer (SOMOS 6110) at a solids loading of 25 vol %, with the addition of a commercial dispersant to prevent particle agglomeration and settling. Viscosity and cure depth measurements were performed to insure that CPP suspension met the requirements deemed necessary for use in SFF. The CPP suspension was bulk cured and sintered in molds in order to assess binder removal and sintering parameters. Using a three-point bend test, the ultimate bending strength and energy-to-fracture of sintered CPP samples simulating parts to be formed by this strategy were characterized. In vitro degradation studies using 0.1M of tris-buffered solution were performed to assess the effect of aging on mechanical properties of the samples as a function of the processing route and resulting structures. The polymer binder successfully was removed from the cured ceramic suspension by developing a procedure that combined slow heating rates with low temperature dwells. Sintering CPP at 585 degrees C for 1 h produced amorphous material samples with average porosity of 27.7 +/- 2.0%. Sintering CPP at 600 degrees C for 1 h produced a crystalline material with samples having an average porosity of 22.9 +/- 1.3%. Crystalline CPP was found to exhibit superior bend strength and toughness compared with amorphous CPP. Both samples experienced a decline in mechanical properties during in vitro degradation; however, the effects were more pronounced with the amorphous CPP samples. Amorphous CPP was found to degrade four times faster than crystalline CPP, as shown by high levels of phosphate present in the degradation solution and a noticeable increase in the porosity of the samples. Crystalline CPP was more resistant to attack as dissolution was limited to surface features of the sintered particles.
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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 | 0.001 |
| 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) | 0.000 | 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 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".