Hetero-Dimensional 2D Ti3C2Tx MXene and 1D Graphene Nanoribbon Hybrids for Machine Learning-Assisted Pressure Sensors.
Ho Jin LeeJun Chang YangJungwoo ChoiJingyu KimGang San LeeSuchithra Padmajan SasikalaGun-Hee LeeSang-Hee Ko ParkHyuck Mo LeeJoo Yong SimSteve ParkSang Ouk KimPublished in: ACS nano (2021)
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.
Keyphrases
- machine learning
- reduced graphene oxide
- high resolution
- artificial intelligence
- high throughput
- big data
- deep learning
- carbon nanotubes
- single molecule
- high glucose
- small molecule
- room temperature
- quantum dots
- ionic liquid
- gold nanoparticles
- cancer therapy
- oxidative stress
- molecular dynamics simulations
- drug delivery
- nucleic acid
- low cost
- human health
- mass spectrometry
- simultaneous determination
- climate change
- cell migration
- stress induced