Reaction rate constant of CO<sub>2</sub> hydrate formation and verification of old premises pertaining to hydrate growth kinetics
Bibliographic record
Abstract
Abstract Experimental data on the rate of carbon dioxide hydrate formation in a semibatch stirred‐tank reactor was obtained using a particle‐size analyzer capable of detecting particles as small as 0.6 nanometers in a closed‐loop system. Experiments were carried out at temperatures between 275.3 and 279.4 K and pressures ranging from 2,014 to 3,047 kPa. The reaction rate constant of CO 2 hydrate formation was determined using a newly developed kinetic model independent of the dissolution rate at the vapor‐liquid water interface. The average reaction rate constant determined experimentally was found to increase with temperature following an Arrhenius‐type relationship, from 1.8 × 10 −8 m/s to 1.8 × 10 −7 m/s, over the 4‐degree range investigated. Similarly, the reaction rate constant calculated from a population balance varied from 1.4 × 10 −8 m/s to 1.7 × 10 −7 m/s over the same temperature interval. The initial number of hydrate particles was calculated using the mole fraction of the gas hydrate former in the bulk‐liquid phase at the onset of hydrate growth rather than the equilibrium solubility. The cumulative relative scattering was also compared to the derived count rate to determine whether or not the number of hydrate particles remained constant during the hydrate growth experiment. © 2008 American Institute of Chemical Engineers AIChE J, 2008
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".