Infrared spectroscopy of (CO2)N nanoparticles (30<N<14500) flowing in a uniform supersonic expansion
Bibliographic record
Abstract
The infrared signature of carbon dioxide clusters of nanometric size is discussed both in the bending (ν2 mode at 15 μm) and in the asymmetric stretching (ν3 mode at 4.2 μm) spectral region of the monomer. The carbon dioxide nanoparticles were formed using a capillary tube injection inserted upstream of a uniform supersonic flow of argon generated by a Laval nozzle. The size of the formed clusters was varied by changing the stagnation pressure P0 of the capillary. The empirical power law connecting P0 to the number N of monomers per cluster: N∝P02.2 was verified in this work. The cluster mean size was estimated using a Rayleigh scattering experiment showing the formation of nanometric clusters whose radii are in the range 0.7 nm<r<5.3 nm, corresponding to 30<N<14 500. The thermodynamic and kinetic parameters of the flow were determined from the rovibrational absorption lines of the monomer and from a time-of-flight experiment. The measured flow velocity and flow temperature show that CO2 condensation is responsible for both a strong flow warming and a non-negligible flow acceleration. The translational and rotational temperatures of the monomers were found to be identical, highlighting a thermal equilibrium between these two motions. The cluster temperature Tc ranging from 93 to 135 K was estimated assuming a thermal equilibrium between the clusters and the monomer bath, induced by a high flow density of about 1016 molecules cm−3. The double peak feature at 657 and 667 cm−1 reflects the crystalline nature of the clusters. A single Lorentzian peak is observable at 2360 cm−1 whose position however appears to be weakly size dependent. The pronounced narrowing of the peak with increasing N surprisingly stopped evolving for N=820 and Tc=108 K.
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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 | 0.001 |
| 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".