Molecular Dynamics Simulations of Hydrogen Bonding in Clathrate Hydrates with Ammonia and Methanol Guest Molecules
Bibliographic record
Abstract
We performed molecular dynamics simulations of the ammonia and methanol-based clathrate hydrates with the emphasis on characterizing hydrogen-bonding interactions of these guest molecules with the water lattice. Systems studied include structure II (sII) binary clathrate hydrates of tetrahydrofuran (THF) (large cage, L) + NH 3 (small cage, S) and THF (L) + CH 3 OH (S), the structure I (sI) pure NH 3 (L), pure CH 3 OH (L), the binary NH 3 (L) + CH 4 (S), and binary CH 3 OH (L) + CH 4 (S) clathrate hydrates. We simulated these clathrate hydrates with the transferable intermolecular potential with four point changes (TIP4P) water potential and the TIP4P/ice water potential to determine the effect of the water potential on the predicted hydrogen bonding of the guest molecules. Simulations show that, despite strongly hydrogen bonding with the framework water molecules, clathrate hydrate phases with NH 3 and CH 3 OH can be stable within temperatures ranges up to 240 K. Indeed, a limited number of thermodynamic integration free energy calculations show that both NH 3 and CH 3 OH molecules give more stable guest–host configurations in the large sI clathrate hydrate cages than methane guests. Predictions of hydrogen bonding from simulations with the two different water potentials used can differ substantially. To study the effect of proton transfer from water to the basic NH 3 guests, simulations were performed on a binary NH 3 + CH 4 sI clathrate hydrate where less than 10 % of the ammonia guests in the large cages were converted to NH 4 + and a water molecule of the hydrate lattice in the same large cage was converted to OH – . The small percentage of proton transfer to ammonia guests in the large cages did not affect the stability of the resultant hydrate. The structural perturbations in the lattice that result from this proton transfer are characterized.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".