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.

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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.

Resistive random access memories (RRAMs) based on electrochemical metallization mechanism (ECM) have potential applications in high-density data storage and efficient neuromorphic computing. However, the high variability of ECM device still...