Temperature Dependence of Förster Thermalization and Population Decay in PbSe Nanocrystals
Bibliographic record
Abstract
Time-resolved photoluminescence spectroscopy is used to quantify the Förster-mediated exciton migration rate and the exciton population decay rate in drop-cast solid emulsions of PbSe colloidal nanocrystals emitting near 1.5 μm from 77 to 300 K. For both unimodal and bimodal emulsions, at a fixed temperature in a given sample the measured time constants that characterize the fast transient decay (blue side of the spectrum) and buildup (red side of the spectrum) vary considerably with emission wavelength, but the average fast time constant, ∼25 ns, varies little (i.e., within <25%) with temperature from 77 to 300 K. Over the same temperature range, the exciton population lifetime, ascribed to nonradiative decay, decreases by ∼5 times but is always longer than the Förster time constant. The increase of the Förster-mediated efficacy of exciton redistribution at low temperatures before they decay is therefore almost all due to the variation of the nonradiative decay rate. By analyzing the temporally resolved and steady-state emission spectra, it is noted that the time required for the exciton population to equilibrate is nonexponential and considerably longer (∼150 ns) than the rapid decay and buildup time constants extracted from the decay curves at fixed wavelengths.
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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) | 0.000 | 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".