Exploring Structure-Property Relationships in a Family of Ferrocene-Containing, Triphenylamine-Based Hybrid Organic Dyes
Bibliographic record
Abstract
In this work, a new family of triphenylamine-based dyes equipped with ferrocene (Fc)-containing donors have been synthesized, characterized, and studied within dye-sensitized solar cells (DSSC). With the objective of designing a redox-robust iron-containing dye that effectively sensitizes titania, a family of five structurally related dyes containing ferrocene were prepared. The physicochemical properties of all dyestuffs were studied using UV-Vis and electrochemical measurements. Different cross-coupling strategies resulted in the ability to modestly tune the Fc/Fc+ redox potentials of the dye. Despite the Fc-containing dyes having optoelectronic properties consistent with the non-ferrocene parent dye, the performance of the dyes in devices was dismal and decreased with the number of appended ferrocenes. While this finding was consistent with previous attempts to explore Fc-TPA DSSC dyes, our spectroelectrochemical data supports the hypothesis that the ferrocene component of the dye is oxidized by the electrolyte, ultimately decreasing the dye’s ability to be a suitable sensitizer. While these dyes are not suitable for DSSC applications, they might find applications in other photo-induced integrated devices where charge recombination is minimal.
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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".