Water‐Soluble Nanoparticles from Random Copolymer and Oppositely Charged Surfactant, 3
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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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 | 0.001 | 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 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".