Optimal conditions determination for hydrodeoxygenation of free fatty acids to obtain green diesel
Bibliographic record
Abstract
Abstract In this work, the production of green diesel involving the hydrodeoxygenation reaction of vegetable oil, such as oleic acid, producing CO or CO 2 as byproducts, was studied. This reaction takes place under hydrogen saturation to produce stearic acid; subsequently, heptadecane is produced by the decarbonylation and decarboxylation pathways, while octadecane is obtained by the subsequent hydrodeoxygenation of octadecanal. In the formation of octadecane, water is obtained as a byproduct, while the production of heptadecane leads to CO and CO 2 as byproducts of the decarbonylation and decarboxylation reactions. When considering the products and reaction routes in the hydrotreatment of triglycerides and free acids, a mathematical model was found to be reliable in determining the minimization of the Gibbs free energy of reaction over a range of reaction temperatures and pressures. This model followed the methods of Marrero‐Gani, Joback‐Reid, and Chen‐Dinivahi‐Jeng for the estimation of thermodynamic properties of the pure components. The fugacity was calculated by considering the partial fugacity coefficients, and the Peng‐Robinson equation of state and the van der Waals mixing rule were used. The mole fractions at equilibrium were estimated by least squares analysis, using MATLAB, in order to account for non‐idealities in reaction thermodynamic properties and to find the equilibrium composition that minimized the total Gibbs free energy. Likewise, the reaction coordinates of the equilibrium reaction were estimated together with the known values of the composition in order to know the effect of pressure and temperature on the aforementioned reactions.
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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".