Infiltration processing of metal matrix composites using coated ceramic particulates
Bibliographic record
Abstract
A new process was developed to fabricate particulate metal matrix composites (MMCs). The process involves three steps: (1) modifying the particulate surface by metal coating, (2) forming a particulate porous compact; and (3) introducing metal into the channel network by vacuum infiltration. MMCs with different reinforcements, volume fractions, and sizes can be produced by this technique. Powders of alumina and silicon carbide were successfully coated with nickel and copper in preparation for infiltration with molten aluminum. Electroless Ni and Cu deposition was used since it enhances the wettability of the reinforcements for composite fabrication. While Cu deposits were polycrystalline, traces of phosphorous co-deposited from the electroless bath gave an amorphous Ni-P coating. The effect of metal coating on wetting behavior was evaluated at 800ºC on plain and metal-coated ceramic plates using a sessile drop technique. The metallic films eliminated the non-wetting behavior of the uncoated ceramics, leading to equilibrium contact angles in the order of 12º and below 58º for Ni and Cu coated ceramics, respectively. The spreading data indicated that local diffusion at the triple junction was the governing mechanism of the wetting process. Precipitation of intermetallic phases in the drop/ceramic interface delayed the formation of Al4C3. Infiltration with molten Al showed that the coated-particulates are suitable as reinforcing materials for fabricating MMCs, giving porosity-free components with a homogeneously distributed reinforcing phase. The coating promoted easy metal flow through the preform, compared to the non-infiltration behavior of the uncoated counterparts. Liquid state diffusion kinetics due to temperature dependent viscosity forces controlled the infiltration process. Microstructural analysis indicated the formation of intermetallic phases such as CuAl 2, in the case of Cu coating, and Ni2Al3 and NiAl 3 when Ni-coated powders were infiltrated. The overall Ni and Cu content increased from bottom to top of the samples due to dissolution of the metal film by the stream of liquid Al during infiltration. The strengths of the Al/Ni-SiC composites, measured by four-point bending, were 205 and 225 MPa for samples reinforced with 78 mum and 49 mum Ni-SiC, respectively. The mode of fracture was mainly controlled by SiC particle fracture.
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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".