Hetero-Dimensional 2D Ti<sub>3</sub>C<sub>2</sub>T<sub><i>x</i></sub> MXene and 1D Graphene Nanoribbon Hybrids for Machine Learning-Assisted Pressure Sensors
Ho Jin Lee, Jun Chang Yang, Jungwoo Choi, Jingyu Kim, Gang San Lee, Suchithra Padmajan Sasikala, Gunhee Lee, Sang‐Hee Ko Park, Sang-Hee Ko Park, Hyuck Mo Lee, Joo Yong Sim, Steve Park, Steve Park, Sang Ouk Kim
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 (∼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.