Carbonized Bamboo Culm-Based Composite Materials: Mechanical and Frictional Performance for Brake Pad Applications
Bibliographic record
Abstract
This study examines the development and application of composite materials based on dry and carbonized bamboo culm particles for friction material applications, particularly as a potential replacement for asbestos-based materials.Due to the environmental and health risks associated with asbestos, sustainable, high-performance alternatives are essential.Carbonized bamboo particles offer excellent thermal stability, while bamboo culm enhances strength.The development involved selecting bamboo culm composites, carbonizing, drying, and integrating them with other materials to achieve the desired friction properties.The composite materials were developed in a laboratory setting, and mechanical and thermal experiments were used to characterize the materials' properties.A systematic experimental design approach, including the Taguchi method, was employed to optimize the formulation and processing parameters.Test results show that the developed composite material has high mechanical strength, with an average tensile strength of 10.31 ± 0.21 MPa, a modulus of elasticity of 80.07 ± 1.60 MPa, an impact strength of 0.6912 J/mm, and a Vickers hardness of 107 HV.Thermal stability was further confirmed during testing, with a maximum temperature of 950℃ at a heating rate of 10℃/min.The developed composite material also performed well in friction material tests, with a friction coefficient of 0.378 and a wear rate of 0.15 mm³ /Nm.Thermogravimetric analysis showed that optimized carbonized bamboo brake pads had lower temperature degradation than commercial ones.Results indicated that dry and carbonized bamboo culm composite materials are effective for friction applications, performing comparably to commercial brake pads.
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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".