Large area stimulated emission luminescent solar concentrators modelled using detailed balance consistent rate equations
Bibliographic record
Abstract
Stimulated emission luminescent solar concentrators (SELSCs) have the potential to reduce escape cone losses in luminescent solar concentrators (LSCs). However, a functional SELSC is yet to be demonstrated. Previous numerical studies and detailed balance limits provide guidance, but they also contradict and likely overestimate performance and underestimate requirements. In this work, we introduce a rate-equation model with inversion requirements compatible with detailed balance limits and apply this model to the numerical modelling of window-sized SELSCs. We find that the optimal pump photon energy for both LSCs and SELSCs is 1.35 eV and the potential improvement of SELSCs over LSCs is found to be 19.3%. The efficiencies found are much lower than those specified in previous work due to the increase in Stokes shift required for a highly luminescent material. We also find that SELSCs are more attractive at higher matrix losses, that emission linewidths <0.05 eV are desirable, and that SELSC devices can potentially achieve performance equal to LSCs at low illumination levels and simultaneously exceed it by up to 16.5% at 1-sun illumination.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".