The in-depth understanding of ions' generation and movement inside all-inorganic perovskite quantum dots (CsPbBr QDs), which may lead to a paradigm to break through the conventional von Neumann bottleneck, is strictly limited. Here, it is shown that formation and annihilation of metal conductive filaments and Br ion vacancy filaments driven by an external electric field and light irradiation can lead to pronounced resistive-switching effects. Verified by field-emission scanning electron microscopy as well as energy-dispersive X-ray spectroscopy analysis, the resistive switching behavior of CsPbBr QD-based photonic resistive random-access memory (RRAM) is initiated by the electrochemical metallization and valance change. By coupling CsPbBr QD-based RRAM with a p-channel transistor, the novel application of an RRAM-gate field-effect transistor presenting analogous functions of flash memory is further demonstrated. These results may accelerate the technological deployment of all-inorganic perovskite QD-based photonic resistive memory for successful logic application.

Recently, in-sensor computing with individual sensors or multiple connected sensors directly processing information has been proposed to improve energy, area, and time efficiency of artificial intelligence systems. Current investigations mainly focus on a single sensory processing such as auditory, visual, tactile, olfactory, and so on. However, a human perception system can sense and process different types of information with a complex environment and small perceptive field simultaneously. For example, the recognition accuracy of human eyes is highly affected by the environment such as extremely low or high relative humidity (RH). Here, a multi-modal MXene-ZnO memristor that combines visual data sensing, RH sensing, and pre-processing functions to emulate the unique environmental adaptive behavior of the human eye is designed and constructed. The multi-field controlled resistive switching of the MXene-ZnO memristor is originated from the photon-/protons-regulated formation of oxygen vacancies filaments. Finally, in-sensor computing with a MXene-ZnO memristor functioning as both filter to preprocess the information and synapse to implement a weight updating process with different humidity adaptability has been demonstrated. Multimodal in-sensor computing provides the potential to reduce the underlying circuitry complexity of the traditional neuromorphic visual system and contributes to the development of intelligence in device-level implementations.

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 carrot-inspired solar thermal evaporator exhibits a water evaporation rate of 2.04 kg m−2 h−1 and an outstanding durability and stability.