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Hetero-Dimensional 2D Ti3C2Tx MXene and 1D Graphene Nanoribbon Hybrids for Machine Learning-Assisted Pressure Sensors

Authors
Lee, Ho JinYang, Jun ChangChoi, JungwooKim, JingyuLee, Gang SanSasikala, Suchithra PadmajanLee, Gun-HeePark, Sang-Hee KoLee, Hyuck MoSim, Joo YongPark, SteveKim, Sang Ouk
Issue Date
Jun-2021
Publisher
AMER CHEMICAL SOC
Keywords
MXene; graphene nanoribbon; hybridization; pressure sensor; machine learning; health-care monitoring
Citation
ACS NANO, v.15, no.6, pp 10347 - 10356
Pages
10
Journal Title
ACS NANO
Volume
15
Number
6
Start Page
10347
End Page
10356
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/146535
DOI
10.1021/acsnano.1c02567
ISSN
1936-0851
1936-086X
Abstract
Hybridization of low-dimensional components with diverse geometrical dimensions should offer an opportunity for the discovery of synergistic nanocomposite structures. In this regard, how to establish a reliable interfacial interaction is the key requirement for the successful integration of geometrically different components. Here, we present 1D/2D heterodimensional hybrids via dopant induced hybridization of 2D Ti3C2Tx MXene with 1D nitrogen-doped graphene nanoribbon. Edge abundant nanoribbon structures allow a high level nitrogen doping (similar to 6.8 at%), desirable for the strong coordination interaction with Ti3C2Tx MXene surface. For piezoresistive pressure sensor application, strong adhesion between the conductive layers and at the conductive layer/elastomer interface significantly diminishes the sensing hysteresis down to 1.33% and enhances the sensing stability up to 10 000 cycles at high pressure (100 kPa). Moreover, large-area pressure sensor array reveals a high potential for smart seat cushion-based posture monitoring application with high accuracy (>95%) by exploiting machine learning algorithm.
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