Performance Comparison of Cost Efficient Natural Dye Sensitized Solar Cell
Bibliographic record
Abstract
Dye-sensitized solar cells (DSSCs) enticed the attention in photovoltaic design due to their unique features of ease of fabrication, low-cost materials, tunable color, and flexibility. In this work, we studied the performance of a low cost dye-sensitized solar cell structure with several natural dyes as a sensitizer. Titanium dioxide (TiO2) was used as the semiconducting layer. The TiO2 film was fabricated on Florine doped Tin Oxide (FTO) glass plate and was annealed and sintered for an hour at 450°C temperature to create a mesoporous layer. To reduce the manufacturing cost, we used Carbon black instead of Platinum (Pt) as a counter electrode. Carbon black provides excellent stability and shows high catalytic ability along with its low cost as the counter electrode in the DSSCs. Eight different dyes have been extracted and purified by Silica gel column chromatography to use in the DSSCs. UV-Visible absorption spectroscopy and fluorescence spectroscopy has been done to measure the absorbance coefficient and fluorescence coefficient of each of the cells. The cells with an additional peak in the fluorescence spectra showed much better electrical performance compared with others. Among the fabricated DSSCs, the Curcuma longa based DSSC gives the highest open-circuit voltage of 0.5959 V and short circuit current density of 1.06 mA/cm2. The study also indicates that the dyes with a peak at 380 nm to 400 nm wavelength at fluorescence spectrum has better photovoltaic performance rather with a moderate absorbance spectrum.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".