The Mechanism of Heterogeneous Ice Nucleation by Fatty Alcohol Monolayers
Bibliographic record
Abstract
Organic ice nucleating substances (INSs) are thought to play an essential role in cloud formation and, hence, precipitation and climate. Organic INSs are an important but poorly understood class of INSs in the atmosphere. To study organic INSs with exposed hydroxylated surfaces, researchers have previously used fatty alcohol monolayers as model systems. For alcohol monolayers, ice nucleation temperatures increase with increasing alkyl chain length and show a high–low oscillation following the number (odd–even) of carbon atoms in the alkyl chains. We employ atomistic models, together with molecular dynamics simulations, to investigate ice nucleation by C 20 H 41 OH, C 30 H 61 OH, and C 31 H 63 OH monolayers. As expected, we find that ice nucleation by alcohol monolayers depends on the lattice match to ice, and a poorer lattice match can at least partially account for the reduced ice nucleation ability of C 20 H 41 OH monolayers compared to monolayers of the longer chain alcohols. More interestingly, our simulations identify a limited range of alcohol configurations that readily nucleate ice via the basal plane. For configurations outside this range, ice nucleation did not occur on the time scale of our simulations (i.e., 5000 ns). The configurational feature that crucially influences ice nucleation is the angle between the alcohol C–O bond and the interfacial plane. C–O bonds directed sharply toward or away from the water phase strongly inhibit ice nucleation. In contrast, ice nucleation is easily observed for a relatively narrow band of C–O bond orientations centered about the surface plane. For comparable surface configurations, the ice nucleating abilities of C 30 H 61 OH and C 31 H 63 OH monolayers are practically identical, but the existence of a narrow band of ice-compatible surface configurations can perhaps explain why odd-chain alcohol monolayers are better INSs than even-chain alcohol monolayers. Earlier simulations have shown that for alcohols differing by a single carbon atom, the odd-chain monolayer is less rigid than the even-chain monolayer. This suggests the possibility that for odd-chain alcohol monolayers, the orientation of the C–O bonds can more easily adjust into the ice-compatible range than their even-chain counterparts, accounting for their enhanced ice nucleating ability.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".