Environmentally Responsive Nanoparticles from Block Ionomer Complexes: Effects of pH and Ionic Strength
Bibliographic record
Abstract
Nanoscale size materials, displaying environmentally responsive behavior, are of special interest for various applications, including drug delivery. This work explores the effects of environmental parameters (pH, concentration, and chemical nature of low molecular weight salts) on self-assembly and physicochemical properties of block ionomer complexes (BIC). BIC are synthesized by reacting block ionomer (PEO- b -PMA) and oppositely charged surfactant (hexadecyltrimethylammonium bromide). The resulted BIC form stable aqueous dispersions at any ionomer/surfactant ratio (particle size in the 60−90 nm range). Decrease of the ionization degree of the PMA block upon decrease of pH causes elevation of particle size at pH < 5.5 followed by formation of large aggregates at pH < 4. Increase of pH causes a decrease of the particle size. Addition of low molecular weight salts leads to disintegration of BIC at a specific salt concentration termed the “critical salt concentration” or csc. The csc values strongly depend on the nature of the salt. For cations csc increases in the order K + ≈ Li + ≈ Na + > N(CH 3 ) 4 + . For anions it increases in the order I - > Br - > Cl - > AcO - > F - . Such behavior is explained by the contribution of binding of counterions with PMA segments and surfactant cations. The disintegration process is reversible, as BIC particles reconstitute as the salt concentration decreases.
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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".