Thermally Activated Dual‐Room‐Temperature Phosphorescence: Triplet Up‐Converted Anti‐Kasha in Dendrimers Enabled by Rigid Matrix Stabilization
Bibliographic record
Abstract
ABSTRACT Room‐temperature phosphorescence (RTP) materials are a significant research field for anti‐counterfeiting, bioimaging, and optoelectronic devices, but anti‐Kasha RTP still lacks clear molecular design strategies, and conventional rigid polymer matrices fail to break Kasha's rule. To address these issues, this work proposes an acceptor dendronization strategy to synthesize the dendrimer emitter dTC‐BPSAF. Carbazole dendrons regulate triplet hybridization, enabling dTC‐BPSAF to form near‐degenerate lowest triplet ( T 1 ) and high‐lying triplet ( T 2 ) states with hybrid local‐charge transfer (HLCT) character and large spin‐orbit coupling. Integrating dTC‐BPSAF into rigid polymers further stabilizes T 2 by suppressing non‐radiative decay. Temperature‐dependent time‐resolved phosphorescence spectra and transient absorption spectra confirm that rigid matrix‐based films exhibit thermally activated endothermic T 1 → T 2 up‐conversion and dual‐band anti‐Kasha RTP. In contrast, a moderately rigid polymer matrix shows weak T 2 emission, while a soft polymer matrix only produces T 1 emission. This study establishes a dendrimer‐matrix synergy strategy combining molecular‐level triplet engineering, providing a generalizable approach for efficient anti‐Kasha RTP materials and new avenues for advanced photonics.
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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".