Enhanced Photovoltaic and Optical Properties of Red Cabbage Dye Sensitized with ZnO Nanoparticles for Solar Cell Applications
Bibliographic record
Abstract
In this study, 100 mL of distilled water were used to prepare red cabbage dye solutions at varying concentrations (0.002 g, 0.004 g, and 0.006 g) to investigate how concentration affects optical properties without altering the material's nature.Spectral analysis showed a clear increase in absorption within the visible range (400 nm-700 nm) with higher dye concentrations, indicating strong light-harvesting potential.Subsequently, 1.6 g of zinc oxide (ZnO) nanoparticles were added to each solution.Four solar cells were arranged at the edges of a square basin filled with the dye-ZnO mixtures to evaluate their effect on solar cell efficiency.Results showed a general improvement in efficiency across all concentrations.The highest solar efficiency was recorded at 0.004 g dye with a light concentrator, outperforming the baseline efficiency of 0.6% without it.When epoxy resin was added along with ZnO nanoparticles, the best efficiency shifted to a dye concentration of 0.002 g, suggesting enhanced nanoparticle stability and improved energy transfer.Fluorescence spectra revealed shifts in emission intensity with varying concentrations and ZnO presence, reflecting complex interactions.The dye's quantum yield increased with concentration up to 0.004 g before declining due to self-quenching effects at higher levels.These findings demonstrate that ZnO nanoparticles and epoxy resin synergistically improve the optical and photovoltaic properties of natural red cabbage dye for Solar Applications.
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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 | 0.000 | 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) | 0.000 | 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".