Messy or Ordered? Multiscale Mechanics Dictates Shape‐Morphing of 2D Networks Hierarchically Assembled of Responsive Microfibers
Bibliographic record
Abstract
Abstract Shape‐morphing active networks of mesoscale filaments are a common hierarchical feature in biology for applying forces, transporting materials, and inducing motility with microscale resolution. Synthetic morphing systems of similar dimensions and capabilities hold potential for a range of technological applications, from micro‐muscles to shape‐morphing optical devices. Here, the fabrication of highly‐ordered 2D networks hierarchically constructed of thermoresponsive mesoscale polymeric fibers, which can exhibit morphing with microscale resolution, is presented. It is demonstrated both experimentally and computationally that the morphing of such networks strongly depends on the physical attributes of the single fiber, in particular on two intrinsic length scales—the fiber diameter and mesh size, which stems from network's density. It is shown that depending on these parameters, such fiber‐networks exhibit one of two thermally driven morphing behaviors: i) the fibers stay straight, and the network preserves its ordered morphology, exhibiting a bulk‐like behavior; or ii) the fibers buckle and the network becomes messy and highly disordered. Notably, in both cases, the networks display memory and regain their original ordered morphology upon shrinking. This hierarchically induced phase transition, demonstrated here on a range of networks, offers a new way of controlling the shape‐morphing of synthetic materials with mesoscale resolutions.
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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) | 0.003 | 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 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".