Water‐Soluble Nanoparticles from Random Copolymer and Oppositely Charged Surfactant, 3
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this report, we investigate the nanoparticle formation between random copolymers (RCPs) of methoxy-poly(ethylene glycol) monomethacrylate (MePEGMA) and (3-(methacryloylamino)propyl)trimethylammonium chloride (MAPTAC) and oppositely charged natural surfactants, sodium oleate and sodium laurate, using turbidimetric titration, steady-state fluorescence, dynamic light scattering, and electron microscopy. Though sodium oleate and sodium laurate are sparingly soluble in water, the nanoparticle complexes formed between the RCPs and these surfactants are soluble in the entire range of compositions studied here, including the stoichiometric electronetural complexes. The spherical nature of these nanoparticle complexes is revealed by electron microscopic (EM) analysis. Dynamic light scattering (DLS) showed that the average diameters of the nanoparticles are in the range 50 to 150 nm, which is supported by EM analysis. Pyrene fluorescence experiments suggested that these soluble nanoparticles have hydrophobic cores, which may solubilize hydrophobic drug molecules. The polarity index (I(1)/I(3)) obtained from the pyrene fluorescence spectra and the conductometric measurements showed that the critical concentration of fatty acid salts needed to obtain nanoparticles are in the order of 10(-4) M. Further, the complexation of such poorly water-soluble amphiphilic surfactants with polymers offers a useful method for the immobilization of hydrophobic compounds towards water-soluble drug carrier formulations. The formation of water-soluble nanoparticles by the self-assembly of fatty acid salts upon interacting with oppositely charged poly(ethylene glycol)-based polyions.
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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 | 0.000 | 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 it