Smart Polymer Nanoparticles Designed for Environmentally Compliant Coatings
Bibliographic record
Abstract
We describe the synthesis, characterization, and film-forming properties of two-component nanoparticles that undergo a reversible morphology transformation in water as a function of pH. The particles consist of a high molecular weight acrylate copolymer and an acid-rich oligomer designed to be miscible with the polymer when its -COOH groups are protonated. Attaching a fluorescence resonance energy transfer (FRET) pair to components inside the nanoparticles enabled us to assess morphology at the molecular level. By inspecting changes in the donor fluorescence decay profile at different pH values, we established miscibility of the components in acidic solution but with charge-induced phase separation when the oligomers were neutralized to their carboxylate form. Complementary titration experiments revealed that the nanoparticles adopt a core-shell structure when the acid groups are deprotonated. We studied the effect of the acid-rich oligomer on the diffusion rate of the high molecular weight polymers following film formation. Our results show that the carboxylated oligomer enhanced the rate of diffusive mixing between high molecular weight molecules by more than 2 orders of magnitude. FRET measurements carried out on partially dried films using a low-resolution microscope showed that the carboxylate oligomer shell can delay coalescence for ca. 30 min after passage of the drying front. This delay is expected to help with increasing the 'open time' of latex paints, a desirable property of solvent-based paints that remains difficult to achieve with (environmentally compliant) waterborne paints. Use of ammonia as a volatile base resulted in synergistic effects: initial retardation of coalescence followed by acceleration of diffusive mixing as the ammonium salts dissociated and ammonia evaporated from the film.
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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 | 0.000 | 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) | 0.000 | 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".