Laser Induced Fluorescence Spectroscopy of Tetracene with Large Ar, Ne, and H<sub>2</sub> Clusters in Superfluid He Nanodroplets
Bibliographic record
Abstract
Clusters of tetracene molecules with different numbers of attached (Ar)(N), (Ne)(N) and (H(2))(N) particles (N = 1-2000) are assembled inside superfluid He nanodroplets and studied via laser-induced fluorescence. The frequency shift of the fluorescence spectrum of the tetracene molecules is studied as a function of cluster size and pickup order of tetracene and cluster species. For (Ar)(N) and (Ne)(N) clusters, our results indicate that the tetracene molecules reside inside the clusters when tetracene is captured by the He nanodroplet before the cluster species; conversely, the tetracene molecules stay on the surface of the clusters when tetracene is captured after the cluster species. In the case of (H(2))(N) clusters, however, tetracene molecules reside inside the (H(2))(N) clusters irrespective of the pickup order. We conclude that (Ar)(N) and (Ne)(N) clusters are rigid at T = 0.38 K, while (H(2))(N) clusters of up to N = 2000 remain fluxional at the same temperature. The results may also indicate the occurrence of heterogeneous nucleation of the (H(2))(N) clusters, which is induced by the interaction with tetracene chromophore molecules.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".