Relaxation Pathways of Photoexcited Iodide–Methanol Clusters: A Computational Investigation
Bibliographic record
Abstract
Upon photoexcitation of iodide-methanol clusters, I(-)(CH3OH)n, to a charge-transfer-to-solvent (CTTS) excited state, extensive relaxation was found to occur, accompanied by a convoluted modulation of the stability of the excited electron, which ultimately decreases substantially. In order to develop a molecular-level understanding of the relaxation processes of CTTS excited I(-)(CH3OH)n, high-level quantum chemical calculations are first used to investigate the ground, excited, and ionized states of I(-)(CH3OH)n (n = 2). Because of the relatively small size of I(-)(CH3OH)2, it was possible to characterize the contributions of solvent-solvent interactions to the stability of the CTTS excited cluster relative to dissociation into methanol, iodine, and a free electron, which exhibits a substantial dependence on the cluster geometric configuration. Ab initio molecular dynamics simulations of CTTS excited I(-)(CH3OH)3 are then performed to shed some light onto the nature of the relaxation pathways involved in the modulation of the stability of the excited electron in larger clusters. Simulation results suggest that separation of I and (CH3OH)3(-) accompanied by solvent reorganization in the latter can initially stabilize the excited electron, while gradual cluster fragmentation to I, (CH3OH)2(-), and CH3OH ultimately destabilizes it. This work shows, for the first time, that the inability of small CTTS excited I(-)(CH3OH)n to retain a solvated electron may be attributed to the limited hydrogen-bonding capacity of CH3OH, which increases the propensity for fragmentation to smaller clusters with lower excess-electron binding energies, and highlights the critical role of intricate molecular interactions in the electron solvation process.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".