Efficient Room-Temperature Phosphorescence of Covalent Organic Frameworks through Covalent Halogen Doping
Bibliographic record
Abstract
Organic room-temperature phosphorescence, a spin-forbidden radiative process, has emerged as an interesting but rare phenomenon with multiple potential applications in optoelectronic devices, biosensing, and anticounterfeiting. Covalent organic frameworks (COFs) with accessible nanoscale porosity and precisely engineered topology can offer unique benefits in the design of phosphorescent materials, which are presently unexplored. Here, we report an original approach of covalent doping, whereby a bi-component COF is synthesized by copolymerization of halogenated and unsubstituted phenyldiboronic acids, allowing for random distribution of functionalized units at varying ratios, yielding highly phosphorescent COFs. Such controlled halogen doping enhances the intersystem crossing while minimizing the triplet-triplet annihilation by diluting the phosphors. The rigidity of the COF suppresses vibrational relaxation and allows high phosphorescence quantum yield (Φ(phos) <29%) at room-temperature. The permanent porosity of the COFs and the combination of the singlet and triplet emitting channels enable a highly efficient COF-based oxygen sensor, with an ultra-wide dynamic detection range, ~ 10^3…10^-5 torr of partial oxygen pressure.
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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".