Selectively Harvesting Nonvisible Photons in Hybrid Solar Lighting Systems for Power Generation in Buildings
Bibliographic record
Abstract
Hybrid solar lighting (HSL) systems reduce building energy consumption by supplementing conventional indoor lighting with solar light that is channeled into the building using optic cables. Herein, it is demonstrated that HSL systems can be improved by harnessing the nonvisible portion of sunlight to generate electric power. HSL systems are integrated with parabolic‐ and elliptic‐shaped solar spectrum splitters (SSSs) that partition collimated solar radiation into its visible and nonvisible parts. In the proposed SSS, luminescent materials and a bifacial photovoltaic cell capture and convert light energy in the spectral ranges from 280 to 435 nm and 675 to 900 nm into electricity. The visible light is coupled to a waveguide to be used in indoor lighting systems. The proposed HSL system is analyzed for a 0.2 m2 projected area of solar radiation and the results show that a nonvisible‐light‐to‐electricity conversion efficiency of up to ≈13.4% can be achieved for light entering the SSS. The power generated in the system can be used to power the electrical components of the HSL system and indoor lighting during off‐sun hours.
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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".