The human brain is a sophisticated, high-performance biocomputer that processes multiple complex tasks in parallel with high efficiency and remarkably low power consumption. Scientists have long been pursuing an artificial intelligence (AI) that can rival the human brain. Spiking neural networks based on neuromorphic computing platforms simulate the architecture and information processing of the intelligent brain, providing new insights for building AIs. The rapid development of materials engineering, device physics, chip integration, and neuroscience has led to exciting progress in neuromorphic computing with the goal of overcoming the von Neumann bottleneck. Herein, fundamental knowledge related to the structures and working principles of neurons and synapses of the biological nervous system is reviewed. An overview is then provided on the development of neuromorphic hardware systems, from artificial synapses and neurons to spike-based neuromorphic computing platforms. It is hoped that this review will shed new light on the evolution of brain-like computing.

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Due to the rapid development of artificial intelligence (AI) and internet of things (IoTs), neuromorphic computing and hardware security are becoming more and more important. The volatile memristors, which feature spontaneous decay of device conductance, own the distinct combination of high similarity to the biological neurons and synapses and unique physical mechanisms. They are excellent candidates for mimicking the synaptic functions and ideal randomness source of the entropy for hardware‐based security. Herein, the recent advances of volatile memristors in devices, mechanisms, and application aspects are summarized. First, a brief introduction is presented to describe the switching type, materials, and temporal response of volatile memristors. Second, the volatile switching mechanisms are discussed and grouped into ion effects, thermal effects, and electrical effects. Third, attention is focused on the applications of volatile memristors for access devices, neuromorphic computing (artificial neurons and synapses), and hardware security (true random number generators and physical unclonable functions). Finally, major challenges and future outlook of volatile memristors for neuromorphic computing and hardware security are discussed.

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2D materials with intriguing properties have been widely used in optoelectronics. However, electronic devices suffered from structural damage due to the ultrathin materials and uncontrolled defects at interfaces upon metallization, which hindered the development of reliable devices. Here, a damage‐free Au/h‐BN/Au memristor is reported using a clean, water‐assisted metal transfer approach by physically assembling Au electrodes onto the layered h‐BN which minimized the structural damage and undesired interfacial defects. The memristors demonstrate significantly improved performance with the coexistence of nonpolar and threshold switching as well as tunable current levels by controlling the compliance current, compared with devices with evaporated contacts. The devices integrated into an array show suppressed sneak path current and can work as both logic gates and latches to implement logic operations allowing in‐memory computing. Cross‐sectional scanning transmission electron microscopy analysis validates the feasibility of this nondestructive metal integration approach, the crucial role of high‐quality atomically sharp interface in resistive switching, and a direct observation of percolation path. The underlying mechanism of boron vacancies‐assisted transport is further supported experimentally by conductive atomic force microscopy free from process‐induced damage, and theoretically by ab initio simulations.