Epoxidation of crambe seed oil with peracetic acid formed in situ
Bibliographic record
Abstract
Abstract This study investigated the epoxidation of crambe seed oil (CSO) using peracetic acid formed in situ during the reaction process. First, a preliminary study of the main operational variables was carried out. Then, the kinetic behavior of the reaction was verified, evaluating the effect of the molar ratio of hydrogen peroxide to ethylenic unsaturation, catalyst percentage and temperature. The results indicate that the smallest amount of hydrogen peroxide (1.1 mol mol−1) favors the relative conversion to oxygen oxirane (RCO) and that an increase in the catalyst percentage up to 2.4 wt% intensifies the reaction, maintaining the stability of the process. In addition, the reaction carried out at high temperatures results in greater conversions in short time, however, it is necessary that the reaction is stopped at the exact time, avoiding exceeding the formation of epoxy resulting in the obtaining of by‐products. Some unsaturated fatty acids are partially consumed while others (linolenic and gondoic acid) are completely consumed during the entire reaction. The epoxidized oils showed higher viscosities in relation to the CSO. The FTIR spectra indicated the appearance of the epoxide group and the analysis by gas chromatography coupled to a mass spectrometer indicated the formation of two epoxidized compounds, 3‐octyl oxirane octanoic acid and 10‐oxo‐octadecanoic acid methyl ester. The highest efficiency for the formation of CSO epoxides, within the ranges of the variables evaluated, was observed at 80°C, 8 h reaction, using a H2O2 to CC molar ratio of 1.1 mol mol−1 and 2.4 wt% H2SO4.
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 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 | 0.000 |
| 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) | 0.001 | 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 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".