Exploring the Effects of Bay Position Chlorination on the Emissive Properties of Chloro-(Chloro)n-Boron Subnaphthalocyanines for Light Emission.
Bibliographic record
Abstract
Abstract: It has been previously found that through an established synthesis of the macrocycle boron subnaphthalocyanine (BsubNc) that random bay-position chlorination occurs and results in a mixed alloyed composition that cannot be separated; called chloro-(chloro n )-boron subnaphthalocyanines (Cl-Cl n BsubNcs). Through modifications of the synthetic method, amounts of the average bay-position chlorination can be varied. Cl-Cl n BsubNcs are fluorescent and therefore here we explore the effect of the amount of bay-position chlorination on the photoluminescent and electroluminescent properties of Cl-Cl n BsubNcs. Distinct from previous reports detailing the positive impact of higher average bay-position chlorination, we find that the photophysical processes important to OLEDs improve with lower average bay-position chlorination. A higher degree of bay-position chlorine shows higher nonradiative recombination rates, lower photoluminescence quantum efficiencies and a basic OLEDs exhibits a greater host emission fraction, implying less effective energy transfer. These results advance the consideration of subnaphthalocyanines for light-emitting and optoelectronic applications.
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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".