Effects of external electric fields on double proton transfer kinetics in the formic acid dimer
Bibliographic record
Abstract
Molecules can be exposed to strong local electric fields of the order of 10(8)-10(10) V m(-1) in the biological milieu. The effects of such fields on the rate constant (k) of a model reaction, the double-proton transfer reaction in the formic acid dimer (FAD), are investigated. The barrier heights and shapes are calculated in the absence and presence of several static homogenous external fields ranging from 5.14 × 10(8) to 5.14 × 10(9) V m(-1) using density functional theory (DFT/B3LYP) and second order Møller-Plesset perturbation theory (MP2) in conjunction with the 6-311++G(d,p) Pople basis set. Conventional transition state theory (CTST) followed by Wigner tunneling correction is then applied to estimate the rate constants at 25 °C. It is found that electric fields parallel to the long axis of the dimer (the line joining the two carbon atoms) lower the uncorrected barrier height, and hence increase the raw k. These fields also flatten the potential energy surface near the transition state region and, hence, decrease the multiplicative tunneling correction factor. The net result of these two opposing effects is that fields increase k(corrected) by a factor of ca. 3-4 (DFT-MP2, respectively) compared to the field-free k. Field strengths of ∼3 × 10(9) V m(-1) are found to be sufficient to double the tunneling-corrected double proton transfer rate constant at 25 °C. Field strengths of similar orders of magnitudes are encountered in the scanning tunneling microscope (STM), in the microenvironment of a DNA base-pair, in an enzyme active site, and in intense laser radiation fields. It is shown that the net (tunneling corrected) effect of the field on k can be closely fitted to an exponential relationship of the form k = aexp(bE), where a and b are constants and E the electric field strength.
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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 | 0.000 |
| 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) | 0.001 | 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".