journal article·2021-03

Electrical conduction of reduced graphene oxide coated meta-aramid textile and its evolution under aging conditions

Chungyeon Cho, Anastasia Elias, Jane Batcheller, Patricia Dolez, Hyun-Joong Chung

Journal of Industrial Textiles· Volume 50· Issue 8
Publisher page

Abstract

High-performance textiles – such as those used in protective clothing – age silently, undergoing a gradual reduction in their protective properties. We propose that an electrically conducting layer that loses its conductivity systematically under aging conditions can be used as an end-of-life-sensor for textiles. In the present work, we first present a simple method to prepare conductive tracks on a meta-aramid woven fabric using reduced graphene oxide. While 15 iterations of reduced graphene oxide coating cycles were needed to wrap around each m-aramid fiber with reduced graphene oxide sheets completely, 10 cycles were sufficient to establish the electrical conductivity that remained stable for up to 10 laboratory wash cycles (equivalent to 50 domestic laundry cycles). The conductivity of these reduced graphene oxide coated fabrics remained stable upon immersion in water. Furthermore, we established a fabrication protocol for patterning both single-sided and two-sided reduced graphene oxide tracks on the m-aramid fabric. The former is designed to lose its conductivity upon abrasion, while the latter is designed to undergo a gradual transition in properties during aging. Assessment with a Martindale abrasion tester revealed that the single-sided reduced graphene oxide–track lost its conductivity after 150 abrasion cycles, whereas the two-sided reduced graphene oxide–tracks survived 3000 abrasion cycles. These results demonstrate that a simple reduced graphene oxide coating technique can be used to prepare end-of-life sensors for high-performance textiles.
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Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Nanomaterials and Printing Technologies · Additive Manufacturing and 3D Printing Technologies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

University of Alberta

Funding

Natural Sciences and Engineering Research Council of Canada

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