UV‐Blocking Photoluminescent Silicon Nanocrystal/Polydimethylsiloxane Composites
Bibliographic record
Abstract
It is a challenge to synthesize transparent polydimethylsiloxane (PDMS) materials that can completely absorb the light energy of ultraviolet (UV) A, B, and C regions. Herein, near‐infrared (NIR) photoluminescent PDMS composites with hydrogen‐terminated silicon nanocrystals (ncSi:H) or decyl‐terminated silicon nanocrystals (ncSi‐decyl) fabricated by combination of hydrosilylation and polymer encapsulation are reported. Their morphologies, optical and mechanical properties, and thermal stabilities are investigated. It is interesting to find that these PDMS composites filled with even a very small amount of ncSi:H or ncSi‐decyl have unprecedented UV‐blocking properties and superior thermal stabilities as compared to the PDMS reference. In particular, the ncSi‐decyl/PDMS composite possesses impressive photoluminescence. Furthermore, ncSi‐decyl are favorable for reinforcing the mechanical properties of the PDMS composites as compared to the PDMS reference and the ncSi:H/PDMS composite. The enhancement in the mechanical properties and thermal stabilities of these novel PL PDMS composites depends upon the creation of crosslinkable sites and entanglement interactions between the PDMS chains and the ncSi. These results suggest that potential applications for NIR photoluminescent ncSi/PDMS composites will likely be found in the fields of advanced UV‐blocking textiles, cosmetics, photofluids, stretchable electronic devices, anticounterfeiting materials, biological imaging, and diagnostics.
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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".