Bibliographic record
Abstract
Experimental data on the kinetics of formation of structure H gas hydrate obtained in a semibatch stirred vessel at pressures of 0.63−1.5 MPa above equilibrium are reported. Methane was used as a guest substance and neohexane, tert -butyl methyl ether, and methylcyclohexane were used as the large molecule guest substance (LMGS). The results indicate that the rates of hydrate formation and the induction times are dependent on the magnitude of the driving force and the type of LMGS. When tert -butyl methyl ether is used as the LMGS, rapid hydrate formation and a much smaller induction time can be achieved. Furthermore, the methane consumption rate for hydrate formation in the presence of tert -butyl methyl ether is 3 times greater than that for a pure methane−water system. It was also observed that, although the induction period was greatly shortened by the memory effect, the rate of gas consumption rate was not affected. Hydrate decompositions were also conducted at a pressure 20% below equilibrium. The system with tert -butyl methyl ether as LMGS exhibited the fastest decomposition rate.
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 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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".