Antagonistic effects leading to turn-on electrochemiluminescence in thermoresponsive hydrogel films
Bibliographic record
Abstract
centers increases, due to the reduced distance between adjacent redox centers. To generate ECL, cationic and anionic coreactants are employed, which are free to diffuse in the medium. In both cases, the ECL intensity exhibits a remarkable amplification of up to 58-fold at the swell-to-collapse transition, whereas the oxidation current undergoes a steep decrease in the case of the cationic coreactant. Indeed, the diffusion of the coreactant is hindered by the collapse of the film. The fact that ECL emission is enhanced whereas less coreactant radicals are generated is an intriguing observation because it is classically believed that the higher the oxidation rate of the coreactant the stronger the ECL emission. Thanks to the study of such films where antagonistic effects occur, we demonstrate that ECL enhancement is neither correlated with the oxidation efficiency of the coreactant nor with the hydrophilic-hydrophobic transition, but solely due to film shrinking. The decrease of the distance between adjacent redox centers, which favors better electron-transfer processes, is found to be the main parameter governing the ECL enhancement. Finally, it is noteworthy that the present turn-on ECL signal with increasing temperature is unique compared to many thermoresponsive luminescent systems.
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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".