Mechanical Force Sensitive Acrylic Latex Coating
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We prepared force sensitive acrylic latex coatings by covalently incorporating spiropyran mechanophore. The acrylic latexes were obtained through emulsion copolymerization of butyl acrylate (BA), methyl methacrylate (MMA) with vinyltriethoxysilane (VTES) as interparticle cross-linker, and (1′-(2-(methacryloyloxy)ethyl)-3′,3′-dimethylspiro[chromene-2,2′-indolin]-6-yl)methyl methacrylate) (SP) as intraparticle cross-linker. The latexes of P(BA- co -MMA- co -SP- co -VTES) were subsequently cast onto Teflon-coated surface to form latex coatings. The condensation of hydrolyzed VTES provided interparticle cross-linking and improved mechanical properties of the formed thin films. Intraparticle cross-linker SP endowed the coatings with mechanoreponsiveness. The mechanoactivation of SP-containing latex films was demonstrated. Increasing the content of intra-cross-linker SP resulted in higher stress sensitivity and lower critical stress required for mechanoactivation. Increasing the content of interparticle cross-linker VTES resulted in higher critical stress for SP mechanoactivation but had little effect on the stress sensitivity. T g and operation temperature also showed significant effect on mechanoactivation. Slower strain rate allowed for higher SP-to-MC conversion. This work represents the first example of mechanochromic acrylic latexes and provides insight into the design of force sensitive and self-reporting polymer coatings.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it