Luminescence characteristics of PPV-yttrium oxide nanocomposite layers for photonic devices
Bibliographic record
Abstract
Summary form only given. The luminescence characteristics of polymer based optoelectronic devices can be modified and improved by embedding crystalline nanoparticles within the polymer matrix. There exist a few experimental indications of the influence of dielectric inclusions in conducting polymers on photoelectric properties without revealing a clear physical picture. We provide herein a detailed analysis of this problem for the particular system of Y/sub 2/O/sub 3/ inclusions in a PPV matrix. Contrary to semiconductor quantum dots, dielectric nanocrystals with large band gap play the role of antidots -potential bumps for carriers. Experiment reveals the following modification of PPV luminescence spectrum caused by dielectric inclusions: the luminescence maximum shifts to a shorter wavelength of approximately 460 nm; the maximum becomes wider; the new spectrum no longer contains distinct vibronic structure; the luminescence kinetics is non-exponential but contains a noticeable component with /spl tau/ = 0.4 ns typical for pure PPV. Electroluminescence spectra are also shown for pure PPV and PPV/Y/sub 2/O/sub 3/ nanocomposites at the same injected current density. In addition to the spectral and time-resolved features described above in the context of photoluminescence, the composite structures demonstrate a considerable increase in the luminescence intensity for a given injected current density. The nonuniform current density in the composites creates regions of high local electric fields with intense light emission. The results obtained demonstrate that dielectric nanocrystals can essentially modify luminescent properties of conducting polymers, offering one avenue to improved efficiency and spectral tailoring for applications in light-emitting devices.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".