Use of liquid carbon dioxide to remove hexane from soybean oil
Bibliographic record
Abstract
Abstract Liquid carbon dioxide (L‐CO 2 ) was investigated as a means to separate hexane from the mixture of soybean oil (SBO) and hexane resulting from the hexane extraction of soybeans. Using a fractionation tower, 5 vol of CO 2 (i.e., 100, 200, 300, 500, and 1000 L expanded gas) were passed through 50 mL of two concentrations of n ‐hexane (i.e., 10 and 25% w/w) in SBO. After passing through the hexane/SBO mixture, the expanded CO 2 was passed through a chilled collection flask to capture extracted hexane and SBO. The raffinate SBO was removed from the column and analyzed for residual hexane using International Organization for Standardization Method 9832:2002. Residual hexane decreased as the amount of L‐CO 2 used increased and was less than 20 ppm after 200 L of CO 2 . The amount of SBO extracted increased with the volume of CO 2 used. Significantly more SBO and hexane were collected from the 25% sample than the 10% sample. During the extraction of the mixture, the CO 2 selectively carried over TG with lower M.W. This research demonstrates the ability to use L‐CO 2 to remove haxane from mixtures of hexane and SBO at both low pressures and temperatures.
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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) | 0.000 | 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".