Semicontinuum (Cluster-Continuum) Modeling of Acid-Catalyzed Aqueous Reactions: Alkene Hydration
Bibliographic record
Abstract
An effort is made to reduce the errors of continuum solvation models (CSMs) with semicontinuum modeling to achieve 3 kcal mol –1 agreement with experiment for acid-catalysis activation Gibbs energies. First, two underappreciated CSM issues are reviewed: errors in the CSM solvation Gibbs energies grow beyond 5 kcal mol –1 (i) as ions are made smaller and (ii) as water clusters grow larger. Second, the computational reproduction of the known Gibbs energies (Δ r G and Δ ‡ G ) of the paradigmatic reaction ethene + H 2 O + H 3 O + → TS + → ethanol + H 3 O + is attempted. It is argued that, despite the >5 kcal mol –1 solvation errors for ions, it is possible to employ error cancellation strategies to reduce the errors in the reaction and activation Gibbs energies to 3 kcal mol –1 accuracy. A new 3 kcal mol –1 effect due to solvent-molecule “placement” (confinement from 1 M bulk concentration) was isolated and proved useful. Third, computational reproduction of the known entropies (Δ r S and Δ ‡ S ) of the paradigmatic reaction is attempted using Trouton’s constant and neglect of solvent structure reorganization effects (which must cancel well for this reaction); this worked well for Δ r S but needs empirical correction of ∼11 cal mol –1 K –1 for Δ ‡ S due to solvent disorientation when H 3 O + is consumed. These entropy estimates allow for enthalpy (Δ r H and Δ ‡ H ) estimation from the Gibbs energy values. Fourth, two recommended options, including A + H 3 O + ·2W → [AHOH 2 + ·2W] ‡, are shown to also work well for the activations of propene and isobutene.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".