Methanol incorporation in clathrate hydrates and the implications for oil and gas pipeline flow assurance and icy planetary bodies
Bibliographic record
Abstract
One of the best-known uses of methanol is as antifreeze. Methanol is used in large quantities in industrial applications to prevent methane clathrate hydrate blockages from forming in oil and gas pipelines. Methanol is also assigned a major role as antifreeze in giving icy planetary bodies (e.g., Titan) a liquid subsurface ocean and/or an atmosphere containing significant quantities of methane. In this work, we reveal a previously unverified role for methanol as a guest in clathrate hydrate cages. X-ray diffraction (XRD) and NMR experiments showed that at temperatures near 273 K, methanol is incorporated in the hydrate lattice along with other guest molecules. The amount of included methanol depends on the preparative method used. For instance, single-crystal XRD shows that at low temperatures, the methanol molecules are hydrogen-bonded in 4.4% of the small cages of tetrahydrofuran cubic structure II hydrate. At higher temperatures, NMR spectroscopy reveals a number of methanol species incorporated in hydrocarbon hydrate lattices. At temperatures characteristic of icy planetary bodies, vapor deposits of methanol, water, and methane or xenon show that the presence of methanol accelerates hydrate formation on annealing and that there is unusually complex phase behavior as revealed by powder XRD and NMR spectroscopy. The presence of cubic structure I hydrate was confirmed and a unique hydrate phase was postulated to account for the data. Molecular dynamics calculations confirmed the possibility of methanol incorporation into the hydrate lattice and show that methanol can favorably replace a number of methane guests.
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 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 | 0.001 |
| 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 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".