Relationship between Raman spectral features and fugacity in mixtures of gases
Bibliographic record
Abstract
Abstract Raman spectroscopy yields information about the internal vibrational modes of covalently bonded molecules, which are sensitive to the local molecular environment. As such, Raman spectra of a gas composed of covalently bonded molecules collected at different temperatures and/or pressures show variations in band positions and other spectral features, reflecting molecular‐scale interactions (attraction and repulsion) among gas particles associated with the local physical and chemical environment. Because the molecules interact, gases are nonideal, and fugacity is the fundamental thermodynamic quantity that describes partial pressures of gases, adjusted to account for the nonideality. The fugacity of a substance is generally obtained from thermodynamic calculations rather than by direct analysis or measurement and, as such, is conceptually nebulous. Here, we perform spectroscopic analyses of a gas mixture of known composition at variable and known pressures and couple these results with thermodynamic calculations of gas fugacities. We show that Raman peak shifts in gas mixtures are directly correlated to fugacities of the component gas species. Our results thus provide experimental evidence that fugacities of gases can be estimated from Raman spectra collected in situ . By this approach, the thermodynamic quantities fugacity and the related thermodynamic property activity are linked directly with underlying molecular‐scale phenomena, according to the vibrational properties of molecular species. This represents a tractable method to efficiently obtain large datasets on thermodynamic properties of gas mixtures, and with some adjustments, may lead to a viable method for developing nonideal mixing rules for other substances, such as crystalline solid solutions, aqueous ions, and electrolytes.
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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) | 0.001 | 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".