Ice formation via deposition nucleation on mineral dust and organics: dependence of onset relative humidity on total particulate surface area
Bibliographic record
Abstract
We present ice nucleation results for Arizona test dust, kaolinite, montmorillonite, silica, silica coated with a hydrophobic octyl chain, oxalic acid dihydrate, Gascoyne leonardite (a humic material), and Aldrich humic acid (sodium salt). The focus was on deposition mode nucleation below water saturation at 233 K. Particles were deposited onto a hydrophobic cold stage by atomization of a slurry/solution and exposed to a constant partial pressure of water vapor. By lowering the temperature of the stage, the relative humidity with respect to ice (RH i ) was gradually increased until ice nucleation was observed using digital photography. Different numbers of particles were deposited onto the cold stage by varying the atomization solution concentration and deposition time. For the same total particulate surface area, mineral dust particles nucleated ice at lower supersaturations than all other materials. The most hydrophobic materials, i.e. Gascoyne leonardite and octyl silica, were the least active. For our limit of detection of one ice crystal, the ice onset RH i values were dependent on the total surface area of the particulates, indicating that no unique threshold RH i for ice nucleation prevails.
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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".