Evaluating Characteristic Parameters for Carbon Dioxide in the Sanchez–Lacombe Equation of State
Bibliographic record
Abstract
For many different pure substances, large numbers of competing characteristic parameter sets exist in the literature for the Sanchez–Lacombe equation of state. This is due in part to differing research requirements or differing procedures used for determining the parameters. The existing parameters for carbon dioxide are reviewed in order to determine whether a single set of parameters can describe the equation of state over large ranges of temperature and pressure. It is found that by consideration of a large collection of experiments, a good fit can be achieved over much larger temperature and pressure ranges than previously thought possible. Properties directly related to the equation of state, such as the thermal expansivity and isothermal compressibility, are also predicted well; however, as expected, properties that depend on the internal degrees of freedom of molecules, such as the specific heats, do not correlate well. Closely agreeing parameter sets are found in the literature that fit the equation of state data reasonably well over a large range. A new set of parameters is found using a least-squares approach over the largest ranges of temperature and pressure to date. These parameters are found to be P * = 419.9 MPa, T * = 341.8 K, and ρ*= 1.397 g/cm 3 using N = 556 experimental data points over the temperature range of 216.58–1800 K and the pressure range of 0.5–66.57 MPa.
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 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 | 0.001 |
| 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 | 0.001 | 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".