Interactions Between Athabasca Pentane Asphaltenes and<i>n</i>-Alkanes at Low Concentrations
Bibliographic record
Abstract
The mass fraction and the properties of asphaltenes vary significantly with the n -alkane used to separate them from their parent oil and with the details of the separation procedure, such as washing steps. Measurement repeatability is challenging, with different error bounds reported within the American Society for Testing and Materials (ASTM) standards for a single operator using the same equipment and procedure vis-à-vis measurements performed by different operators in different laboratories. In this work, reversible interactions between Athabasca pentane asphaltenes and n -alkanes from pentane to hexadecane were observed using cross-polarized and visible light microscopy and were quantified using high-precision density measurements for mixtures ranging from 1000 to 8000 ppmw (from 0.8 to 6.5 g/L) and enthalpy of solution measurements for mixtures comprising from 1000 to 3500 ppmw (from 0.8 to 3 g/L) asphaltenes. The partial specific volumes of Athabasca pentane asphaltenes and the enthalpy of solution values, including a change of sign, were found to vary systematically with n -alkane carbon number. The microscopic observations revealed the formation of liquid crystals followed by isotropic liquid on the surface of the asphaltene particles. The interactions at low concentrations are consistent with n -alkane sorption by asphaltene particles, asphaltene particle swelling, and dissolution of a fraction of the asphaltenes in n -alkanes. The partial specific volume and enthalpy of solution results, simulated using a phenomenological model that includes these effects, explain the sensitivity of the repeatability of asphaltene mass fraction determinations to the details of the washing procedure applied during their preparation. Preparation techniques without washing appear to be preferred because the mass fractions of asphaltenes recovered are expected to be more repeatable and their properties are likely to be more consistent.
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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) | 0.002 | 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".