Transesterification catalyst strength as observed by solution-based oxygen-17 nuclear magnetic resonance spectroscopy
Bibliographic record
Abstract
Natural abundance oxygen-17 nuclear magnetic resonance spectroscopy ( 17 O-NMR) was applied to study homogeneous transesterification catalysts for fatty acid methyl ester production. Alkoxide catalysts were made with selected permutations of lithium, sodium, magnesium, and potassium hydroxides with ethanol, methanol, isopropanol, and glycerol. Pilot scale transesterification reactions of Canola oil were completed and the 17 O-NMR spectra were collected from the reaction products. The alkoxide solutions showed the downfield shifts relative to the reagent alcohol, in a linear relationship with the concentration of catalyst ion. The electron deshielding of the oxygen of the alkoxide catalyst is observed directly by 17 O-NMR, and the fastest catalyst has the largest downfield (high frequency) shift. This effect is most pronounced in potassium methoxide and less pronounced for less polar solvents such as isopropanol.
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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) | 0.001 | 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 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".