The Strecker reaction — an examination in terms of no-barrier theory
Bibliographic record
Abstract
For those examples of the Strecker reaction where information about both rate and equilibrium is available, we have been able to calculate rate constants for the addition of cyanide ion to the iminium ion by the no-barrier theory (NBT) approach. Both experimental and calculated values are for reaction in aqueous solution. Only for the reactions of benzaldehyde with benzyl or allyl amines and HCN are the equilibrium constants and rate constants for the final, rate-determining, step directly available from the literature. For the reactions of acetone with ammonia, methylamine, or dimethylamine and HCN rate constants for the retro-Strecker cleavage and the equilibrium constants for the overall Strecker reaction have been reported. These equilibrium constants, combined with equilibrium constants for iminium ion formation, which can be extracted from information in the literature, allow calculation of the equilibrium constants for the final step of these Strecker reactions. No-barrier theory has already been applied to carbonyl additions, including cyanohydrin formation; this report provides further evidence for the generality of this approach for calculating rate constants without using any kinetic information.Key words: Strecker reaction, rate constant, equilibrium constant, no-barrier theory, computation.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".