Polyol‐Derived Alkoxide/Hydroxide Base Catalysts I. Production
Bibliographic record
Abstract
Abstract A metal methoxide is more expensive than a metal hydroxide and dissolves in methanol releasing a methoxide ion without producing water. The methoxide ion has a higher reaction rate making it more preferred for industrial biodiesel production. This study describes the preparation of alkoxide catalysts from metal hydroxides and non‐volatile, non‐toxic polyols. Heating aqueous solutions of metal hydroxides and different polyols (1,2‐propanediol, 1,3‐propanediol, glycerol, xylitol and sorbitol) under vacuum yielded polyol‐derived alkoxide base catalysts (PDABC). Comparison of the drying process for respective sodium hydroxide‐polyol combinations at two mole ratios of sodium hydroxide to polyol showed that drying at 2:1 mole ratio (metal hydroxide to polyol) was more efficient than that of 3:1. Dehydration of alkaline solutions containing three or more hydroxyl groups (glycerol, sorbitol and xylitol) was faster than drying similar solutions of diols. The empirical formula determined confirmed that the resulting powders contained mono‐sodium substituted alkoxides at 1:1, 2:1 and 3:1 (sodium hydroxide: polyol) mole ratio. Fatty acid methyl esters were prepared from canola oil and methanol using glycerol sodium alkylate as a catalyst. The conversion yield of oil to methyl ester was greater than 99 %.
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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 | 0.000 |
| 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 | 0.001 |
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".