Rate and equilibrium constants for formation and hydrolysis of 9-formylfluorene oxime: diffusion-controlled trapping of a protonated aldehyde by hydroxylamine
Bibliographic record
Abstract
Equilibrium constants Kadd = 440 and Kox = 3.0 × 108 for formation of a carbinolamine adduct and oxime, respectively from 9-formylfluorene and hydroxylamine, and pKa = 1.62 for protonation of the oxime, have been evaluated at 25°C in aqueous solution, based on measurements in hydroxylamine buffers, acetic acid buffers, and dilute HCl. Rate constants for hydrolysis of the oxime have been measured in the acidity range pH 412 M HClO4. At the highest acidities, a reaction pathway via protonated carbinolamine has been identified: evidence is presented that the reverse of this reaction involves rate-determining attack of hydroxylamine upon protonated 9-formylfluorene. By assuming that the attack of hydroxylamine is diffusion-controlled, with rate constant 3 × 109 M 1 s1, a pKa for O-protonation of the aldehyde (4.5) is derived. Taking account of the equilibrium constant for enolization of 9-formylfluorene (KE = 16.6), a pKa for for C-protonation of the enol tautomer ((5.7) may also be obtained. Comparison of this pKa with that of the enol of acetophenone shows that the enol of 9-formylfluorene is less basic by a factor of 1010. By combining pKas for protonation of the aldehyde and oxime with measured or estimated equilibrium constants for addition of water, hydroxide ion, and hydroxylamine to 9-formylfluorene, it is also possible to obtain values of pKR = 5.3, 4.1, and 12.25 for the protonated 9-formylfluorene, protonated oxime, and 9-formylfluorene, respectively. The usefulness of pKR in providing a general measure of equilibrium constants for electrophile-nucleophile combination reactions is discussed.Key words: oxime, formyfluorene, hydrolysis, protonation, diffusion-control.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".