Dye-sensitized solar cells based on anatase- and brookite-TiO<sub>2</sub>: enhancing performance through optimization of phase composition, morphology and device architecture
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Herein, we demonstrate an optimization of dye-sensitized solar cells (DSSCs) through the development of single-layer and double-layer configurations. Focusing on the incorporation of brookite and anatase phases in varying ratios, the study aims to determine the optimal composition for enhanced photovoltaic performance. The active layer, composed of anatase- and brookite-TiO 2 nanoparticles, is further modified with a scattering layer comprising a mixture of anatase nanoparticles and brookite-TiO 2 in the form of nanocube or rice-like particles. The synthesis of TiO 2 nanostructures with various morphologies and phase compositions and their subsequent application in single-layer and double-layer DSSCs are presented. The results highlight the superior light-harvesting capabilities achieved through the strategic incorporation of brookite phase into the anatase phase, emphasizing the importance of optimizing the anatase: brookite ratio. The single-layer DSSCs exhibit a peak efficiency of 8.73%, achieved with a composition of 30 wt.% brookite and 70 wt.% anatase at a thickness of 15 μ ms. In the context of double-layer DSSCs, the combined optimization of the active layer composition, scattering layer morphology, and utilization of anatase nanoparticles leads to a remarkable efficiency of 9.18%. These findings underscore the critical role of composition and morphology in enhancing the performance of DSSCs, showcasing the potential for brookite-based DSSCs in solar energy conversion.
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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 | 0.001 |
| 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 it