Recovery and Recycling of Isopropyl Alcohol Used in Biodiesel Production From Yellow Mustard Oil
Bibliographic record
Abstract
Abstract The recovery of solvents used during biodiesel synthesis is an important factor in the economic feasibility and sustainability of the entire process. In this study, we looked at the use of isopropyl alcohol (IPA) for oil extraction and biodiesel production, as well as its potential for recovery and recycling. We found that multistage extraction improved oil recovery, with up to 86% oil yield using four stages of extraction at an IPA:mustard flour (volume:weight) ratio of 1.5:1 at room temperature. Using acid–base‐catalyzed transesterification, 99% of the mustard oil was converted to biodiesel. At the end of this process, IPA was recovered from the azeotrope by salting out using potassium carbonate or sodium carbonate. The solubility behavior of the components was evaluated by means of ternary‐phase diagrams of IPA/water/sodium carbonate and IPA/water/potassium carbonate, which determined their liquid–liquid–solid equilibrium constants at ambient pressure and at room temperature. Using 20% (w:w) potassium carbonate, 95% of the IPA was recovered at 99% purity from a starting mixture of IPA containing 13% water. Azeotropic distillation of the IPA–water azeotrope with 10% potassium carbonate resulted in the recovery of 99% of the IPA at 94% purity. These results suggest that IPA is not only a suitable solvent for mustard‐oil extraction but also for salt‐enhanced azeotropic distillation resulting in near‐complete recovery from aqueous solutions.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".