Structural Characterization and Mechanical Evaluation of Bioactive Glass 45S5 Foams Obtained by a Powder Technology Approach
Bibliographic record
Abstract
Bioactive glass 45S5 foams were produced using a powder technology process developed by The National Research Council Canada–Industrial Materials Institute. NRC – IMI 's proprietary process, combining powder technology and polymer foam technique, allows the production of materials having different structures and properties. It can be used to produce components into various forms, such as fully porous bodies or coatings on solid structures. During foaming, the foaming agent is decomposed and expands the binder‐bioactive glass suspension. Then, the binder is burnt out by heating the sample at 500°C and finally the bioactive glass particle network is sintered to consolidate the material. Foams sintered at various temperatures were characterized from a microstructural and mechanical point of view. The foam structure and properties are affected by the sintering temperature when it is varied between 950°C and 1025°C. Foams exhibited open porosity (64%–79%) and pore size (335–530 μm) optimal for bone ingrowth. In all cases, the glass crystallized during sintering and the material was mostly composed of Na 6 Ca 3 Si 6 O 18 and Na 2 Ca 4 ( PO 4 ) 2 SiO 4 phases. The mechanical strength increased from 1.7 to 5.5 MPa while the density of the material increased from 0.56 to 0.97 g/cm 3 .
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".