Hetero-Dimensional 2D Ti3C2T x MXene and 1D Graphene Nanoribbon Hybrids for Machine Learning-Assisted Pressure Sensors

• Published in: ACS nano Vol. 15; no. 6; pp. 10347 - 10356
• Main 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
• Format: Journal Article
• Language: English
• Published: American Chemical Society 22-06-2021
• Subjects: pressure sensor; graphene nanoribbon; MXene; health-care monitoring; hybridization; machine learning
• ISSN: 1936-0851; 1936-086X
• DOI: 10.1021/acsnano.1c02567

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 Ti3C2T x MXene with 1D nitrogen-doped graphene nanoribbon. Edge abundant nanoribbon structures allow a high level nitrogen doping (∼6.8 at%), desirable for the strong coordination interaction with Ti3C2T x 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.