Overcoming Kinetic Limitations of Electron Injection in the Dye Solar Cell via Coadsorption and FRET
Bibliographic record
Abstract
A new, extremely simple concept for the use of energy transfer as a means to the enhancement of light absorption and current generation in the dye solar cell (DSC) is presented. This model study is based upon a carboxy-functionalized 4-aminonaphthalimide dye (carboxy-fluorol) as donor, and (NBu4)2[Ru(dcbpy)2(NCS)2] (N719) as acceptor chromophores. A set of three different devices is assembled containing either exclusively carboxy-fluorol or N719, or a mixture of both. This set of transparent devices is characterized via IV-measurements under AM1.5G and monochromatic illumination and their light-harvesting and external quantum efficiencies (LHE and EQE, respectively) are determined as well. It is shown that the device containing only the donor chromophore has a marginal power conversion efficiency, thus indicating that carboxy-fluorol is a poor sensitizer for the DSC. Cyclovoltametric measurements show that the poor sensitization ability arises from the kinetic inhibition of electron injection into the TiO2 conduction band. Comparing the spectral properties of the DSCs assembled presently, however, demonstrates that light absorbed by carboxy-fluorol is almost quantitatively contributing to the photocurrent if N719 is present as an additional sensitizer. In this case, N719 acts as a catalyst for the sensitization of TiO2 by carboxy-fluorol in addition to being a photosensitizer. Evaluation of the maximum output power under blue illumination shows that the introduction of an energy-donor moiety via coadsorption, leads to a significant increase in the monochromatic maximum output power. This result demonstrates that energy transfer between coadsorbed chromophores could be useful for the generation of current in dye-sensitized solar cells.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".