Infrared Spectra of Gas Hydrates from First-Principles
Bibliographic record
Abstract
The infrared spectra of sII gas hydrates have been computed using density functional theory for the first time, at equilibrium, and under pressure. It is also the first account of a full vibrational analysis (both guest and host vibrations) for gas hydrates with hydrocarbon guest molecules. Five hydrate structures were investigated: empty, propane, isobutane, ethane–methane, and propane–methane sII hydrates. The computed IR spectra are in good agreement with available experimental and theoretical results. The OH stretching frequencies were found to increase, while the H-bond stretching and H 2 O libration frequencies decreased with an increase in guest size and cage occupancy and with a decrease in pressure. The H 2 O bending vibrations are relatively independent of guest size, cage occupancy, pressure, temperature, and crystal structure. The guest vibrational modes, especially the bending modes, also have minimal pressure dependence. We have also provided more quantitative evidence that gas hydrate material properties are defined by their hydrogen bond properties, by linking H-bond strength to Young’s modulus. The results and ensuing vibrational analysis presented in this paper are a valuable contribution to the ongoing efforts into developing more accurate gas hydrate identification and characterization methods in the laboratory, in industry/nature, and even in outer space.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".