Unveiling the intermediate hydrated proton in water through vibrational analysis on the 1750 cm−1 signature
Bibliographic record
Abstract
Hydration of proton is the key to understand the acid-base chemistry and biochemical processes, for which the Zundel and Eigen cations have been recognized as the foundation. However, their dominance remains contentious due to the challenge of attributing the infrared signature at ~1750 cm−1, stemming from the theoretical dilemma of balancing structural diversity and solvent fluctuations. Herein, we circumvent this obstacle by devising an integrated approach for computing frequency-specific vibrational vectors via inverse Fourier transform of the vibrational density of states. When applied to aqueous acid, it unveils an additional “Intermediate” configuration, linked to the aforementioned spectral signature, which exhibits a higher population (44%) and longer lifetime (51 fs), compared to Zundel-like (28%, 25 fs) and Eigen-like (28%, 36 fs), benefitting from the local electric field induced by surrounding solvent molecules. The dominant hydrated proton solvation structure remains debated due to ambiguous 1750 cm−1 IR band assignment. Here, authors assign this signature by unveiling a distinct Intermediate configuration with the devised FFT-based vibrational analysis.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".