Charge-Transfer Dynamics of Fluorescent Dye-Sensitized Electrodes under Applied Biases
Bibliographic record
Abstract
The development of dye-sensitized solar cells requires an in-depth understanding of the interfacial charge-transfer dynamics that take place between dye sensitizers and semiconductors. Here, we describe a prototype system to probe these dynamics by monitoring in real time the fluorescence of two organic sensitizers, a perylene and a squaraine, bound to a SnO2 semiconductor thin film as a function of potentiostatic control of the Fermi level. The two different sensitizer fluorophores characterized by vastly different redox potentials undergo similar fluorescence modulation with applied bias, an indication that the density of states of the semiconductor largely influences the charge-transfer dynamics while energetics play a minimal role. We further show that the rate of photodegradation of the perylene sensitizer with applied bias provides a suitable marker to study the rate of charge injection and charge recombination. Taken together, our results demonstrate a suitable platform to visualize and study charge-transfer dynamics on films and constitute a step toward achieving single-molecule resolution in our quest to decipher the static and dynamic heterogeneity of charge-transfer dynamics in dye-sensitized photoanodes.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".