Ti–5Al–5Mo–5V–3Cr bone implants with dual-scale topography: a promising alternative to Ti–6Al–4V
Bibliographic record
Abstract
Modifications to the compositional, topographical and morphological aspects of bone implants can lead to improved osseointegration, thus increasing the success of bone implant procedures. This study investigates the creation of dual-scale topography on Ti-5Al-5Mo-5V-3Cr (Ti5553), an alloy not presently used in the biomedical field, and compares it to Ti-6Al-4V (Ti64), the most used Ti alloy for bone implants. Dual-scale surface topography was obtained by combining selective laser melting (SLM) and electrochemical anodization, which resulted in micro- and nanoscale surface features, respectively. Ti5553 and Ti64 samples were manufactured by SLM and showed comparable surface topography. Subsequent electrochemical anodization succeeded in forming titania nanotubes (TNTs) on both alloys, with larger nanotubes obtained with Ti5553 at all investigated anodization voltages. At an anodization voltage of 40 V, a minimum time of 20 min was necessary to have nanotube formation on the surface of either alloy, while only nanopores were evident for shorter times. Seeded Saos-2 cells showed ideal interactions with surface-modified structures, with filopodia extending to both surface microparticles characteristic of SLM and to the interior of TNTs. Attractiveness of Ti5553 lies in its lower elastic modulus (E = 72 GPa) compared to Ti64, which should mitigate stress-shielding phenomena in vivo. This, combined with the analogous results obtained in terms of dual-scale surface topography and cell-substrate interaction, could indicate Ti5553 as a promising alternative to the widely-employed Ti64 for bone implant device manufacturing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".