A Simple Model for Gas-Phase Synthesis of Nickel Nanoparticles
Bibliographic record
Abstract
Gas-phase synthesis of nickel (Ni) nanoparticles by thermal decomposition of nickel tetracarbonyl, Ni(CO) 4, is simulated accounting for nucleation, surface growth, coagulation, and sintering. By detailed analysis of phenomenological expressions for sintering, it is shown that surface diffusion (SD) is the dominant sintering mechanism for Ni nanoparticles at low temperatures ( T < 700 K) and early stages of sintering, but grain boundary diffusion (GBD) dominates as sintering progresses and at higher temperatures. This is consistent with molecular dynamics simulations of noble metal nanoparticle sintering. Using the average of the above SD and GBD characteristic sintering times for Ni as well as a monodisperse population balance model (MPBM) that accounts for agglomerate morphology, polydispersity, and evolving structure with scaling laws from mesoscale simulations, Ni agglomerate sintering is benchmarked with measurements of agglomerate mobility and primary particle diameters. The MPBM predictions are in good agreement with the measured concentration and sizes of Ni nanoparticles by thermal decomposition of Ni(CO) 4 in a hot wall flow reactor.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".