Growth Mechanisms for SiC–AlN Solid Solution Crystals Prepared by Combustion Synthesis
Bibliographic record
Abstract
AlN–SiC solid solution particles with a variety of morphologies including faceted polyhedrons with or without ledges; hexagonal platelets; hexagonal columns with a hexagonal plate or a pyramidal cap; and interpenetrating cones, have been found in the combustion products of a mixture of Al, Si, and carbon black under a nitrogen pressure of 10 MPa. Combustion temperature (the growth temperature of crystals) is the most important factor controlling the morphology of crystals formed in the combustion product. When temperatures are close to the melting point of the solid solutions, a small driving force for nucleation and long distances of surface migration make nucleation on the basal plane difficult, and thus the solid solution particles tend to grow as platelets. Supersaturation is the second key factor influencing crystal growth. At relatively low temperatures, a low supersaturation at the large pores renders nucleation difficult and the solid solution particles tend to grow as platelets. At relatively low temperatures and high supersaturation, a relatively high driving force for nucleation and short mean distances of surface migration promote the growth of AlN–SiC solid solutions as polyhedrons. The formation of the ledges on the polyhedral particles is attributed to the differences in the evaporation rates and the deposition rates between Al and Si. At relatively low temperatures and an intermediate supersaturation, the solid solution particles grow as prismatic columns. The formation of the prismatic columns with a hexagonal plate, or a pyramidal cap, is attributed to a sudden change of temperature during combustion. A possible growth mechanism for the AlN–SiC solid solution cones is proposed.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".