Efficient UV Organic Solid‐State Lasers with Ultra‐Short Wavelengths Based on Dispirofluorene‐Indenofluorene Isomers
Bibliographic record
Abstract
Abstract The development of efficient UV organic solid‐state lasers (OSLs) remains a significant challenge, yet it is crucial for enabling advanced photonic technologies. This study investigates two dispirofluorene‐indenofluorene regioisomers, (2,1‐a)‐DSF(tBu) 4 ‐IF ( DSFIF‐syn ) and (1,2‐b)‐DSF(tBu) 4 ‐IF ( DSFIF‐anti ), to elucidate the impact of subtle structural differences on their solid‐state photophysical and lasing properties. Through a combination of experimental techniques and theoretical approaches, including comprehensive optical characterization and molecular dynamics simulations, it is demonstrated that DSFIF‐syn exhibits significantly reduced intermolecular aggregation compared to DSFIF‐anti , resulting in enhanced optical performance in solid‐state thin films. Remarkably, amplified spontaneous emission (ASE) is achieved at a record‐short wavelength of 365 nm with a low threshold of 4.5 µJ cm −2 (5000 W cm − 2 ) in a PMMA blend film. Moreover, distributed feedback (DFB) laser devices incorporating a blend film of DSFIF‐syn dispersed in polystyrene (PS) enabled lasing at an unprecedentedly short wavelength of 358.5 nm, as well as a low lasing threshold of 0.7 µJ cm − 2 (780 W cm − 2 ) at 363.3 nm. These results demonstrate that dispirofluorene‐indenofluorene derivatives are highly promising UV laser dyes, highlighting isomeric control as a valuable molecular design strategy for advancing high‐performance organic lasers.
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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".