Quantitative Determination of the Raman Enhancement of Ag<sub>30</sub>(CO)<sub>25</sub> and Ag<sub>50</sub>(CO)<sub>40</sub> Matrix Isolated in Solid Carbon Monoxide
Bibliographic record
Abstract
Size-selected Ag clusters in the range Ag 3 –Ag 50 were prepared by sputtering a silver substrate, mass-selecting Ag cation clusters using a Wien filter, neutralizing and matrix-isolating them at cryogenic temperatures in solid CO. The Raman spectra of the resulting silver-cluster carbonyls were recorded using excitation wavelengths in the range 457.9 to 514.5 nm. For Ag 30 and Ag 50, the “adsorbed” carbon monoxide (which we estimated to number ∼25 and ∼40, respectively) gave rise to broad Raman bands centered at ∼2110 cm –1 . Because both the metal cluster and the CO density were measured quantitatively, a good estimate was computed for the increase in the Raman scattering cross-section per CO molecule adsorbed on the silver particle. For Ag 50 and 457.9 nm laser excitation, an enhancement of ∼1850 was measured, which dropped to ∼1350 at 514.5 nm excitation. For Ag 30 (and 457.9 nm excitation) the enhancement was ∼530. The enhancements of Ag 3, Ag 5, and Ag 9 were too low to measure accurately (i.e., <10). Extrapolating the enhancements obtained with blue and green wavelengths to the “plasmonic” band center, which for an Ag 50 cluster is expected to be at ∼370 nm, and assuming the excitation band to be a Lorentzian with a fwhh of 0.8 eV, the maximum Raman enhancement per CO ligand in Ag 50 CO 40 was estimated to be ∼12000, in good agreement with computed results using a time-dependent density functional quantum calculation, carried out on a Ag 20 cluster complex by Jensen et al. (Jensen et al. Size-Dependence of the Enhanced Raman Scattering of Pyridine Adsorbed on Ag n ( n = 2–8, 20) Clusters. J. Phys. Chem. C 2007, 111, 4756–4764).
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 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".