Benefits of supercritical CO₂ debinding for titanium powder injection moulding?
Bibliographic record
Abstract
Supercritical CO₂ debinding has been described as a clean and environmentally friendly alternative to other debinding routes. The claims are that SC-CO₂ should prevent oxidation, lead to less defects and reduce the debinding time. This appears therefore as the process of choice for titanium MIM since this material is very sensitive to contamination by interstitial elements during the whole process which, in turn, affects the mechanical properties and integrity required for demanding sectors such as biomedical. In this paper, the potential benefits of using the SC-CO₂ technology for titanium MIM parts have been evaluated as a replacement for the conventional immersion in solvent process. The efficiency of the debinding processes (SC-CO₂ and hexane) as well as their effect on final properties of titanium MIM dental implants, and in particular on interstitials composition (C wt.%, O wt.% and N wt.%) and dimensional variations will be presented and discussed, as a function of the processing debinding parameters.
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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 | 0.000 | 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) | 0.002 | 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".