A computational study of ultrafast acid dissociation and acid-base neutralization reactions. I. The model
Bibliographic record
Abstract
Ultrafast, time-resolved investigations of acid-base neutralization reactions have recently been performed using systems containing the photoacid 8-hydroxypyrene-1,3,6-trisulfonic acid trisodium salt (HPTS) and various Bronsted bases. Two conflicting neutralization mechanisms have been formulated by Mohammed et al. [Science 310, 83 (2005)] and Siwick et al. [J. Am. Chem. Soc. 129, 13412 (2007)] for the same acid-base system. Herein an ab initio molecular dynamics based computational model is formulated, which is able to investigate the validity of the proposed mechanisms in the general context of ground-state acid-base neutralization reactions. Our approach consists of using 2,4,6-tricyanophenol (exp. pKa congruent with 1) as a model for excited-state HPTS( *) (pKa congruent with 1.4) and carboxylate ions for the accepting base. We employ our recently proposed dipole-field/quantum mechanics (QM) treatment [P. Maurer and R. Iftimie, J. Chem. Phys. 132, 074112 (2010)] of the proton donor and acceptor molecules. This approach allows one to tune the free energy of neutralization to any desired value as well as model initial nonequilibrium hydration effects caused by a sudden increase in acidity, making it possible to achieve a more realistic comparison with experimental data than could be obtained via a full-QM treatment of the entire system. It is demonstrated that the dipole-field/QM model reproduces correctly key properties of the 2,4,6-tricyanophenol acid molecule including gas-phase proton dissociation energies and dipole moments, and condensed-phase hydration structure and pKa values.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".