Iota-Carrageenan/Chitosan Nanoparticles via Coacervation: Achieving Stability for Tiny Particles
Bibliographic record
Abstract
-carrageenan (ι-carrageenan) on the formation of polymeric nanoparticles in suspension (coacervates). A preliminary purification step of the polymers was essential for obtaining stable nanoparticles with small sizes as impurities, particularly metal ions that interfere with complexation, are removed by dialysis. Microparticles (13.5 μm in dry diameter) are obtained when aliquots of chitosan solution are poured into the ι-carrageenan solution. In general, an excess of chitosan results in the formation of agglomerated particles. The addition of an aliquot of ι-carrageenan solution (30 mL at 0.6 mg/mL and pH 4.0) to the chitosan solution (6.0 mL at 0.3 mg/mL and pH 4.0) leads to dispersed nanoparticles with a hydrodynamic radius of 278 ± 5 nm, a zeta potential of -31 ± 3 mV, and an average dry diameter of 45 ± 11 nm. The hydrodynamic radius increases as the pH rises. The partial deprotonation of ι-carrageenan chains enhances the interaction with water molecules, causing the particles to swell. These findings contribute to the fundamental understanding of polyelectrolyte complexation processes in aqueous suspension and provide insights for developing stable nanomaterials for potential practical applications.
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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) | 0.001 | 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 | 0.001 |
| 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".