Mechanoreceptors endow humans with the sense of touch by translating the external stimuli into coded spikes, inspiring the rise of artificial mechanoreceptor systems. However, to incorporate slow adaptive receptors-like pressure sensors with artificial neurons remains a challenge. Here we demonstrate an artificial mechanoreceptor by rationally integrating a polypyrrole-based resistive pressure sensor with a volatile NbO x memristor, to mimic the tactile sensation and perception in natural skin, respectively. The artificial mechanoreceptor enables the tactile sensory coding by converting the external mechanical stimuli into strength-modulated electrical spikes. Also, tactile sensation enhancement is achieved by processing the spike frequency characteristics with the pulse coupled neural network. Furthermore, the artificial mechanoreceptor can integrate signals from parallel sensor channels and encode them into unified electrical spikes, resembling the coding of intensity in tactile neural processing. These results provide simple and efficient strategies for constructing future bio-inspired electronic systems.

Memristors based neuromorphic devices can efficiently process complex information and fundamentally overcome the bottleneck of traditional computing based on von Neumann architecture. Meanwhile, natural biomaterials have attracted significant attention for biologically integrated electronic devices due to their excellent biocompatibility, mechanical flexibility, and controllable biodegradability. Thus, biomaterial‐based memristors may have a transformative impact on bridging electronic neuromorphic systems and biological systems. However, the working voltage in biological system is low, but the operation voltages of conventional memristors are high, violating the energy‐efficient biological system. Here, high‐performance silk fibroin‐based threshold switching (TS) memristors are demonstrated, which reveal an on‐current of 1 mA, a low threshold voltage (Vth) of 0.17 V, a high selectivity of 3 × 106, and a steep turn‐on slope of <2.5 mV dec–1. Meanwhile, the silk TS devices depict outstanding device uniformity and stability even at high humidity (80%) and temperature (70 °C) environments. The silk TS devices exhibit typical short‐term plasticity (STP) of biological synapses including pair‐pulse facilitation (PPF). More importantly, a leaky integrate‐and‐fire (LIF) artificial neuron is successfully realized based on the volatile characteristics of silk TS memristors. These achievements pave the way for utilizing silk biomaterials in advanced bioelectronics and neuromorphic computing.

Metal oxide thin-films transistors (TFTs) produced from solution-based printing techniques can lead to large-area electronics with low cost. However, the performance of current printed devices is inferior to those from vacuum-based methods due to poor film uniformity induced by the “coffee-ring” effect. Here, we report a novel approach to print high-performance indium tin oxide (ITO)-based TFTs and logic inverters by taking advantage of such notorious effect. ITO has high electrical conductivity and is generally used as an electrode material. However, by reducing the film thickness down to nanometers scale, the carrier concentration of ITO can be effectively reduced to enable new applications as active channels in transistors. The ultrathin (~10-nm-thick) ITO film in the center of the coffee-ring worked as semiconducting channels, while the thick ITO ridges (>18-nm-thick) served as the contact electrodes. The fully inkjet-printed ITO TFTs exhibited a high saturation mobility of 34.9 cm2 V−1 s−1 and a low subthreshold swing of 105 mV dec−1. In addition, the devices exhibited excellent electrical stability under positive bias illumination stress (PBIS, ΔVth = 0.31 V) and negative bias illuminaiton stress (NBIS, ΔVth = −0.29 V) after 10,000 s voltage bias tests. More remarkably, fully printed n-type metal–oxide–semiconductor (NMOS) inverter based on ITO TFTs exhibited an extremely high gain of 181 at a low-supply voltage of 3 V, promising for advanced electronics applications.