Highly Efficient Aggregation-Induced Electrochemiluminescence of Polyfluorene Derivative Nanoparticles Containing Tetraphenylethylene
Bibliographic record
Abstract
The aggregation-induced electrochemiluminescence (AIECL) of polyfluorene derivative nanoparticles containing tetraphenylethylene (TPE) in aqueous media is reported in this work. The TPE unit limits the intramolecular free rotation of phenyl rings, as well as the π-π stacking interactions of molecules, which significantly enhances ECL signal of the polyfluorene nanoparticles. With co-reactants of tri-n-propylamine (TPrA) and S 2 O 8 2− , the copolymer nanoparticles show visualized ECL emissions at both positive and negative potentials. The ECL efficiency of copolymer nanoparticles in solid state is 163% compared with that of standard ECL species, Ru(bpy) 3 2+ . And at negative potential, the ECL intensity of copolymer nanoparticles is even stronger with 6.5 times compared with that at positive potential. The ECL generation mechanisms are analyzed detailed by annihilation and co-reactant route transient ECL test (millisecond scale). This work provides a reference for the organic structure design for AIECL and shows promising potential in luminescent device and biological applications.
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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) | 0.000 | 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".