Block copolymer structural color strain sensor
- Authors
- Park, Tae Hyun; Yu, Seunggun; Cho, Sung Hwan; Kang, Han Sol; Kim, Yeongsik; Kim, Min Ju; Eoh, Hongkyu; Park, Chanho; Jeong, Beomjin; Lee, Seung Won; Ryu, Du Yeol; Huh, June; Park, Cheolmin
- Issue Date
- 18-4월-2018
- Publisher
- NATURE PUBLISHING GROUP
- Citation
- NPG ASIA MATERIALS, v.10, pp.328 - 339
- Indexed
- SCIE
SCOPUS
- Journal Title
- NPG ASIA MATERIALS
- Volume
- 10
- Start Page
- 328
- End Page
- 339
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/76117
- DOI
- 10.1038/s41427-018-0036-3
- ISSN
- 1884-4049
- Abstract
- The development of electrically responsive sensors based on the capacitance, voltage, and resistance that can detect and simultaneou sly visualize the large strain involved with human motion is in great demand. Here, we demonstrate a highly stretchable, large strain capacitive sensor that can visualize strain based on the strain-responsive structural color (SC). Our device contains an elastomeric sensing film that produces a capacitance change under strain, in which a self-assembled block copolymer (BCP) photonic crystal (PC) film with 1D periodic in-plane lamellae aligned parallel to the film surface is embedded for the efficient visualization of strain. The capacitance change arises from changes in the dimensions of the elastomer film under strain. The mechanochromic BCP PC film responds to strain, giving rise to an SC change with strain. The initial red SC of the sensor blueshifts and turns blue when the sensor is stretched to 100%, resulting in a full-color SC alteration as a function of the strain. Our BCP SC strain sensor exhibits a fast strain response with multi-cycle reliability of both the capacitance and SC changes over 1000 cycles. This property allows for efficient visible recognition not only of the strained positions during finger bending and poking with a sharp object but also of the shapes of the strained objects.
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Collections - College of Engineering > Department of Chemical and Biological Engineering > 1. Journal Articles
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