Corrosion behavior of selective laser melted biomaterials in a physiological environment
Bibliographic record
Abstract
Medical applications are today the most important areas that use additively manufactured parts. The choose of the convenient biomaterial during implant design depends on several criteria such as biocompatibility, osteointegration and processing cost. The purpose of this work is to compare the corrosion behavior of AISI 316L austenitic stainless steel and Titanium TiAl6V4 orthopedic implants manufactured by selective laser melting. For each material the process parameters were varied to obtain comparable surface states mainly evaluated by microgeometric quality and porosities distribution. The electrochemical interaction between biomaterial and the physiological environment was simulated by corrosion tests performed in a Ringer type solution. From the obtained results it can be seen that selective laser melted Titanium TiAl6V4, despite its higher roughness, exhibits the highest corrosion resistance compared to AISI.316L stainless steel samples. In fact, for comparable porosities distribution density, enhanced corrosion properties, such as corrosion rate, pitting potential (Epp) and corrosion potential ( E corr ) were achieved for Titanium alloy.
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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".