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Stress Sensing in Polycaprolactone Films via an Embedded Photochromic Compound

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O’Bryan, Greg, Wong, Bryan M., McElhanon, James R.·2010·ACS Applied Materials & Interfaces

Abstract

A photochromic polymer exhibiting mechanochromic behavior is prepared by means of ring-opening polymerization (ROP) of epsilon-caprolactone by utilizing a difunctional indolinospiropyran as an initiator. The configuration of having the photochromic initiating species within the polymer backbone leads to a mechanochromic effect with deformation of polymer films leading to ring-opening of the spiro C-O bond to form the colored merocyanine. Active stress monitoring by dynamic mechanical analysis (DMA) in tension mode was used to probe the effects of UV irradiation on polymer films held under constant strain. Irradiation with UV light induces a negative change in the polymer stress of approximately 50 kPa. Finally, a model of the mechanochromic effect was performed using density functional theory (DFT) and time-dependent DFT (TDDFT) calculations. A sharp increase in the relative molecular energy and the absorption wavelength as well as a drastic decrease in the spiro-oxygen atom charge occurred at a molecular elongation of >39%.

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Metadata

Authors
O’Bryan, G., Wong, B. M., & McElhanon, J. R.
Venue
ACS Applied Materials & Interfaces
Published
2010-05-19
Volume
2
Issue
6
Pages
1594-1600
ISSN
  • 1944-8244 (ISSN-L)
  • 1944-8252
OpenAlex
W1983551924
Cited by
213
References
0
FWCI
8.37
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Stress Sensing in Polycaprolactone Films via an Embedded Photochromic Compound. https://app.cochat.ai/papers/10.1021/am100050v
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O’Bryan, G., Wong, B. M., & McElhanon, J. R. (2010). Stress Sensing in Polycaprolactone Films via an Embedded Photochromic Compound. ACS Applied Materials & Interfaces. https://doi.org/10.1021/am100050v

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.