Steam Distillation of Acidulated Soapstock and FAME Synthesis
Bibliographic record
Abstract
Use of rapeseed soapstock to produce biodiesel is a sustainable choice, because it deals with waste stream use in biofuel synthesis and lowers the use of food grade oil as fuel feedstock.Rapeseed soapstock was acidulated, and fatty acid and glycerides containing acid oil was separated from water phase.Steam distillation -a mild purification method -was used to separate fatty acids from acid oil.Distilled fatty acids were subjected to sulfuric acid catalyzed esterification with methanol.The chosen reaction conditions were: 65 °C temperature, molar ratio of MeOH to FFA 20:1, 7.5 mol% H2SO4, and a reaction time 1 h.Esterification of distilled fatty acids proceeded with 98.3-98.5% conversion to FAME and product yield 93-95% from theoretical.The esterification reaction conditions were determined using lauric acid as model compound, the catalyst concentration was adjusted to be less than usually reported, so to avoid oxidation and side reactions.Use of ultrasound assisted synthesis was elaborated by comparing reaction of lauric acid at 25 °C temperature in ultrasonic bath and with stirring.Reaction was faster with stirring than use of ultrasound.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| 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) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".