Stimuli-Responsive Thermally Activated Delayed Fluorescence in Polymer Nanoparticles and Thin Films: Applications in Chemical Sensing and Imaging
Bibliographic record
Abstract
Though molecules exhibiting thermally activated delayed fluorescence (TADF) have seen extensive development in organic light-emitting diodes, their incorporation into polymer nanomaterials and thin films has led to a range of applications in sensing and imaging probes. Triplet quenching can be used to probe oxygen concentration, and the reverse intersystem crossing mechanism which gives rise to TADF can also be used to measure temperature. Moreover, the long emission lifetimes of TADF materials allows for noise reduction in time-gated microscopy, making these compounds ideal for time-resolved fluorescence imaging (TRFI). A polymer matrix enables control over energy transfer between molecules, and can be used to modulate TADF behavior, solubility, biocompatibility, or desirable mechanical properties. Additionally, a polymer's oxygen permeability can be tuned to suit imaging applications in a range of media. Here we review the applications of polymer nanoparticles and films exhibiting TADF in sensing and imaging, demonstrating that this class of materials has great potential beyond electroluminescent devices still waiting to be explored.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".