Hetero-Dimensional 2D Ti3C2Tx MXene and 1D Graphene Nanoribbon Hybrids for Machine Learning-Assisted Pressure Sensors
- Authors
- Lee, Ho Jin; Yang, Jun Chang; Choi, Jungwoo; Kim, Jingyu; Lee, Gang San; Sasikala, Suchithra Padmajan; Lee, Gun-Hee; Park, Sang-Hee Ko; Lee, Hyuck Mo; Sim, Joo Yong; Park, Steve; Kim, 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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Collections - 공과대학 > 기계시스템학부 > 1. Journal Articles
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