Determination of Phase Behavior of Poly(ethylene oxide) and Chitosan Solution Blends Using Rheometry
Bibliographic record
Abstract
Aqueous solutions of PEO exhibit a lower critical solution temperature (LCST) phase diagram. In this work, phase separation behavior of PEO/water solutions was investigated using small-amplitude oscillatory shear and steady shear rheological measurements. Binodal decomposition temperatures were determined from the sudden changes in the slope of the dynamic temperature sweep of storage modulus and loss tangent. The spinodal decomposition points were also estimated by a mean-field theoretical approach. Comparing the obtained critical points with other conventional methods revealed that rheological measurements are powerful and sensitive to detect even the early stage of phase separation of PEO solutions. This successful method was employed to investigate phase separation and miscibility of chitosan/PEO solutions at different compositions in aqueous acetic acid solutions that have already showed anomalous behavior in a forming process. Lower critical solution temperature (LCST) phase behavior was observed for chitosan/PEO solution blends. Phase separation temperature, miscibility range, and correlation length of the solutions were determined from isochronal dynamic temperature sweep experiments. The effect of chitosan/PEO ratio on the binodal and spinodal decomposition temperatures was studied. Finding phase separation information on polymer solutions through rheological measurement is very promising. Isothermal steady shear rheological measurements were also carried out on chitosan/PEO solutions over a temperature range in which phase separation occurs. Viscosity increase at low shear rates above but in the vicinity of phase separation temperature was observed, which confirms the validity of the theoretical approach employed to determine the critical temperatures through dynamic rheological measurements. Finally, the Flory–Huggins interaction parameters were estimated from critical solution temperature and concentration results.
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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".