How intermolecular interactions influence electronic absorption spectra: insights from the molecular packing of uracil in condensed phases
Bibliographic record
Abstract
The photoexcitation mechanism in photochemistry and photophysics is a key to understanding the photostability and photoreaction of nucleobases. Using a combination of the generalized energy-based fragmentation (GEBF) and quantum mechanical and molecular mechanical (GEBF-QM/MM) approach and the QM/MM approach, we have investigated the electronic absorption spectra for the π-π* transition of uracil in aqueous solution, amorphous solid, and crystal. Our results indicate that the intermolecular interactions in terms of molecular packing are crucial for the investigation of the absorption spectra of uracil in different environments. There is a large red-shift (relative to uracil in the gas-phase) for uracil in the amorphous phase, which arises from hydrogen-bonding (HB) and close π-π stacking interactions. In contrast, the relatively smaller red-shift of uracil in aqueous solution can be attributed to the cooperative HB and long-range electrostatic and polarization interactions. Due to the HB and weak π-π interactions, the red-shift of the crystal is smaller than that of amorphous uracil. Furthermore, the results suggest that a large system is required to obtain the accurate absorption spectra of solutions, whereas small electrostatically embedded cluster models could be used to obtain the corresponding results for amorphous solids and molecular crystals.
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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".