Laboratory investigation of Martian water ice cloud formation using dust aerosol simulants
Bibliographic record
Abstract
The ice nucleation abilities of submicron aerosol particles of two Martian regolith analogs, the Mojave Mars simulant and Johnson Space Center Mars‐1, were investigated with the University of Toronto continuous flow diffusion chamber. The temperature range studied (> 200 K) is relevant to low‐altitude water ice cloud formation in the Martian atmosphere and the aerosol particles were suspended in air, in contrast to previous experiments. Both simulants were found to be active ice nuclei in the deposition nucleation mode between 223 K and 203 K. The Mojave Mars simulant particles were found to be better ice nuclei than the Johnson Space Center Mars‐1 particles requiring lower supersaturations to nucleate ice. It was observed that the critical supersaturation ( S crit ) to activate 1% of the particles increased with decreasing temperature in accord with previous low‐temperature studies, rising to a value of above 1.7 at 203 K. This corroborates literature results that there is a substantial barrier to ice nucleation at low temperatures, underlining the need for incorporating this effect in Martian cloud microphysical models. It was also found that S crit did not change when the size of the Mojave Mars simulant particles was increased from 240 to 400 nm. Comparison of the Martian simulants with other mineral dusts shows that the Johnson Space Center Mars‐1 analog behaves similarly to the well‐known terrestrial ice nuclei such as kaolinite and Arizona test dust particles, whereas the Mojave Mars simulant behaves closer to another clay, montmorillonite. The wettability parameter, m , was calculated to range from 0.955 to 0.959.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.002 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".