We report an artificial eardrum using an acoustic sensor based on two-dimensional MXene (Ti 3 C 2 T x ), which mimics the function of a human eardrum for realizing voice detection and recognition. Using MXene with a large interlayer distance and micropyramid polydimethylsiloxane arrays can enable a two-stage amplification of pressure and acoustic sensing. The MXene artificial eardrum shows an extremely high sensitivity of 62 kPa −1 and a very low detection limit of 0.1 Pa. Notably, benefiting from the ultrasensitive MXene eardrum, the machine-learning algorithm for real-time voice classification can be realized with high accuracy. The 280 voice signals are successfully classified for seven categories, and a high accuracy of 96.4 and 95% can be achieved by the training dataset and the test dataset, respectively. The current results indicate that the MXene artificial intelligent eardrum shows great potential for applications in wearable acoustical health care devices.

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With rapid development of integrated circuits, urgent requirements for a transistor with lower subthreshold swing (SS) and better contact properties are needed. To optimize the SS and contact issues, we propose a concept of molybdenum disulfide (MoS2) filament transistor with two modes. We successfully fabricated the proposed devices in a wafer-scale. Mode I can enable the device with extremely low SS down to 2.26 mV/dec by switching the contact filament between on and off while mode II can realize a record high on/off ratio of 2.6 × 109 by using filament as quasi-zero dimensional (quasi-0D) contact. Compared to conventional three-dimensional (3D) contact, quasi-0D contact using conductive filament improves the current density nearly 50 times. We also built a spice model to simulate the electrical behaviors, and the simulation results show an extremely low SS in mode I (using abrupt filament formation/rupture) and excellent quasi-0D contact in mode II. The two-mode MoS2 filament transistor can significantly improve the SS and contact comparing to those of the state-of-the-art transistors, which has the great potential to boost the development of the next generation mainstream transistors.