Exciton Trapping and Recombination in Type II CdSe/CdTe Nanorod Heterostructures
Bibliographic record
Abstract
Trap states are known to influence the excited-state dynamics in nanocrystalline semiconductors, but the nature and magnitude of the exciton−trap interaction is poorly understood owing to the relative optical inactivity of carrier traps and the heterogeneity of trap-state distributions. Nanocrystal time-resolved fluorescence measurements are typically complex traces that contain information about both radiative and nonradiative processes. The interpretation of these fluorescence transients is nontrivial, and typical multi- or stretched exponential analyses yield little specific photophysical information. Here, we develop a stochastic model of nanocrystal exciton and trap-state dynamics, which is used to describe coupled excitonic and charge-transfer photoluminescence from a series of CdSe/CdTe collinear quantum rod heterostructures. In this way we evaluate the photoexcitation dynamics of core nanocrystal states: the CdTe exciton and CdSe(e - )−CdTe(h + ) charge-separated state and states associated with one or more trapped charge carriers. We describe the overwhelming influence of traps on the population dynamics and resolve population changes caused by the addition of a surface passivating ligand. Additionally, the long radiative lifetimes of the charge-separated state are reported.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".