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Studying Large Amplitude Oscillatory Shear Response of Soft Materials
Published on: April 25, 2019
'Seeing' Strain in Soft Materials
Zhiyong Xia1, Vanessa D Alphonse2, Doug B Trigg3
1Applied Physics Laboratory, The Johns Hopkins University, Laurel, MD 20723, USA. Zhiyong.Xia@jhuapl.edu.
A novel passive strain sensor using poly(dimethyl siloxane) (PDMS) and spiropyran (SP) can measure high-rate impact strains. This reversible color-changing sensor offers a new method for quantifying material deformation, potentially aiding traumatic brain injury research.
Area of Science:
- Materials Science
- Mechanical Engineering
- Biomedical Engineering
Background:
- Existing methods for measuring soft material strain under impact lack continuous 3D spatial distribution.
- High-rate impact testing of soft materials is crucial for understanding material behavior and failure.
Purpose of the Study:
- To develop a novel passive strain sensor for measuring impact-induced strains in soft materials.
- To demonstrate the sensor's capability to provide continuous 3D spatial strain data.
Main Methods:
- Incorporation of spiropyran (SP) mechanophore into poly(dimethyl siloxane) (PDMS) elastomer.
- Utilizing the reversible color change of SP in PDMS to quantify strain under high strain rates (up to 1500 s⁻¹).
- High-speed imaging to capture dynamic strain events.
Main Results:
- A novel PDMS-based passive strain sensor with covalently incorporated SP was successfully developed.
- The sensor demonstrated the ability to measure impact strains via a reversible color change at strain rates up to 1500 s⁻¹ within milliseconds.
- The SP incorporation at 0.25 wt% was found to be effective for strain measurement.
Conclusions:
- The developed passive strain sensor offers a new, continuous, and reversible method for quantifying high-rate impact strains in soft materials.
- This technology has significant potential for applications such as quantifying brain strain in traumatic brain injury research.
- The sensor overcomes limitations of existing technologies by providing continuous 3D spatial strain distribution data.
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