Evaluation of Selective Laser Melted Ti6Al4V/ST316L Composite and Selective Laser Sintered Polyamide 12 Implants for Orthopedic Applications: Finite Element Analysis, Physical and Mechanical Characterization, in Vitro and in Vivo Biocompatibility
Bibliographic record
Abstract
This study examined the compatibility of an orthopedic implant made from polyamide 12 sintering, coupled with a composite made from Ti6Al4V/ST316L laser fusion, both in vitro and in vivo.SLM 3D printing was used to construct the composite implant of Ti6Al4V/ST316L, while SLS 3D printing was used for the polyamide 12 implant.SEM analysis, X-ray diffraction analysis, and energy dispersive spectroscopy (EDS) were used to characterize the fabricated implants.Mechanical properties of the implants were evaluated using a universal testing machine.Using finite element modeling, von Mises stresses within implants and human bones could be examined.It involved increasing the cell count and implanting MC3T3-E1 preosteoclasts on implants for a week.Biocompatibility was determined using an AlamarBlue® fluorescence test.After six weeks of implantation, rabbit femurs were stained with Hematoxylin and Eosin to determine in vivo biocompatibility of the implant.Based on the findings, both the polyamide 12 implant and the Ti6Al4V/ST316L composite SLM-3D printed by SLS-3D printing were biocompatible.Finite element analysis revealed that the maximum Von Misses stress was within acceptable limits.
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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".