Challenges in predicting Δ<sub>rxn</sub><i>G</i> in solution: Hydronium, hydroxide, and water autoionization
Bibliographic record
Abstract
Abstract Standard non‐semiempirical continuum‐dielectric orbital‐based methods horribly overpredict, by 26‐50 kcal mol −1 , the Gibbs energy for the water autoionization reaction 2 H 2 O (l) → H 3 O + (aq) + OH – (aq) . Here, we demonstrate these errors, fully investigate the reasons for these errors, and show that the use of 4 explicit solvent within the continuum (the “semicontinuum,” “cluster‐continuum,” or “hybrid” technique) can reduce the error of a standard continuum model from 50 to 2 kcal mol −1 . Results from pure cluster, pure continuum (several versions including semiempirical ones), and semicontinuum modeling are each presented and discussed. We recommend use of 3 waters around hydronium and 4 waters around hydroxide with standard continua whenever these ions are involved in reaction. To the possible surprise of some, time‐consuming molecular‐dynamics simulations are not needed to reproduce this problematic energy.
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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 | 0.000 | 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 | 0.000 | 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".