Ice Nucleation Studies of Mineral Dust Particles with a New Continuous Flow Diffusion Chamber
Bibliographic record
Abstract
A new continuous flow diffusion chamber (CFDC) has been designed and constructed to study the ice nucleation efficiency of natural and anthropogenic aerosol particles over a range of temperatures and supersaturations. The CFDC system at Dalhousie University, Canada is based on the design of (CitationRogers et al. 1988, Citation1994) at Colorado State University, USA. A steady airflow (2.83 lpm) composed of sheath flows and an aerosol flow passes through the annular gap of the diffusion chamber. The walls of the chamber are ice-covered and are held at different temperatures. Aerosol particles are injected into the center of the gap near the location of maximum supersaturation. Particles greater than 5 μm in aerodynamic diameter are removed with impactors before entry to the chamber. Ice crystals are identified with an optical particle counter at the outlet of the chamber. In this article we report on the ice nucleation results of two mineral dust particles of potential atmospheric relevance, kaolinite and montmorillonite. Our results indicate that kaolinite and montmorillonite act as efficient ice nuclei in deposition/condensation nucleation mode. The onset relative humidity of both kaolinite and montmorillonite mineral dust particles were determined. The percentage of active ice nuclei is higher in montmorillonite compared to kaolinite at each temperature within the experimental conditions. The fraction of active ice nuclei increases with decreasing temperature and also with increasing relative humidity.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".