Metrological characterization of porosity graded β-Ti21S triply periodic minimal surface cellular structure manufactured by laser powder bed fusion
Bibliographic record
Abstract
The design of a functionally graded porous structure (FGPS) for use in prosthetic devices is crucial for meeting both mechanical and biological requirements. One of the most commonly used cellular structures in FGPS is the triply periodic minimal surface (TPMS) structure due to its ability to be defined by implicit equations, which allows for smooth transitions between layers. This study evaluates the feasibility of using a novel β-Ti21S alloy to fabricate TPMS-based FGPS. This beta titanium alloy exhibits low elastic modulus (53 GPa) and good mechanical properties in as-built condition. Two TPMS FGPSs with relative density gradients of 0.17, 0.34, 0.50, 0.66, and 0.83 and unit cell sizes of 2.5 mm and 4 mm were designed and fabricated using laser powder bed fusion (LPBF). The as-manufactured structures were analyzed using scanning electron microscopy (SEM) and X-ray micro-computed tomography (μ-CT), and the results were compared to the design. The analysis revealed that the pore size and ligament thickness were undersized by less than 5%. Compression tests showed that the stabilized elastic modulus was 4.1 GPa for the TPMS with a 2.5 mm unit cell size and 10.7 GPa for the TPMS with a 4 mm unit cell size. A finite element simulation was performed to predict the specimen's elastic properties, and a lumped model based on lattice homogenized properties was proposed and its limitations were explored.
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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) | 0.000 | 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 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".