Infrared spectroscopy of (CO2)N nanoparticles (30<N<14500) flowing in a uniform supersonic expansion
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.001 | 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 it