Complementary Experimental Data and Extended Density and Viscosity Reference Models for Squalane
Bibliographic record
Abstract
New experimental density and viscosity measurements of squalane (C 30 H 62; 2,6,10,15,19,23-hexamethyltetracosane) have been carried out in the temperature range of 283–353 K and pressures up to 40 MPa for density and 303–333 K and pressures up to 20 MPa for viscosity. The viscosity was measured with an improved capillary technique that avoids calibration at high pressures, which results in better accuracy in the case of capillary techniques. The new data and the data currently available in the open literature were used to develop new density and viscosity reference models. A previously published Tait density reference equation of state (EoS) has been reviewed, upgraded with the most recent data, and extended in the temperature range. Additionally, a friction theory viscosity model has been coupled to the reviewed Tait EoS. Both the density and viscosity models are reliable in the 280–550 K temperature range and pressures up to 400 MPa. The models’ accuracy is better than 0.2% for density and between 2 and 3% for viscosity in the full range of temperature and pressure. For pressures up to 200 MPa, the viscosity model is expected to deliver an overall accuracy of 2% and can be reliably extrapolated up to 400 MPa, about twice the validated pressure range of the Tait EoS. The model is intended for viscosity calibration of high-pressure industrial equipment for dense fluids, such as reservoir fluids at deep-water conditions.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".