Multi‐Stimuli Dually‐Responsive Intelligent Woven Structures with Local Programmability for Biomimetic Applications
Bibliographic record
Abstract
This work focuses on multi-stimuli-responsive materials with distinctive abilities, that is, color-changing and shape-memory. Using metallic composite yarns and polymeric/thermochromic microcapsule composite fibers, processed via a melt-spinning technique, an electrothermally multi-responsive fabric is woven. The resulting smart-fabric transfers from a predefined structure to an original shape while changing color upon heating or applying an electric field, making it appealing for advanced applications. The shape-memory and color-changing features of the fabric can be controlled by rationally controlling the micro-scale design of the individual fibers in the structure. Thus, the fibers' microstructural features are optimized to achieve excellent color-changing behavior along with shape fixity and recovery ratios of 99.95% and 79.2%, respectively. More importantly, the fabric's dual-response by electric field can be achieved by a low voltage of 5 V, which is smaller than the previously reported values. Above and beyond, the fabric is able to be meticulously activated by selectively applying a controlled voltage to any part of the fabric. The precise local responsiveness can be bestowed upon the fabric by readily controlling its macro-scale design. A biomimetic dragonfly with the shape-memory and color-changing dual-response ability is successfully fabricated, broadening the design and fabrication horizon of groundbreaking smart materials with multiple functions.
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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) | 0.000 | 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) | 0.000 | 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".