Bibliographic record
Abstract
Recently it has become apparent that the mechanism of amide hydrolysis in relatively dilute strong acid media is the same as the one observed for ester and benzimidate hydrolysis, two water molecules reacting with the O-protonated amide in the rate-determining step. This is not the whole story, however, at least for benzamide, N-methylbenzamide, and N,N-dimethylbenzamide, since the observed rate constants for these substrates deviate upwards from the observed excess acidity correlation lines at acidities higher than about 60% H2SO4, meaning that another, faster, reaction with a different mechanism is taking over at higher acidities. It has never been clear what this latter mechanism was until the work reported in this paper. An exhaustive excess acidity analysis of all the available measured reaction rate constants for the three substrates in three different acidic media, aqueous H2SO4, aqueous HClO4, and aqueous HCl, shows that this second mechanism involves a second rate-determining proton transfer to the O-protonated benzamide, followed by (or possibly concerted with) irreversible loss of +NH4 to give an acylium ion. Subsequent reaction of this with water (or bisulfate, etc.) eventually gives the observed carboxylic acid product. This latter reaction mechanism has never been previously considered for amide hydrolysis, but it may not be uncommon; at least one other reaction with a similar mechanism is known, and another possible case is suggested.Key words: amides, benzamides, hydrolysis, excess acidity, mechanism, acid media.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".