Multiple interfaces in diffusional phase transitions in binary mesogen-nonmesogen mixtures undergoing metastable phase separations
Bibliographic record
Abstract
Theory and simulations of simultaneous chemical demixing and phase ordering are performed for a mixed order parameter system with an isotropic-isotropic (I-I) phase separation that is metastable with respect to an isotropic-nematic (I-N) phase-ordering transition. Under certain conditions, the disordered phase transforms into an ordered phase via the motion of a double front containing a metastable phase produced by I-I demixing, a thermodynamically driven mechanism not previously reported. Different kinetic regimes are found depending on the location of the initial conditions in the thermodynamic phase diagram and the ratio between diffusional and nematic phase-ordering mobilities. For a diffusional process, depending if the temperature is above or below the critical codissolution point, an inflection point or a phase separation takes place in the depletion layer. This phase separation leads to the formation of a second interface where the separation of the two metastable isotropic phases grows monotonically with time. The observed deviations from the typical Fickian concentration profiles are associated with strong positive deviations of the mixture from ideality due to couplings between concentration and nematic ordering. Although systems of interest include liquid-crystalline nanocomposites, this mechanism may apply to any mixture that can undergo an order-disorder transition and demix.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".