Molecular-Scale Simulation of Auxetic Behavior in Side-Chain Liquid Crystalline Polymers (SCLCPs)
Bibliographic record
Abstract
Auxetic materials, characterized by a negative Poisson’s ratio (NPR), exhibit unique mechanical properties with applications in medical and military technologies. Recent experimental and theoretical studies have demonstrated bulk auxetic behavior in liquid crystal elastomers (LCEs), highlighting the molecular reorientation mechanisms involved. However, side-chain liquid crystalline polymers (SCLCPs) remain underexplored for intrinsic molecular auxeticity. Using coarse-grained molecular dynamics simulations, we investigate SCLCPs inspired by Griffin’s architecture, focusing on their phase transitions and Poisson’s ratio. One-arm and two-arm SCLCP variants were simulated, revealing NPR in one-arm systems at low lateral monomer volume fractions ( R < 6%), driven by the swirling motion of longitudinal monomer domains. Phase transitions from amorphous to polycrystalline smectic-like configurations were analyzed using a cooling process, with properties evaluated below the transition threshold (∼400 K). To enhance accuracy, the ab initio calculations on energy interactions between different configurations of ellipsoids and beads were performed. Our findings elucidate molecular mechanisms underlying auxetic behavior in SCLCPs, complementing existing LCE studies and offering insights for designing tailored auxetic polymers.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".