Transesterification of palm oil in a microtube reactor
Bibliographic record
Abstract
Abstract Transesterification of palm oil and methanol with KOH as a catalyst in biodiesel synthesis was studied in a microtube reactor. The first part is the investigation on the influences of catalyst amount (5–13 mg/g, 0.5–1.3 mass%), reaction temperature (52–70 °C), methanol‐to‐oil molar ratio (4.5:1–9:1), and residence time (5–20 s) on fatty acid methyl ester content (%FAME). The optimal %FAME of 97.14 % was achieved with the catalyst amount of 10 mg/g (1 mass%), operating at 60 °C, and using a methanol‐to‐oil molar ratio of 6:1 and a residence time of 5 s. High %FAME was obtained at low residence time due to the small size of droplets in the micro‐channel reactor. The second part deals with the effect of mixer and reactor geometry. A comparison between %FAME obtained from the synthesis in a batch stirred‐tank reactor and in a microtube suggested that the reaction proceeded much faster for the latter. The use of a T‐mixer provided superior reaction performance compared to the J‐mixer throughout the conditions studied.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".