Effect of Cu addition on microstructure and corrosion behavior of Al–15Mg<sub>2</sub>Si composite
Bibliographic record
Abstract
Abstract The Cu effect on the microstructure and corrosion resistance of Al–15Mg 2 Si composites was studied. The results showed that Cu addition decreased the average size of primary Mg 2 Si (Mg 2 Si P ) particles, changed the hopper-like Mg 2 Si P particles to polyhedrals, and caused the formation of θ -Al 2 Cu and Q -Al 5 Mg 8 Si 6 Cu 2 compounds in the composite matrix. According to the image analysis results, increasing the Cu content from 0.01 to 5 wt% halved the average size of Mg 2 Si P particles, increased their fraction by about 40 %, and increased the composite porosity content. The electrochemical impedance spectroscopy showed that adding 5 wt% of Cu resulted in an increase of about 3.7 times in the corrosion resistance as compared to Al–15Mg 2 Si composite. The beneficial effects of Cu were also confirmed by the potentiodynamic polarization experiments. Cu addition seems to promote less intense general corrosion than the base alloy’s localized attack.
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".