Kinetic analysis of the temperature dependence of PbSe colloidal quantum dot photoluminescence: Effects of synthesis process and oxygen exposure
Bibliographic record
Abstract
A kinetic model is derived and used to analyze recently published works and new data on the temperature dependence of the spectrally integrated photoluminescence (PL) from thick-film formulations of PbSe colloidal quantum dots (QDs), with particular attention to the effects of air exposure. The model assumes that the excitons thermalize within a ground-state manifold of states and treats the distribution of radiative and nonradiative decay rates within the distribution as generally as possible, while using a minimal number of free parameters. By adjusting the parameters of the model, good fits are obtained for the wide range of integrated PL behaviors reported in [J. Phys. Chem. Lett. 2, 889 (2011); ACS Nano 6, 5498 (2012); Phys. Rev. B 82, 165435 (2010)] and the new data presented in this manuscript. By comparing the extracted parameters we deduce the following: (i) All of the samples in the first two references emit from two distinct clusters of states separated by an energy of 55 to 80 meV regardless of air exposure, while there is only one cluster of emissive states that contributes to the emission reported in the third reference. (ii) In the absence of intentional air exposure, the nonradiative decay from all samples can be described by a single Arrhenius-like process. (iii) Although air-exposure effects are reversible in some samples and irreversible in others, the changes in integrated PL behavior brought about by air-exposure forces the introduction of a common, low-activation-energy nonradiative pathway in all cases. (iv) The low-lying emissive cluster of the two-emissive-cluster samples exhibits behavior similar to the single emissive cluster of the other samples. (v) Many hours of air exposure do not trend either the radiative or nonradiative behavior of the dual-emissive-cluster samples towards the behavior of the single-emissive-cluster samples.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".