Light-Selective Nanofilms of Quantum Dot-Poly(ethylene-<i>co</i>-vinyl acetate) Synthesized with Supercritical CO<sub>2</sub>
Bibliographic record
Abstract
The synthesis of polymer nanocomposites with incorporated quantum dots (QDs) has been attracting significant interest due to their unique applications in a variety of fields. Here we explored the synthesis and characterization of novel QD-poly(vinyl acetate) (PVAc) and poly(ethylene-co-vinyl acetate) (PEVA) nanocomposites for application as light-selective nanofilms. Both CdS and CdS-ZnS core−shell QDs were synthesized by means of pyrolysis of single molecular precursors at 180 °C, and then functionalized with a methoxysilane group for subsequent attachment to polymer chains by using sol−gel chemistry. These novel materials were examined with FTIR, EDX elemental analysis, solubility tests, photoluminescence, and UV−vis spectroscopy for characterization of the QDs, indicating successful synthesis and functionalization. The functionalized QDs were then used to synthesize novel QD-PVAc and QD-PEVA nanocomposites via a one-pot technique in supercritical carbon dioxide (scCO 2 ), which acts as a solvent and drying agent for the sol−gel chemistry linking the QDs to the polymer chains. In the synthesis of QD-PVAc, the characteristic emission peak of the QDs was quenched attributed to phase separation in the nanocomposites. By stabilizing the QDs with an excessive amount of ligands and controlling the reaction conditions, light-selective QD-PEVA nanofilms were successfully synthesized by using a two-step technique in scCO 2 . The synthesized QD-PEVA nanofilms displayed significant absorption in the UV and violet regions of the electromagnetic spectrum, while providing a characteristic emission in the region from orange to red light. This novel synthesis route can be applied to the synthesis of other light-selective nanofilms by varying the quantum dot and polymer systems.
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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".