Effect of Concentration on the Photoinduced Aggregation of Polymer Nanoparticles
Bibliographic record
Abstract
We describe the effect of concentration on the photoinduced flocculation and aggregation of a nonaqueous dispersion of core−shell nanoparticles (diameter = 50 nm), which consist of a tightly cross-linked core composed of poly(butyl methacrylate- co -ethylene glycol dimethacrylate) and a lightly cross-linked shell of poly(butyl methacrylate- co -ethylene glycol dimethacrylate- co -methacrylic acid). The particles could be dispersed in cyclohexane after modification of the acid groups by ester formation with 2-bromo-1-phenyl-octadecan-1-one. Photocleavage of these substituents (λ = 310 nm) regenerated the −COOH groups and led to aggregation of the destabilized particles. Since the rate of aggregation is relatively slow in this system, we were able to study the process of particle aggregation kinetics by a combination of static and dynamic laser light scattering. Our results indicate, for particle dispersions from 0.23 mg/mL to 0.93 mg/mL, that there are three stages in the aggregation process. Initially, several particles come into contact to form small elongated clusters. Subsequently, these clusters undergo further aggregation to form larger aggregates characterized by a fractal dimension of around 2.3. This result indicates that aggregation in the second stage follows a reaction-limited cluster−cluster aggregation mechanism. At very long times, the aggregate size appears to level off, consistent with a reversible aggregation mechanism. We also found for the three different concentrations that the measured average radius of gyration 〈 R g,app 〉 during aggregation scaled with time with an exponent of about 1.4 ± 0.1.
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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 | 0.001 |
| 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 | 0.001 | 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".