Reabsorption Losses in Luminescent Solar Concentrators: Effect of the Band Gap of Semiconductor Quantum Dots, their Size and Dispersion
Bibliographic record
Abstract
We investigate the effect of semiconductor quantum dots (QDs) radius r and its dispersion r on the re absorption during a luminescence process. QDs are promising as chromophores in luminescence solar concentrators (LSCs). To minimize detrimental reabsorption losses, six semiconduc tors, typically used to fabricate QDs, with a wide range of the bulk bandgaps Eg0 have been considered: CdS (Eg0 = 2.42 eV), CdSe (Eg0 = 1.67 eV), CdTe (Eg0 = 1.5 eV), InP (Eg0 = 1.27 eV), InAs (Eg0 = 0.355 eV), and PbSe (Eg0 = 0.27 eV). We prove that by adjusting the QD radius r and dispersion r, it is possible to optimize nanocrystal dimensions to minimize the reabsorption. It was shown that for the semiconductor bulk band gap range between 2.42 eV to 1.27 eV there is always the optimum QD size and its dispersion, at which the reabsorption is below the total experimental error of the measured normal ized both absorption coefficient and luminescence intensity. Further reduction of Eg0 increases the reabsorption at any val ues of r and r: for instance, for PbSe based QD with Eg0 = 0.27 eV, 1 nm mean radius and its 1% dispersion, the reabsorp tion reaches 54%. We estimate the width of the part of the solar spectrum, from which the photons contribute to the lumines cence processes. This is important for several LSCs, stalked on top of each other.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".