Dual-modal flexible sensors based on flexible Ti3C2Tx (MXene)-bacterial cellulose composites for neural network-assisted pronunciations, shapes, and materials perception

Abstract

In the contemporary digital era, where human-machine interaction and robotics are rapidly evolving, the application of bacterial cellulose (BC) in the field of sensors is gradually gaining attention but still faces many challenges in practical applications. Here, Ti₃C₂Tx (MXene) was combined with BC by vacuum self-assembly technique to prepare MXene-BC composites. MXene-BC composites effectively combine the excellent electrical conductivity of MXene with the robust mechanical properties of BC, which significantly extends its application in flexible electronic devices. The results showed that the MXene-BC composites had excellent mechanical properties (fracture stress up to 41.09 MPa and Young's modulus up to 7.34 GPa) and good electrical properties (conductivity up to 353.77 S m^-1). The pressure sensors made with MXene-BC composites have fast response/recovery times (10 ms/10 ms), low detection thresholds (1 Pa), and excellent stability. The proximity sensors have good hysteresis, reversibility, response and stability. Notably, sensors based on MXene-BC composites can function as both pressure and proximity sensors. Basing on these properties, our combine 3D printing technology to create a proximity sensor array with shape recognition function. At the same time, combined with a multilayer perceptron neural network model, the dual-mode sensors can recognize pronunciations, and materials. It provides new options for the field of robotics and human-machine interaction.