Investigation of structural and optical properties of CdSe quantum dots in glass matrices for photovoltaic application
Bibliographic record
Abstract
In this work preparation methods for spin-cast uniform layers of cadmium selenide (CdSe) quantum dots (QDs) with specific thickness and subsequent film treatment methodologies are presented. Dimensional and lattice structures as well as the homogeneity of the nanocrystals distribution over the film thickness are studied through high resolution transmission electron microscopy (HRTEM). Ultra violet (UV) spectrometric and spectrofluorometric measurements are performed to obtain absorption-emission spectrum of the provided films. The results show that the absorption is sensitive to size of the nanocrystals and the refractive index of the medium in which they are embedded. Refractive index of the thin films is extracted using spectroscopic Ellipsometery. Results are presented on the incorporation of the CdSe in glass matrices and a graded index structure is optimized for embedment of nanocrystals. The photon conversion ability of the fabricated layer has been verified. Effect of size and glass matrix contraction on the Raman shifts of CdSe quantum dots has been also investigated. The results from such characterization methods are vital in knowing the properties of the nanocrystals, as well as in optimizing a converter layer for solar cell applications.
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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) | 0.001 | 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".