ZnO Nanostructures for Dye‐Sensitized Solar Cells Using the TEMPO<sup>+</sup>/TEMPO Redox Mediator and Ruthenium(II) Photosensitizers with 1,2,3‐Triazole‐Derived Ligands
Bibliographic record
Abstract
Abstract A series of thiocyanate‐free bis(tridentate) ruthenium(II) complexes incorporating 1,2,3‐triazole‐derived NNN‐, NCN‐, and CNC‐coordinating ligands has been employed for sensitizing ZnO photoanodes for dye‐sensitized solar cells (DSSCs). Additionally, the first use of the TEMPO+/TEMPO (2,2,6,6‐tetramethyl‐piperidine‐1‐oxyl) redox mediator as a surrogate for the I3−/I− redox couple in ZnO nanostructured DSSCs is presented. Compared with I3−/I−‐based electrolytes, shorter charge lifetimes and diffusion lengths were determined for the TEMPO+/TEMPO‐based electrolyte. Nonetheless, similar power conversion efficiencies (PCEs) were achieved with both electrolytes for the RuNCN and RuCNC complexes, whereas higher PCEs are enabled by the iodine‐free electrolyte in case of RuNNN. The combination of the molecular sensitizers and the TEMPO‐based electrolyte exhibits relatively high external quantum efficiency (EQE) and promising PCEs, ranging from 4.48 to 1.47 %, which are—in part—comparable to that of ZnO‐DSSCs with the benchmark N749 black dye. The TEMPO‐based electrolyte also exhibits less absorption compared with its I3−/I− counterpart, a favorable feature for enhancing the light harvesting ability of the photoanode. Furthermore, the results show the effect of the dye‐sensitization procedure on the PCE values: The use of ethanol as the solvent compared with methanol increases the DSSC's efficiency, which is attributed to improved chemisorption of the sensitizer onto the ZnO surface.
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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".