Tantalum Processing Development for Medical Applications Insights from Relationship of Thermal Processes and Mechanical Properties by LMM-based AM and MIM
Bibliographic record
Abstract
The resurgence of interest in tantalum (Ta) within the medical industry is fueled by its refractory nature and exceptional X-ray reflection properties. Despite its commendable malleability, the machining challenges of Ta necessitate the development of powder metallurgy production techniques. While Ta powder metallurgy has found application in condenser production, the deliberate retention of an oxide layer is mandated. In contrast to condenser applications, medical applications demand superior mechanical properties and the impact of oxygen, hydrogen, and nitrogen contamination on Ta is crucial. This research focused on understanding the relationship between the thermal process and mechanical properties, utilising specimens produced through metal injection moulding and lithography-based additive metal manufacturing. The investigation included traditional solvent or thermal debinding, along with an exploration of superheated steam debinding. The findings contribute valuable insights into optimising the thermal processes for Ta in medical applications.
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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) | 0.001 | 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".