Effects of tungsten carbide and cobalt particles on corrosion and wear behaviour of copper matrix composite
Bibliographic record
Abstract
Copper matrix composites reinforced with various contents (10–20 wt-%) and sizes (1–9 μm) of tungsten carbide particles (WCp) and cobalt particles (Cop, 1·5 μm and 5 wt-%) were fabricated by hot pressing. The effects of WCp and Cop on the wear and corrosion properties of the copper composites were evaluated. Dry wear testing was conducted in ambient conditions and wear corrosion testing was carried out in 3·5 wt-%NaCl solution (pH 6·7). The results show that the hardness, wear resistance and static corrosion weight loss of Cu/WCp composites increase with a decrease of WCp size or with an increase of WCp content. Also, the corrosion current density I corr increases with a decrease of WCp size or with an increase of WCp content, and the corrosion potential E corr exhibits no specific trend with varying WCp content and size. The wear corrosion rate increases with an increase in WCp content, yet shows no direct correlation with WCp size. On the other hand, Cu/WCp/Cop composites exhibit better wear resistance in both dry wear and corrosive wear conditions. The Cu/WCp/Cop composites show a much lower E corr and significantly more passivity than Cu/WCp composites in polarisation tests. The Cu/WCp/Cop composites exhibit excellent wear corrosion resistance, especially in the passive potential (Ep) state.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".