Uptake and accommodation of water clusters by adamantane clusters in helium droplets: interplay between magic number clusters
Bibliographic record
Abstract
We report an experimental study of water clusters as guests in interactions with clusters of adamantane (Ad) as hosts that occur in doped helium droplets at extremely low temperatures. Separate experiments with pure water as dopant showed ready formation of a distribution of water clusters (H2O)mH+ that peaks at m = 11 and extends beyond m = 100 with local maxima at m = 4, 11, 21, 28 and 30 with (H2O)21H+ being the most anomalous and showing the greatest stability with respect to clusters immediately adjacent in water content. When adamantane is also added as a dopant, extensive hydration is seen in the formation of water/adamantane clusters, (H2O)mAdn+; magic number clusters (H2O)21Adn+ are seen for all the adamantane clusters. Other magic numbers for water clusters attached to adamantane, (H2O)mAdn+, are as for pristine protonated water, with m = 28 and m = 30. The icosahedral shell closure of pure adamantane at n = 13 and 19 appears to be preserved with (H2O)21 replacing one adamantane. (H2O)21Ad12+ and (H2O)21Ad18+ stand out in intensity and demonstrate the interplay of magic number water clusters with magic number adamantane clusters, observed perhaps for the first time in gas-phase cluster chemistry. There was no clear evidence for the formation of clathrate hydrates in which adamantane is trapped within structured water.
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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".