Fabrication of Anisotropic Polymer Materials by Polymerization-Induced Phase Separation (PIPS) Under External Fields: Computational Analysis
Bibliographic record
Abstract
<p>Functionalities and structural properties of multiphase polymeric materials can be modified by imposing external forces to the mixture undergoing phase separation resulting in non-uniform anisotropic microstructures. Anisotropic heterogeneous polymeric materials have practical engineering applications such as anisotropic porous polymer membranes and switchable holographic polymer-dispersed liquid crystal films. Anisotropy can be generated by applying singly or in combination, an external force like shear flow, electric or magnetic field, surface effect, controlled chemical reaction, concentration gradient, or temperature gradient to a polymer solution undergoing phase separation. In this study, the self-condensation polymerization of a monomer in a monomer-solvent mixture and phase separation of the system were simultaneously modeled and simulated. The numerical Galerkin finite-element method was applied to develop the mathematical model. Short-range surface potential, long-range surface potential, and linear temperature and concentration gradients were applied singly and also simultaneously to the system undergoing the polymerization-induced phase separation (PIPS). The expected non- uniform structures were achieved. A comprehensive parametric study was carried out by investigating the effects of diffusivity, temperature gradient, concentration gradient, and surface potential parameter on the lag time, process time, morphology development, thickness of the wetting layer, and the extent of anisotropy of the system. The size analysis and structural characterization of the phase-separated system were also carried out using ImageJ 1.51j8 which is an image processing and analysis software. The numerical results are in good agreement with published experimental data.</p>
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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) | 0.001 | 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) | 0.015 | 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".