Directed stratification in polymer–latex film blends via pH and drying control
Bibliographic record
Abstract
HYPOTHESIS: Stratification in polymer-colloid films is governed by interfacial interactions, component miscibility, and drying kinetics. We hypothesize that introducing a pH-responsive, acid-rich oligomer (ARO2) into latex films enables controlled vertical phase separation through electrostatic tuning and evaporation rate modulation. EXPERIMENTS: = 274 nm), varying pH (8.2-9.5), relative humidity (RH: 15-45 %), and ionic strength (0-50 mM NaCl). Förster Resonance Energy Transfer (FRET) was used to quantify ARO2-latex interdiffusion, while vertical distribution was characterized using confocal laser scanning microscopy (CLSM) and cross-sectional atomic force microscopy (AFM). FINDINGS: ≈ 0.06), creating conditions favorable for stratification during drying. At pH 9.5 and 15 % RH, electrostatic repulsion between ionized ARO2 and latex particles, combined with size ratio (α ≈ 18) and moderate Péclet numbers (Pe ≈ 2.1), drove diffusiophoretic transport of ARO2 toward the evaporating interface. CLSM and AFM revealed a distinct ARO2-rich surface layer (10-20 μm thick) under these conditions, while slower drying or increased salt concentration suppressed segregation. This controllable stratification mechanism enables design of structured polymer-latex coatings: pH > 9 + low RH promotes surface enrichment, while pH < 8 or high RH yields uniform distribution.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".