Encapsulation of Dye Molecules and Nanoparticles in Hollow Organogel Fibers of a Nonchiral Polyurethane Model Compound
Bibliographic record
Abstract
We present the case of a nonchiral organogelator that forms hollow fibers and encapsulates silver nanoparticles (SNP) and a dye molecule. The biscarbamate molecule (a model compound for polyurethanes), which has two hydrogen-bonding motifs symmetrically attached to n-dodecyl side chains (C(12)), gels benzonitrile with hollow fibrillar morphology. The C(12) molecules form sheets that eventually wrap into hollow fibers to form the gel network. Herein, two-component gels were prepared with C(12) as one component and SNP, phthalocyanine (Pc), or perylene (Pe) as the other. Microscopic analysis and partial melting experiments confirmed the inclusion of the silver nanoparticles and phthalocyanine into the hollow fibers. On the other hand, Pe molecules tend to form crystals at the outer surface of the C(12) fibers, which results in a significant increase in the width of the gel fibers. This difference in the behavior of Pc and Pe molecules were accounted for by their crystal geometry and significantly different crystal growth rate compared with that of C(12) fiber formation in the gels. Pc crystallizes in a needle shape that facilitates occlusion in the gel fibers, whereas Pe forms large platelets. X-ray diffraction and spectroscopic analysis of the two-component gels along with their neat components confirmed that there was no change in the packing behavior of the Pc and Pe molecules in the gels. Therefore, these are examples of two-component physical gels in which the Pc crystals are occluded within the hollow fibers of C(12) by physical mixing of the components without the aid of any inter-molecular interactions between the different components. We have thus shown that lumen-loaded gel fibers with nanoparticles and dye molecules can be prepared by the two-component gel route, provided that the above growth rate, shape, and size conditions are satisfied.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".