Numerical and Experimental Study of Bio-Composite Plates as Internal Fixation
Bibliographic record
Abstract
Bone plates are essential for bone fracture healing because they modify the biomechanical microenvironment at the fracture site to provide the necessary mechanical fixation for fracture fragments.This paper focuses on reducing the stress shielding effect that occurs due to a mismatch between cortical bone and metal plate.fabricating bio composites plates fixation by modeling of femur bone with ANSYS software program.However, Bio-composites that involve Ultra-high molecular weight polyethylene polymer (UHMW-PE) reinforced with nano Titanium dioxide particles n-TiO2 at different fractions (0, 1.5, 2.5, 3.5 and 4.5%) and 5% from carbon and Kevlar fibers were fabricated by hot pressing technique.We tested tensile, elastic modulus, and elongation percentages.The results of this study showed a value of tensile strength and elastic modulus improved with increasing weight fraction of nanoparticles and UHMWPE+4.5% n-TiO2 biocomposite were the best mechanical properties, were tensile strength and elastic modulus was (38.57± 1.9285 MPa, 1.15 ± 0.0575 GPa) respectively and elongation percentages reduced to 114.05 ±5.7025% compared with pure UHMWPE 176.68 ± 5.7025%.According to the current study's findings, it is possible to create bio-composites as fixation devices with improved performance by placing different fiber reinforcements.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".