Study Mechanical Properties for Polymer Composite Reinforced by Carbon Fibers and Copper Oxide Particles (CuO) Used in Make Prosthetic Limb
Bibliographic record
Abstract
In the quest to advance the material science underpinning prosthetic limb technology, this study explores the mechanical fortification of unsaturated polyester-based composites via the incorporation of unidirectional carbon fibers and micro-scale copper oxide (CuO) particulates.The mechanical attributes scrutinized include hardness, impact resistance, compressive and tensile strengths, and flexural robustness.The fabrication process entailed manual molding techniques to yield homogenized composite samples.It was observed that the integration of carbon fibers markedly augmented the composite's mechanical performance.Specifically, the carbon fiber-reinforced specimens demonstrated a maximum hardness of 85.4 N/mm 2 , an impact strength cresting at 6.27 KJ/m 2 , a compressive strength peaking at 24.5 MPa, a tensile strength apex of 20 MPa, and a superior bending strength of 39.09 MPa.Conversely, the incorporation of CuO particles yielded mixed outcomes.While there was a notable increment in hardness strength to 83.5 N/mm 2 and a modest rise in impact strength to 0.70 KJ/m 2 , a diminution was witnessed in compressive, tensile, and bending strengths, which dwindled to 8.33 MPa, 5.07 MPa, and 9.54 MPa, respectively.The findings underscore the efficacy of carbon fiber reinforcements in significantly bolstering the structural integrity of composite materials destined for prosthetic applications, outperforming the enhancements provided by CuO particles.This research underscores the potential for carbon fiber to act as a pivotal reinforcement agent in the development of highperformance prosthetic limbs, providing a robust framework for future material innovation.The study's implications extend to the design of lightweight, durable prosthetic components that can endure the multifaceted demands placed on them during use.Future investigations could pivot towards optimizing fiber-matrix interfaces and exploring hybrid reinforcement strategies to further push the boundaries of prosthetic material capabilities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".