Exploiting Mixed Valence Charge Transfer for Electrochromic and Electrofluorochromic Use
Bibliographic record
Abstract
Abstract An asymmetric mixed valence fluorophore with two different electron rich termini was investigated as a dual‐role active material for electrochromism and electrofluorochromism. The fluorescence quantum yield (Φfl) and emission wavelength of the fluorophore were dependent on solvent polarity. The quantum yield of the material in an electrolyte gel, on a glass substrate and in a device was 40 %, 20 % and 13 % respectively. The fluorophore further underwent two near‐simultaneous electrochemical oxidations. The first oxidation resulted in a 1000 nm red shift in the absorption to broadly absorb in the NIR, corresponding to the intervalence charge transfer (IVCT). Whereas the second oxidation led to a perceived green color at 715 nm with the extinction of the NIR absorbing IVCT. Owing to the dissymmetry of the fluorophore along with its two unique oxidation sites, the IVCT gives rise to a mixed valence transfer charge (MVCT). The coloration efficiency of the fluorophore in both solution and a device was 1433 and 200 cm2 C−1, respectively. The fluorescence intensity could be reversibly modulated electrochemically. The photoemission intensity of the fluorophore was modulated with applied potential in an operating electrochromic/electrofluorochromic device. Both the dual electrochromic and the electrofluorochromic behavior of the fluorophore were demonstrated.
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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 | 0.001 |
| 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".