Optimization of Semiconductor Quantum Dots for Luminescent Solar Concentrators: Minimizing Reabsorption Losses
Bibliographic record
Abstract
We investigate theoretically dependence of the reabsorption in semiconductor quantum dots (QDs) on their geometric and electron parameters, namely the radius r̅, its dispersion Δr̅ and bulk semiconductor band gap E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">g0</sub> . QDs are promising as luminophores in luminescence solar concentrators (LSCs). The photo-luminescence (PL) process in QDs is influenced by the reabsorption. To understand how to minimize the detrimental reabsorption losses, we considered six semiconductors, typically used to fabricate QDs, with a wide range of their bulk bandgaps: CdS (E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">g0</sub> = 2.42 eV), CdSe (E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">g0</sub> = 1.67 eV), CdTe (E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">g0</sub> = 1.5 eV), InP (E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">g0</sub> = 1.27 eV), InAs (E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">g0</sub> = 0.36 eV), and PbSe (E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">g0</sub> = 0.27 eV). We prove that by adjusting the QD radius r̅ and dispersion Δr̅ , it is possible to optimize nanocrystal dimensions in order to minimize the reabsorption. It was shown that for the semiconductor bulk band gap in the range between 1.27 eV to 2.42 eV the optimum QD size and dispersion can always be chosen, at which the reabsorption is below the total experimental error of the measured normalized both absorption coefficient and luminescence intensity. Further reduction of Eg0, however, increases the reabsorption at any values of r̅ and Δr̅ : for instance, for PbSe based QD of 1 nm radius and its 1% dispersion, the reabsorption reaches 54%. We estimate the fragment of the solar spectrum, from which the photons, involved in the luminescence processes, originate. This is important for stacked LSCs application.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 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".