Geometric‐Bifurcation Methods for Dual Order‐Disorder Transitions: Applications to the Isotropic‐to‐Smectic A Phase Transformation
Bibliographic record
Abstract
Herein, the focus is on equilibrium self‐assembly of smectic A liquid crystal (LC) phases, characterized by partial orientational and 1D positional order. This LC material organization is observed in the protein solution precursor phases of mussel byssus and its emergence is of importance to biological material science, biomimetics, and green manufacturing. A purely thermodynamic model is intrinsically complex due to proliferation of unknown parameters and computational predictions with low information content. This work extends previous work on smectic self‐assembly using an integrated theory and computational platform based on polynomial conservation laws, differential geometry of thermodynamic surfaces, and soft matter shape algebra. The predictions include two zones (nucleation and growth and spinodal decomposition), the stability predicted for single‐order states (nematic, plastic), and the birth and death of the possible phases under varying quenches. A systematic theory‐computation loop yields conservation laws for smectic ordering, the geometry description (shape and curvedness) of bifurcations, and the response functions to thermal quenches. The outputs of this study form the foundation for characterization of drop‐like spatial‐temporal self‐assembly and colloidal nonequilibrium self‐organization of rod‐like protein precursors into functional biological fibrous materials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".