Comparison of the nucleophilicities of alcohols and alkoxides
Bibliographic record
Abstract
The kinetics of the reactions of benzhydrylium ions with some alcohols and alkoxides dissolved in the corresponding alcohols were photometrically investigated. Using the correlation equation log k (20 °C) = s(E + N), the N and s parameters of methoxide, ethoxide, n-propoxide, and isopropoxide in alcoholacetonitrile (91:9, v/v) were determined. The cosolvent acetonitrile has only a little influence on the rate constants of the reactions of alcohols and alkoxides. The order of N values (OH << MeO < EtO < n-PrO < i-PrO) shows that alkoxides differ only moderately in reactivity but are considerably more nucleophilic than hydroxide. As a consequence, the nucleophilic reactivity of a 0.5 mmol/L aqueous hydroxide solution increases by a factor of 13 when 10% (v/v) methanol is added. In 110 mmol/L alkoxide solutions in alcohols, weak electrophiles react considerably faster with alkoxides than with the corresponding alcohols. With increasing electrophilicity, the preference for alkoxides decreases, and electrophiles of 3 < E < 3 react with alkoxides (110 mmol/L) and alcohols with comparable rates. Stronger electrophiles will react with alcohols exclusively when alkoxides are present in concentrations ≤10 mmol/L. Key words: kinetics, alcohol, alkoxide, linear free energy relationship, nucleophilicity.<
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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 | 0.001 |
| 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 | 0.000 | 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".