Microfluidic Approach for Evaluating the Solubility of Crude Oil Asphaltenes
Bibliographic record
Abstract
In this paper, we describe a microfluidic approach for measuring the solubility of asphaltenes in a sample of crude oil. The solubility parameter is an important property in assessing stability of asphaltenes in crude oils and crude mixtures, particularly when blending different oils or adding diluents. A range of solvent–precipitant mixtures are added to the crude oil, which modifies the native solubility properties, and the degree of asphaltene precipitation is monitored by the change in optical absorbance for each chosen solvent volume fraction. The microfluidic solubility profiles acquired in hours are compared to conventional gravimetric measurements obtained over days and demonstrate excellent agreement. We also show the application of the data generated for tuning solubility parameter-based thermodynamic models of asphaltene precipitation in mixtures of solvents and precipitants. The microfluidic data were used to determine the asphaltene solubility parameter that ranged from 20 to 23 MPa 1/2 for the crude oils used in this study, in agreement with previous reports. The more efficient use of labor and the reduction in measurement time enabled by the microfluidic method will allow for more frequent asphaltene characterization for evaluating stability and tuning models.
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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 | 0.001 | 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".