Efficient Deep Blue Pt(II) Emitters for OLEDs and Push-Pull Boron Functionalized Isomers
Bibliographic record
Abstract
This thesis describes the development of two distinct types of luminescent materials and the exploration of their photophysical properties. The first part of the thesis focuses on the synthesis of four new deep-blue phosphorescent Pt(II) compounds by introducing side alkyl chains of different length to two reported Pt(II) compounds with tetradentate and macrocyclic chelate ligands, respectively. The employment of a new synthetic pathway leads to higher yield of the products and shorter reaction time. The modified Pt(II) compounds possess improved solubility in organic solvents, similar photophysical properties, and better performance as the deep-blue electrophosphorescent emitters of OLEDs, compared to the corresponding original Pt(II) compounds. In second part of the thesis, a series of fluorescent indolizino[6,5,4,3-def]phenanthridine derivatives were produced by 1,3-dipolar cycloaddition reactions between a new azomethine ylide and eight selected alkynes. All the BPhMes2-functionalized compounds are found to exhibit charge-transfer (CT) fluorescence, while the others exhibit π to π* transitions. Among them, the three pairs of push-pull regioisomers that are formed by reactions with BPhMes2-functionalized asymmetrical internal alkynes are worthy of most attention. They possess distinct electronic and photophysical properties and some of which show rare and interesting temperature “turn-on” fluorescence.
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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) | 0.002 | 0.001 |
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".