Interfacial arrangement and phase transitions of PNiPAm microgels with different crosslinking densities
Bibliographic record
Abstract
Microgels are colloidal hydrogel particles that exhibit a pronounced softness, which arises from the swollen nature of the constituent polymer network. This softness leads to a substantial deformability of such particles at liquid interfaces, which, in turn translates into a complex phase behaviour that can exhibit a phase transition between a non-close packed and a close packed arrangement. Here, we explore how the degree of swellability and deformability - and therefore the softness of the particles - affects the phase behaviour of microgels at the air/water interface upon compression. We use precipitation polymerization to synthesize poly(N-isopropylacrylamide) microgels with similar hydrodynamic radii in the collapsed state and systematically vary the degree of swellability by changing the crosslinking density. We spread these microgels onto the air/water interface of a Langmuir trough and characterize their interfacial properties by surface pressure - area isotherms. Furthermore, we continuously transfer the interfacial microgel monolayer during compression onto a solid substrate, thus encoding the complete phase diagram of the microgels with increasing particle density as a function of the position on the solid substrate. We investigate the microgel arrangement by atomic force microscopy and scanning electron microscopy and use image analysis to extract quantitative information on the interparticle distance and degree of order. We find that the phase transition is very sensitive to the crosslinking density and occurs at much lower surface pressures for less deformable particles. The softest microgels do not undergo any phase transition. Instead, the system exhibits pronounced local conformation changes around point defects with local five- and sevenfold symmetries, indicating that the geometry of the assembled structure effectively controls the local pressure experienced by the microgels.
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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".