Simulation, system analysis, and optimization of nematic bipolar droplet in polymer dispersed liquid crystal films
Bibliographic record
Abstract
Polymer dispersed liquid crystal (PDLC) films play an important role in liquid crystal display technology. PDLC films are used in devices such as switchable windows, complex billboards, and flat panel televisions. PDLC films consist of nematic bipolar droplets dispersed randomly in a polymer matrix. In this work, the effect of droplet shape, physical properties, and external field strength is examined on the performance of PDLC films. Finite element method (FEM) and finite difference method (FDM) are used to model a single droplet with external field applied parallel to the droplet axis of symmetry. Results of previous simulations with FEM are reproduced and compared with those with FDM. Genetic algorithm is employed to determine the optimum aspect ratio, and elastic constant ratio for the droplet, and external field strength with respect to minimum energy, response time, and relaxation time.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".