Effect of Ion Specificity on Thermodynamic Inhibition of CH4 and CO2 Hydrates: An Experimental and Modeling Study
Bibliographic record
Abstract
The effects of iodide salts and ion specificity on the thermodynamic inhibition of CH 4 and CO 2 hydrates have not been thoroughly investigated. In this study, we employ the isochoric pressure-search method to measure the dissociation temperature (272.48 – 286.54 K) and pressure (1.38 – 11.24 MPa) of CH 4 and CO 2 hydrates in iodide solutions with concentrations of 6.24 wt% and 12.48 wt%. The measured data are subsequently used to validate a thermodynamic model integrating the Pitzer model into the van der Waals-Platteeuw (vdW-P) model for predicting the dissociation pressure of gas hydrates. The model can accurately predict the dissociation conditions of CH 4 and CO 2 hydrates in iodide solutions. The experimental results reveal that the inhibition effect of iodide salts on CH 4 and CO 2 hydrates is enhanced with an increasing salt concentration. Additionally, the dissociation temperature suppression of CH 4 and CO 2 hydrates is correlated with water activities of different salt solutions to investigate the effect of ion specificity on the thermodynamic inhibition of these hydrates. Our analysis demonstrates that ion specificity exists in the thermodynamic inhibition of CO 2 hydrate but does not apply to CH 4 hydrate. In addition, anions play a major role in the thermodynamic inhibition of CO 2 hydrate.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".