Suitable Density Determination for Heavy Hydrocarbons by Solution Pycnometry: Virgin and Thermal Cracked Athabasca Vacuum Residue Fractions
Bibliographic record
Abstract
Density is an important parameter for understanding molecular packing, stability, and reactivity of petroleum fractions. The determination of density for extremely viscous residual fractions measured at high temperature (reduced viscosity) is difficult and prone to error if results are extrapolated to lower temperature ranges. This problem is addressed in the present study with fractions derived from virgin and visbroken Athabasca vacuum residua. Solution pycnometry (toluene solvent) was studied and demonstrated a feasible, fast, simple, and reliable technique, applicable to a wide variety of petroleum materials, including asphaltenes and vacuum residua. Reported densities were affected to the third decimal position [American Petroleum Institute (API) gravities found reliable to ±0.15° API]. The density for mixtures of residual oil fractions was determined to be an additive property. Athabasca vacuum residue solvent deasphalting and thermal cracked fractions are studied. Thermal cracking was observed to increase asphaltene densities to values as high as those displayed by coals, suggesting that highly aromatic-condensed structures represent these species better. Further application of the methodology is illustrated by monitoring Athabasca bitumen upgrading at bench scale.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".