The Determination of Proton Affinities of Secondary Alcohols from the Dissociation of Proton-Bound Molecular Trios. A New Application of the Kinetic Method
Bibliographic record
Abstract
The kinetic method for determining proton affinity ( PA) values requires that the competing dissociations of proton-bound pairs of bases, AH + B n , essentially only lead to AH + and B n H + ions. The method fails for secondary alcohols because other reactions, involving rearrangement of the AH + B n ion, are dominant. It was found that proton-bound trios of bases, A 2 H + B n , (which incorporate secondary alcohols B n with a primary alcohol, A) do not suffer from this disadvantage. The proton-bound trios decomposed cleanly, to yield only A 2 H + and AH + B n ions. Application of the kinetic method to these competing reactions allowed the PA values for the secondary alcohols to be determined using the appropriate molecular-pair proton affinity [ MPPA] values. The MPPA is the negative of the enthalpy change, [–Δ H], accompanying the formation of a proton-bound pair from the component alkanols and a proton. These were readily estimated using known binding energies, D[AH + –B n ] and established PA values for n-alkanols. In the present brief study, PA values for isopropanol, cyclobutanol and cyclopentanol were measured to be 796, 792 and 798, all ± 6 kJ mol −1 . The results for the cyclic alcohols relate well with the available data from similar compounds, where the C 3 –C 5 rings display lower PA values than their acyclic analogues. This effect is attributed to restricted charge delocalization in the small rings.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".