Panchromatic Enhancement of Light-Harvesting Efficiency in Dye-Sensitized Solar Cells Using Thermally Annealed Au@SiO<sub>2</sub> Triangular Nanoprisms
Bibliographic record
Abstract
Plasmonic enhancement is an attractive method for improving the efficiency of dye-sensitized solar cells (DSSCs). Plasmonic materials with sharp features, such as triangular metal nanoparticles, show stronger plasmonic effects than their spherical analogues; however, these nanoparticles are also often thermally unstable. In this work, we investigated the thermal stability of Au@SiO2 triangular nanoprisms by annealing at different temperatures. Morphological changes were observed at temperatures greater than 250 °C, which resulted in a blue shift of the localized surface plasmon resonance (LSPR). Annealing at 450 °C led to a further blue shift; however, this resulted in better overlap of the LSPR with the absorption spectrum of black dye. By introducing 0.05% (w/w) Au@SiO2 nanoprisms into DSSCs, we were able to achieve a panchromatic enhancement of the light-harvesting efficiency. This led to a 15% increase in the power conversion efficiency from 3.9 ± 0.6% to 4.4 ± 0.4%.
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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".