Room-temperature exciton coherence and dephasing in two-dimensional nanostructures
Bibliographic record
Abstract
Electronic coherence has attracted considerable attention for its possible role in dynamical processes in molecular systems. However, its detection is challenged by inhomogeneous line broadening and interference with vibrational coherences. In particular, reports of ‘persistent’ coherent exciton superpositions at room temperature remain controversial, as the related transitions give typically shorter optical dephasing times of about 10–20 fs. To rationalize these reported long-lived coherences, several models have been proposed, involving strong correlation in the mechanisms of decoherence or that electronic coherences may be sustained by resonant vibrational modes. Here we report a decisive example of electronic coherence occurring in a chemical system in a ‘warm and wet’ (room-temperature solution) environment, colloidal semiconductor nanoplatelets, where details are not obscured by vibrational coherences nor ensemble dephasing. Comparing the exciton and optical coherence times evidences a partial correlation of fluctuations underlying dephasing and allows us to elucidate decoherence mechanisms occurring in these samples. Evidence for exciton coherence in photosynthetic complexes raises questions about whether quantum processes can play a role in biological environments, which are warm and wet. Cassette et al. now demonstrate long-lived electronic coherence in colloidal nanoplatelets in solution and at room temperature.
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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 | 0.001 |
| 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".