Ice nucleation by smectites: the role of the edges
Bibliographic record
Abstract
Abstract. Smectites, like other clay minerals, have been shown to promote ice nucleation in the immersion freezing mode and likely contribute to the population of ice-nucleating particles (INPs) in the atmosphere. Smectites are layered aluminosilicates, which form platelets that depending on composition might swell or even delaminate in water by intercalation of water molecules between their layers. They comprise among others montmorillonites, hectorites, beidellites, and nontronites. In this study, we investigate the ice nucleation (IN) activity of a variety of natural and synthetic smectite samples with different exchangeable cations. The montmorillonites STx-1b and SAz-1, the nontronite SWa-1, and the hectorite SHCa-1 are all rich in Ca2+ as the exchangeable cation; the bentonite MX-80 is rich in Na+ with a minor contribution of Ca2+, and the synthetic Laponite is a pure Na+ smectite. The bentonite SAu-1 is rich in Mg2+ with a minor contribution of Na+, and the synthetic interstratified mica-montmorillonite Barasym carries NH4+ as the exchangeable cation. In emulsion freezing experiments, all samples except Laponite exhibited one or two heterogeneous freezing peaks with onsets between 239 and 248 K and a quite large variation in IN activity yet without clear correlation with the exchangeable cation, with the type of smectite, or with mineralogical impurities in the samples. To further investigate the role of the exchangeable cation, we performed ion exchange experiments. Replacing NH4+ with Ca2+ in Barasym reduced its IN activity to that of other Ca-rich montmorillonites. In contrast, stepwise exchange of the native cations in STx-1b once with Y3+ and once with Cu2+ showed no influence on IN activity. However, aging of smectite suspensions in pure water up to several months revealed a decrease in IN activity with time, which we attribute to the delamination of smectites in aqueous suspensions, which may proceed over long timescales. The dependence of IN activity on platelet stacking and thickness can be explained if the hydroxylated chains forming at the edges are the location of ice nucleation in smectites, since the edges need to be thick enough to host a critical ice embryo. We hypothesize that at least three smectite layers need to be stacked together to host a critical ice embryo on clay mineral edges and that the larger the surface edge area is, the higher the freezing temperature. Comparison with reported platelet thicknesses of the investigated smectite samples suggests that the observed freezing temperatures are indeed limited by the surface area provided by the mostly very thin platelets. Specifically, Laponite, which did not show any IN activity, is known to delaminate into single layers of about 1 nm thickness, which would be too thin to host a critical ice embryo.
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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 | 0.000 | 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) | 0.000 | 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".