Bioinspired artificial haptic neuron system has received much attention in the booming artificial intelligence industry for its broad range of high-impact applications such as personal healthcare monitoring, electronic skins, and human-machine interfaces. An artificial haptic neuron system is designed by integrating a piezoresistive sensor and a Nafion-based memristor for the first time in this paper. The piezoresistive sensor serves as a sensory receptor to transform mechanical stimuli into electric signals, and the Nafion-based memristor serves as the synapse to further process the information. The pyramid-structured sensor exhibits excellent sensitivity (6.7 × 10 7 kPa −1 in 1-5 kPa and 3.8 × 10 5 kPa −1 in 5-50 kPa) and durability (>7000 cycles), while the memristor realizes fundamental synaptic functions under low power consumption (10-200 pJ) and remains stable for over 10 4 consecutive tests. The integrated system can detect tactile stimuli encoded with temporal information, such as the count, frequency, duration and speed of the external force. As a proof-of-concept, English characters recognition with high accuracy can be achieved on the system under a supervised learning method. This work shows promising potential in bioinspired sensing systems owing to the high performance, excellent durability, and simple fabrication procedure.

Metal-organic framework (MOF) nanosheets have attracted significant interests for sensing, electrochemical, and catalytic applications. Most significantly, 2D MOF with highly accessible sites on the surface is expected to be applicable in data storage. Here, the memory device is first demonstrated by employing M-TCPP (TCPP: tetrakis(4-carboxyphenyl) porphyrin, M: metal) as resistive switching (RS) layer. The as-fabricated resistive random access memory (RRAM) devices exhibit a typical electroforming free bipolar switching characteristic with on/off ratio of 10 3 , superior retention, and reliability performance. Furthermore, the time-dependent RS behaviors under constant voltage stress of 2D M-TCPP-based RRAMs are systematically investigated. The properties of the percolated conducting paths are revealed by the Weibull distribution by collecting the measured turn-on time. The multilevel information storage state can be gotten by setting a series of compliance current. The charge trapping assisted hopping is proposed as operation principle of the MOF-based RRAMs which is further confirmed by atomic force microscopy at electrical modes. The research is highly relevant for practical operation of 2D MOF nanosheet-based RRAM, since the time widths, magnitudes of pulses, and multilevel-data storage can be potentially set.

Phototunable biomaterial‐based resistive memory devices and understanding of their underlying switching mechanisms may pave a way toward new paradigm of smart and green electronics. Here, resistive switching behavior of photonic biomemory based on a novel structure of metal anode/carbon dots (CDs)‐silk protein/indium tin oxide is systematically investigated, with Al, Au, and Ag anodes as case studies. The charge trapping/detrapping and metal filaments formation/rupture are observed by in situ Kelvin probe force microscopy investigations and scanning electron microscopy and energy‐dispersive spectroscopy microanalysis, which demonstrates that the resistive switching behavior of Al, Au anode‐based device are related to the space‐charge‐limited‐conduction, while electrochemical metallization is the main mechanism for resistive transitions of Ag anode‐based devices. Incorporation of CDs with light‐adjustable charge trapping capacity is found to be responsible for phototunable resistive switching properties of CDs‐based resistive random access memory by performing the ultraviolet light illumination studies on as‐fabricated devices. The synergistic effect of photovoltaics and photogating can effectively enhance the internal electrical field to reduce the switching voltage. This demonstration provides a practical route for next‐generation biocompatible electronics.

Recently, conductive metal−organic frameworks (MOFs) as the active material have provided broad prospects for electronic device application. The positioning technologies for MOFs enable the fabrication of novel microstructures, which can modulate the morphology of the material and tune the properties for the targeted application. Herein, a template‐method is used to synthesize the hierarchical structure of MOF hybrid array (MHA) on copper mesh (MHA@Mesh) for flexible sensor. Finite element method (FEM) results indicate that the 3D hierarchical MHA@Mesh can mimic the micro/nanoscale structure of human skin, which enables an interlocking contact. MHA@Mesh‐based flexible sensor presents rapid response rate (<1 ms) and high sensitivity (up to 307 kPa−1) which is 20 times higher than that of MHA@Foil‐based sensor (15 kPa−1). The flexible pressure device could be applied to monitor the finger motion and human pulses. Moreover, the music recognition can be performed by integrating the MOFs hardware sensors with machine learning algorithms. Overall, this design concept of 3D hierarchical microarray structures demonstrates potential in the fields of wearable technologies and human–machine interfaces.

A multi-state information storage state could be achievedviaa configurable SET process with non-volatile devices based on Ti3C2nanosheets.