Tuning Ionic Liquids for Simultaneous Dilution and Demulsification of Water-in-Bitumen Emulsions at Ambient Temperature
Bibliographic record
Abstract
Abstract Thermal and flotation processes are widely used to produce bitumen from oil sand in Alberta. However, bitumen contains many surface-active components that tend to form water-in-oil emulsion stabilized by fines and/or asphaltenes. Although several demulsifiers have been proposed in the literature to treat such emulsions, these chemicals are sometimes not effective. We propose ionic liquids whose composition has been designed to enable effective treatment of these emulsions. Different ionic liquids were synthesized and tested for their efficiency in treating bitumen emulsion obtained from a field in Alberta. Ionic liquids tested are mixtures of organic bases with acids. Mixtures of ionic liquids and bitumen emulsion were prepared at several mass ratios. The two components were mixed under ambient conditions. After mixing, segregation of different components in the mixture was accelerated by centrifugation for rapid assessment of the degree of emulsion breaking. Optical microscopy, rheology, thermal gravimetric analysis, and viscosity measurements were used to assess the effect of ionic liquids on bitumen emulsions. The first set of ionic liquids with cations of different alkyl chain lengths were able to separate the water from the emulsion. However, these ionic liquids tend to form a gel when mixed with water. The number and length of alkyl chains proved critical for avoiding gel formation. Ionic liquids with multiple long chains on the cation were immiscible with the separated water. These ionic liquids were very efficient in diluting and demulsifying bitumen emulsion. The emulsion droplet sizes increased upon addition of the ionic liquid. The ionic liquid mixes into the bitumen phase released from the emulsion, yielding a viscosity at ambient temperature close to the pipeline specifications. This work demonstrates that ionic liquids can be tailored to break bitumen emulsions effectively without heat input. The process developed in this paper can replace current practice for the demulsification and dilution of bitumen emulsions, which requires the emulsion to be heated significantly. Hence the ionic liquid process reduces the heat requirements and hence greenhouse gas emissions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".