Recent Advances in Memristive Materials for Artificial Synapses

Neuromorphic architectures are in the spotlight as promising candidates for substituting current computing systems owing to their high operation speed, scale‐down ability, and, especially, low energy consumption. Among candidate materials, memristors have shown excellent synaptic behaviors such as spike time‐dependent plasticity and spike rate‐dependent plasticity by gradually changing their resistance state according to electrical input stimuli. Memristor can work as a single synapse without programming support, which remarkably satisfies the requirements of neuromorphic computing. Here, the most recent developments in memristor‐based artificial synapses are introduced with their excellent synaptic behaviors accompanied with detailed explanation of their working mechanisms. As conventional memristive materials, metal oxides are reviewed with recent advancements in heterojunction technologies. An overview of organic materials is presented with their remarkable synaptic behaviors including their advantages of biocompatibility, low cost, complementary metal‐oxide semiconductor compatibility, and ductility. 2D materials are also introduced as promising candidates for artificial synapses owing to their flexibility and scalability. As emerging materials, halide perovskites and low‐dimensional materials are presented with their synaptic behaviors. In the last section, future challenges and research directions are discussed. This review article is hoped to be a guide to rational materials design for the artificial synapses of neuromorphic computing. Neuromorphic architecture heralds a new era of next generation computing system. Memristor‐based artificial synapses have been considered as promising basic units of neuromorphic computing and have displayed excellent synaptic behaviors. Up‐to‐date advances in artificial synapses are categorized into the type of memristive materials and reviewed with their working mechanisms. Future research directions are provided for improving synaptic functions for neuro‐computing.