Obtenção de ligas à base de titânio-nióbio-zircônio processados com hidrogênio e metalurgia do pó para utilização como biomateriais
Bibliographic record
Abstract
Biomaterials for use in implants must be biocompatible, biofunctional and resistant to corrosion.Utilization of titanium and its alloys is continuously increasing due to their larger strength-weight ratio, superior biocompatibility e corrosion resistance, good mechanical properties and low elastic modulus when compared to other metallic biomaterials such as stainless steel and Co-Cr alloys.Using materials with low elastic modulus, close to bone values, is important to reduce stress shielding effect, which can cause implant loosening.Ti13Nb13Zr ternary alloy shows only elements considered biocompatible and has a lower elastic modulus than Co-Cr alloy, stainless steel and Ti6Al4V, and superior corrosion resistance.In this work TiNbZr alloy was prepared in different compositions, maintaining Ti content at 74%wt with Nb and Zr contents ranging amongst 6 and 20%wt, produced by powder metallurgy using different processing conditions and heat treatments.Characterization via SEM and X-Ray diffraction showed that the Nb increase didn't produce significant alterations on volume fraction of α and β phases in the material, and the increase in Zr content led to an increase in α phase amounts and formation of Widmanstätten patterns.Nb and Zr content increasing produced microstructural modifications, leading to an increase in elastic modulus and hardness values, as well as corrosion susceptibility variations, where higher Zr contents leaded to a surface with less corrosion resistance.Amongst compositions and for the designed processing method, Ti13Nb13Zr presented the most indicated mechanical and microstructural properties for utilization as biomaterials.
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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 | 0.001 |
| 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) | 0.003 | 0.001 |
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".