Metallurgical parameters controlling matrix/B<sub>4</sub>C particulate interaction in aluminium–boron carbide metal matrix composites
Bibliographic record
Abstract
Two base matrixes of Al–15 vol.-%B4C and 6063–15 vol.-%B4C metal matrix composites (MMCs) were produced using a powder injection technique. Alloying element additions of 0·5 wt-%Ti, 0·35 wt-%Zr and 0·35 wt-%Sc were added to the base matrixes to produce various alloy compositions of Al–15 vol.-%B4C and 6063–15 vol.-%B4C MMCs. The production route of the MMCs used in the current project was the molten metal processing technique using powder injection. For the purpose of investigating the reinforcement (B4C)/matrix (Al) interaction, five alloy compositions of pure Al–15 vol.-%B4C and 6063–15 vol.-%B4C with various additions of Ti, Zr and Sc were produced. A metallic L shaped mould was used for casting the aluminium MMCs. Reinforcement/matrix interface interactions in the produced composites were investigated, using a field emission gun scanning electron microscope and energy dispersive X-ray techniques, as a function of alloying element addition.The powder injection technique used in the present work was proven to be very effective in producing Al–B4C MMCs and 6063–B4C MMCs with B4C concentrations of 15 vol.-%. The produced MMCs show a uniform distribution of the reinforcement of B4C in the aluminium matrix. In the alloys free from Ti, Zr and Sc, the B4C particles decompose into other products such as AlB2, Al4C3, Al3BC and/or Al3B48C2 due to the reaction between the reinforcement and the aluminium matrix. In alloys containing Zr and Ti, the B4C particles react with these elements forming Zr and Ti rich phases, which accumulate in layers that encircle the reinforcement particles and act as protective layers that protect the B4C particles from decomposition by preventing their reaction with the aluminium matrix. Sc displays the same positive effect as Ti and Zr in forming protective layers of Sc rich phases surrounding the B4C particles and protects them from decomposition. Scandium, however, is not recommended as an alloying element in this case due to its high cost, and as its effect could be attained using cheaper elements such as Ti and Zr.
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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".