Poly(N-isopropylacrylamide) microgels at the oil–water interface: temperature effect
Bibliographic record
Abstract
Understanding the interfacial properties of soft poly(N-isopropylacrylamide) (PNIPAM) microgels covering an oil-water interface is essential for engineering stimuli-responsive emulsions stabilized by soft microgel particles. This study presents a systematic study on the interfacial properties of the PNIPAM-microgel-laden heptane-water interface as a function of temperature. We measured the interfacial tensions as well as dilatational rheology properties of the microgel-laden heptane-water interface using a pendant drop tensiometer. From fresh droplet experiments, the anomalous interfacial tension minima of the microgels covered oil-water interface were observed around the volume phase transition temperature (VPTT) of the PNIPAM microgels. Such interfacial tension minima are observable regardless of the microgel aggregates. Both dynamic and static parameters contributed to the observed interfacial tension minima around VPTT. The PNIPAM microgel deformability dynamically dominated the microgel spreading at the heptane-water interface in the early states, while PNIPAM microgel packing and interactions dominated the final static equilibrium states. Combining the interfacial tension and the dilatational rheology properties, we propose that the microgels would approach three distinctive states at temperatures below, around, and above VPTT at the heptane-water interface. Single droplet experiments further demonstrate that there exists an irreversible transition among these three states. The results of this study deepen our understanding of soft, porous, and deformable microgels' behaviors at the oil-water interface and have important implications for engineering microgels as stimuli-responsive emulsion stabilizers.
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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) | 0.000 | 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 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".