Nucleation with Simultaneous Chemical Reaction in the Vapor-Phase Synthesis of AlN Ultrafine Powders
Bibliographic record
Abstract
Using the classical (one-component) homogeneous nucleation theory approach of a constrained equilibrium distribution of subcritical particles, a nucleation equation that considers the effect of heterogeneous reaction is derived for the AlN system.In the absence of more detailed information about the aluminum nitride (AlN) reaction kinetics, a simpli ed surface reaction model is formulated.Clusters, which can be formed by AlN and pure Al, are assumed to grow from the condensation of Al vapor followed by surface reaction between condensed Al and absorbed NH 3 .The composition of any subcritical particle is assumed to be determined by the rates at which Al and AlN species are added to their surface and thus made entirely dependent upon local gas concentrations.This assumption resulted in important simpli cations that allowed this development to be cast in a form resembling the one used by the classical theory for one-species nucleation.An analysis intended to evaluate the dependence of this nucleation equation on temperature, concentration of reacting species, and degree of aluminum supersaturation is presented.Considerable changes of the nucleation rate were observed between low and high concentration ratio of reacting species.These changes are directly related to the changes of the surface energy and bulk free energy terms determined as a function of the free-Al content in a nucleus.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".