journal article·2020-10-14

Highly Conductive and Flexible Dopamine–Graphene Hybrid Electronic Textile Yarn for Sensitive and Selective NO2 Detection

Sang Won Lee, Hyo Gi Jung, Insu Kim, Dongtak Lee, Woong Kim, Sang Hun Kim, Jong-Heun Lee, Jinsung Park, Jeong Hoon Lee, Gyudo Lee, Dae Sung Yoon

ACS Applied Materials & Interfaces· Volume 12· Issue 41
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Abstract

Graphene-based electronic textile (e-textile) gas sensors have been developed for detecting hazardous NO2 gas. For the e-textile gas sensor, electrical conductivity is a critical factor because it directly affects its sensitivity. To obtain a highly conductive e-textile, biomolecules have been used for gluing the graphene to the textile surface, though there remain areas to improve, such as poor conductivity and flexibility. Herein, we have developed a dopamine–graphene hybrid electronic textile yarn (DGY) where the dopamine is used as a bio-inspired adhesive to attach graphene to the surface of yarns. The DGY shows improved electrical conductivity (∼40 times) compared to conventional graphene-based e-textile yarns with no glue. Moreover, it exhibited improved sensing performance in terms of short response time (∼2 min), high sensitivity (0.02 μA/ppm), and selectivity toward NO2. The mechanical flexibility and durability of the DGY were examined through a 1000-cycle bending test. For a practical application, the DGY was attempted to detect the NOx emitted from vehicles, including gasoline, diesel, and fuel cell electric vehicles. Our results demonstrated that the DGYs—as a graphene-based e-textile gas sensor for detecting NO2—are simple to fabricate, cheap, disposable, and mechanically stable.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Graphene research and applications · Conducting polymers and applications

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

Affiliations

School of Biomedical Engineering, Korea University, Seoul 02841, South Korea

Department of Control and Instrumentation Engineering, Korea University, Sejong 30019, South Korea

Department of Materials Science and Engineering, Korea University, Seoul 02841, South Korea

Department of Electrical Engineering, Kwangwoon University, Seoul 01897, Republic of Korea

Department of Biotechnology and Bioinformatics, Korea University, Sejong 30019, South Korea

Funding

National Research Foundation of Korea

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