Hierarchically Structured Deformation‐Sensing Mechanochromic Pigments
Bibliographic record
Abstract
Mechanochromic materials alter their color in response to mechanical force and are useful for both fundamental studies and practical applications. Several approaches are used to render polymers mechanochromic, but they generally suffer from limitations in sensing range, capacity to provide quantitative information, and their capability to enable broad and simple implementation. Here, is it reported that these problems can be overcome by combining photonic structures, which alter their reflection upon deformation, with covalent mechanophores, whose spectral properties change upon mechanically induced bond scission, in hierarchically structured mechanochromic pigments. This is achieved by synthesizing microspheres consisting of an elastic polymer with spiropyran-based cross-links and non-close-packed silica nanoparticles. A strain of less than 1% can be detected in a shift of the reflection band from the photonic structure, while the onset strain for the conversion of the spiropyran into fluorescent merocyanine ranges from 30% to 70%, creating a broad strain detection range. The two responses are tailorable and synergistic, permitting the activation strain for the mechanophore response to be tuned. The mechano-sensing photonic pigments are demonstrated to be readily incorporated into different polymeric materials of interest and quantitatively probe spatially heterogeneous deformations over a large strain range.
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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 | 0.001 |
| 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".