Overview of Resistive Random Access Memory (RRAM): Materials, Filament Mechanisms, Performance Optimization, and Prospects

Abstract

Because conventional nonvolatile memory is limited by process technology and physical size, resistive random access memory (RRAM) gradually enters the field of view due to its simple structure, fast program/erase speed, low power consumption, and so on. This review article summarizes the materials, filament mechanisms, performance optimization, and application prospects of RRAM structures to provide readers with a reference for future investigation. The filament mechanisms, which involve the electrochemical metallization mechanism (ECM), valence change mechanism (VCM), and thermochemical mechanism (TCM), of RRAM devices are particularly highlighted. The parameters that determine the RRAM characteristics such as operating voltages, ON/OFF ratio, endurance, and data retention are improved by incorporating the three methods: 1) “interface engineering”, 2) element doping of functional materials, and 3) introduction of low‐dimensional materials. In the last section, a brief introduction to the future RRAM application prospects and challenges is provided.

Advances of RRAM Devices: Resistive Switching Mechanisms, Materials and Bionic Synaptic Application

“…Compared with conventional silicon-based memory devices like flash memory, it is noted that RRAM devices have demonstrated a series of advantages such as low operation voltage, low power consumption, high density, and enhanced compatibility with traditional complementary metal oxide semiconductor (CMOS) technology [31][32][33]. In addition, with the deepening of research on artificial intelligence (AI) hardware equipment, biomimetic synapse behaviors of RRAM devices have also received extensive attention, which has non-negligible influence in the investigation of electrical artificial synapse [15,17,[34][35][36][37][38]. However, some other limitations and challenges of RRAM devices cannot be neglected, such as synthesis methods of RS materials, stability of device performance and storage mechanism of devices with different materials.…”

“…However, conventional synaptic devices cannot meet the requirements of ANNs because of some technological limitations like large device area, high power consumption and slow response speed. As illustrated in Figure 10 b, emerging synaptic device can be integrated in to a single unit and improves the processing efficiency and processing accuracy [ 15 , 17 , 34 , 35 , 36 , 37 , 38 ]. The superior RS characteristics demonstrated in RRAM devices reveal its great potential in the neuromorphic application based on ANNs.…”

Influence of Nitrogen Adsorption of Doped Ta on Characteristics of SiNx‐Based Resistive Random Access Memory

“…Some RRAMs with stable resistance property based on various materials, such as high‐k HfO 2 , TaO 2 , and TiO 2 , have been reported . At present, RRAM is widely accepted as a strong candidate for the next generation of memory due to its advantages of simple structure, good compressibility, fast read–write speed, and compatibility with complementary metal oxide semiconductor (CMOS) technology . Si 3 N 4 is a wide bandgap semiconductor material with many excellent properties, such as stable chemical properties, strong acid and alkali resistance, strong resistance to sodium ions, excellent oxidation resistance, and a designable dielectric constant.…”

Logic-in-Memory Computation: Is It Worth It? A Binary Neural Network Case Study

“…They have included a small external logic which is in charge of computing the accumulations. Based on a similar working principle, Resistive Random-Access-Memory (RRAM) [14] are devices in which the logic data is encoded in two or multiple resistive states. Differently from MTJs, resistance is determined by the conductivity of a conduction path that can be broken (high resistance state) or reformed (low resistance state).…”