Phase equilibrium and liquid mole fraction measurements of tetra-n-butylammonium chloride-carbon dioxide methane-semi-clathrates
Bibliographic record
Abstract
Gas hydrates have many potential industrial applications in gas storage and transportation, particularly for the purpose of reducing energy consumption thus carbon footprint in the transportation of natural gas.Regarding gas storage, the possibility of reducing greenhouse gas emissions via the sequestration of carbon dioxide in the form of gas hydrates.However, to scale up these technologies a fundamental understanding of their formation is required.They require high pressures and low temperatures to form.One of the low-cost alternatives consists of using thermodynamic promoters such as tetra-n-butylammonium chloride (TBAC).These promoters reduce the hydrate equilibrium conditions making them more energetically favorable, allowing higher temperatures and lower pressures to form hydrates.This thesis investigates and studies the three-phase equilibrium conditions and liquid mole fraction measurements of CH4-TBAC-H2O and CO2-TBAC-H2O semi-clathrates.The importance of these liquid mole fraction measurements is for use in reactor design and kinetic models.Concentrations of 5-wt%, 10-wt% and 15-wt % of TBAC were employed.Results from this study show that the thermodynamic promoter used has a significant effect in reducing the semi-clathrate equilibrium conditions for both methane and carbon dioxide.For methane, a pressure range of 0.8 MPa to 4.7 MPa, a temperature range of 280 to 290 K were used with a corresponding mole fraction range from 0.37x10 -3 to 1.88x10 -3 .For carbon dioxide, the pressure range was from 0.1 to 2.4 MPa and temperature was varied from 277 to 288 K with a corresponding mole fraction from 1.42x10 -3 to 18.75x10 -3 .opportunity you gave me to be part of your research group.It has been a pleasure to be part of McGill under your supervision.When I look back to remember the times as a master's student, I will always remember the good moments we all the group had in the BBQs, meetings, and visits to the office.The culmination of this work would not have been the same without the help of my lab and office colleagues Faraz Rajput, Jason Ivall and Francois Pelletier, especially Ahmad Kahn and Jean-Sebastian Renault-Crispo.Without your help Seb, it would have been harder.I thank you very much for the unconditional support you gave me since the first days.The ideas, guidance, and support you gave me in my project were very significant to me making the path clearer and more understandable.Querer es poder, es una de las frases con más años viviendo dentro de mi cabeza.La escuché de mi mamá que siempre me han alentado a seguir adelante.Escribo estas líneas para agradecerle infinitamente a mi mamá Lupita Sandoval y a mi papá Rafa Marín por haberme formado, orientado y educado de la increíble forma que lo hicieron convirtiéndome en la persona que soy.
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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 | 0.000 |
| Open science | 0.000 | 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".