Solvation of formic acid and proton transfer in hydrated clusters
Bibliographic record
Abstract
In this paper we report detailed theoretical studies of formic acid–water clusters using a Gaussian implementation of Kohn–Sham density functional theory (DFT). Some MP2 calculations were made when necessary to make comparison. The newly developed Laplacian-dependent (LAP) functionals are extensively used although calculations with other traditional gradient-corrected functionals were also made for comparison. To assess our techniques we studied first the formic acid dimer. Good results for structures, vibrational frequencies and proton transfer barrier heights were achieved by the LAP functionals in contrary to other DFT methods, which usually give extremely low barrier heights. We obtained optimized structures of the formic acid–water clusters with up to 4 waters with many possible minimum energy states. The vibrational frequencies, successive hydration energy as well as the corresponding enthalpy were calculated. The interaction energy between formic acid and water was found to be larger than that of water–water. Ring-type structures are among the lowest in energy. Transition states were located for formic acid–water with various solvation patterns to study the effect of hydration on the proton transfer barrier. The transition state structures are of two fundamental types, i.e., a formic acid anion bound to H3O+- and H5O2+-centered structures, respectively. The proton transfer barrier is reduced by proper solvation of the transition states, notably to full and proper solvation of the hydrated proton units.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".