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 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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".