Enhancement of optical properties of poly (9,9′-di-n-octylfluorenyl-2,7-diyl) in conjugated polymer/TiO<sub>2</sub> nanocomposites
Bibliographic record
Abstract
The influence of colloidal TiO2 nanoparticle contents on the optical properties of poly (9,9′-di-n-octylfluorenyl-2,7-diyl) conjugated polymer (PFO) has been investigated. The solution blending method was used to prepare homogenous PFO/TiO2 nanocomposite. The nanocomposite films were prepared on glass substrates using the spin-coating technique. The films were divided into two groups, the first was left to dry at room temperature while the second was heat-treated at 120 °C for 1 h. Absorption and emission spectra showed that the PFO existed in α- and β-phases morphology having monomeric, excimeric, and double excimeric states. In addition, both spectra revealed that TiO2 contents and heat treatment temperature extended the conjugation length of PFO. Finally, emission spectra for both cases exhibited decreasing in the line width of zero-phonon emission spectra and increasing in the vibronic splitting energy, upon increment of the TiO2, led to a significant increase in π-electron delocalization and lower degree in chain disorder.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".