Effect of Recycled Tungsten Carbide on the Mechanical, Physical, and Tribological Performance of Copper-Based Composites
Bibliographic record
Abstract
This study comprehensively explores the effect of reinforcing a copper matrix with recycled tungsten carbide (RWC) powder to enhance its mechanical and tribological properties. The copper matrix was initially fortified with fixed proportions of 8 wt.% high-carbon ferrochromium (HC-FeCr), 20 wt. % iron (Fe), 10 wt.% graphite (C), and 2 wt.% molybdenum disulfides (MoS2) via high-energy mechanical milling. Recycled tungsten carbide (RWC) powder in varying concentrations (1-5 wt.%) was subsequently blended with the matrix for 6 hours at 200 rpm. Graphite, MoS2, and RWC surface modification was achieved through nano-copper coating via electroless chemical deposition. The composite powders were consolidated using a hot-press technique at 1010°C under 15 MPa for 15 minutes. The study's comprehensive characterization included density, XRD, SEM analysis, hardness, wear, friction coefficient assessments, and electrical and thermal conductivity measurements. The results revealed a 25% increase in hardness and a 12% reduction in wear rate with the addition of WC, alongside a gradual decline in the friction coefficient. However, the electrical and thermal conductivities diminished as RWC content increased. The Abbott-firestone curves show enhancement in the exploitation zone from (88 – 96%) at load 0.4 MPa and from (84-93%) at load 0.7 MPa.
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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".