Diesel Precursors Via Catalytic Hydrothermal Deoxygenation of Aqueous Canola Oil Emulsion
Bibliographic record
Abstract
Abstract Aqueous extraction for protein isolation from oilseeds is a promising alternative to the conventional hexane‐based solvent extraction widely used in the industry. However, during aqueous extraction, a stable oil‐in‐water emulsion is produced that results in decreased oil yield. We demonstrated the conversion of this aqueous extract into renewable hydrocarbons on 20%w/w Ni/C at 315 °C and at an initial hydrogen headspace pressure of 1.95 MPa. Moderate yield (>50%) and selectivity (~70%) of hydrocarbons within the diesel range were obtained within 12 hours of reaction without additional external hydrogen input. It was also shown that a prolonged experimental run at 305 °C can result in near‐complete conversion of triacylglycerol oil into diesel‐range hydrocarbons (70%) and oxygenates (9%) with selectivity of ~80%. Although the study demonstrates for the first time the possibility of integrating aqueous extraction of protein with renewable diesel production in a hydrothermal medium, the limitations and challenges experienced during this initial study justify additional work that is presently underway.
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 | 0.000 | 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".