Mechanical properties and fluid permeability of gyroid and diamond lattice structures for intervertebral devices: functional requirements and comparative analysis
Bibliographic record
Abstract
Current intervertebral fusion devices present multiple complication risks such as a lack of fixation, device migration and subsidence. An emerging solution to these problems is the use of additively manufactured lattice structures that are mechanically compliant and permeable to fluids, thus promoting osseointegration and reducing complication risks. Strut-based diamond and sheet-based gyroid lattice configurations having a pore diameter of 750 µm and levels of porosity of 60, 70 and 80% are designed and manufactured from Ti-6Al-4V alloy using laser powder bed fusion. The resulting structures are CT–scanned, compression tested and subjected to fluid permeability evaluation. The stiffness of both structures (1.9–4.8 GPa) is comparable to that of bone, while their mechanical resistance (52–160 MPa) is greater than that of vertebrae (3–6 MPa), thus decreasing the risks of wither bone or implant failure. The fluid permeability (5–57 × 10−9 m2) and surface-to-volume ratios (~3) of both lattice structures are close to those of vertebrae. This study shows that both types of lattice structures can be produced to suit the application specifications within certain limits imposed by physical and equipment-related constraints, providing potential solutions for reducing the complication rate of spinal devices by offering a better fixation through osseointegration.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".