Integrating photovoltaic cells into decorative architectural glass using traditonal glasspainting techniques and fluorescent dyes
Bibliographic record
Abstract
Photovoltaic (PV) cells can be integrated into decorative glass, providing a showcase for this renewable technology, whilst assisting in the creation of sustainable architecture through generation of electricity from the building surface. However, traditional, opaque, square, crystalline-silicon solar cells contrast strongly with their surroundings when incorporated into translucent, coloured glazing. Methods of blending PV cells into their surroundings were developed, using traditional glass painting techniques. A design was created in which opaque paint was applied to the areas of glass around underlying PV cells. Translucent, platinum paint was used on the glass behind the PV cells. This covered the grey cell backs whilst reflecting light and movement. The platinum paint was shown to cause a slight increase in power produced by PV cells placed above it. To add colour, very small amounts of Lumogen F dye (BASF) were incorporated into a silicone encapsulant (Dow Corning, Sylgard 184), which was then used to hold PV cells in place between sheets of painted glass. Lumogen dyes selectively absorb and emit light, giving a good balance between colour addition and electricity production from underlying PV cells. When making sufficient quantities of dyed encapsulant for a 600 ? 450 mm test piece, the brightness of the dye colours faded and fluorescence decreased, although some colour was retained. Improvement of the method, including testing of alternative encapsulant materials, is required, to ensure that the dyes continue to fluoresce within the encapsulant. In contrast, the methods of adding opacity variation to glass, through the use of glass painting, are straightforward to develop for use in a wide variety of PV installations. Improvement of these methods opens up a wide variety of architectural glass design opportunities with integrated PV, providing an example of one new medium to make eco-architecture more aesthetically pleasing, whilst generating electricity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".