Triplet–Triplet Annihilation Upconversion from Red to Blue Light Using a TADF Sensitizer Based Polymer
Bibliographic record
Abstract
Molecules capable of thermally activated delayed fluorescence (TADF) can exhibit triplet lifetimes on the order of μs-ms as well as low energy losses in the intersystem crossing (ISC) process. As a result, they have great potential to be used as sensitizers in triplet-triplet annihilation upconversion (TTA-UC) systems with high anti-Stokes shifts, replacing traditional phosphorescent sensitizers. In this study, we employ a red-absorbing boron difluoride curcuminoid-based TADF molecule as the sensitizer and a 9,10-diphenylanthracene derivative as the annihilator. We polymerize them to synthesize a polymer-based red-to-blue TTA-UC system with an anti-Stokes shift of up to 182 nm (0.9 eV) and an upconversion photoluminescence quantum yield (PLQY) of 0.77%. To our knowledge, this is the first report of a TTA-UC polymer containing a TADF photosensitizer. The upconversion properties were investigated through power-dependent experiments and photoluminescence decay measurements. This work provides a more detailed understanding of TTA-UC polymers, highlights the strength of TADF sensitizers in improving anti-Stokes shifts in TTA-UC systems, and demonstrates the feasibility of building polymer-based upconversion systems. This development will expand the application of purely organic TTA-UC.
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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".