With their working mechanisms based on ion migration, the switching dynamics and electrical behaviour of memristive devices resemble those of synapses and neurons, making these devices promising candidates for brain-inspired computing. Built into large-scale crossbar arrays to form neural networks, they perform efficient in-memory computing with massive parallelism by directly using physical laws. The dynamical interactions between artificial synapses and neurons equip the networks with both supervised and unsupervised learning capabilities. Moreover, their ability to interface with analogue signals from sensors without analogue/digital conversions reduces the processing time and energy overhead. Although numerous simulations have indicated the potential of these networks for brain-inspired computing, experimental implementation of large-scale memristive arrays is still in its infancy. This Review looks at the progress, challenges and possible solutions for efficient brain-inspired computation with memristive implementations, both as accelerators for deep learning and as building blocks for spiking neural networks.

Memristive crossbar arrays for brain-inspired computing

This review article attempts to provide a comprehensive review of the recent progress in the so-called resistive random access memories (RRAMs) First, a brief introduction is presented to describe the construction and development of RRAMs, their potential for broad applications in the fields of nonvolatile memory, unconventional computing and logic devices, and the focus of research concerning RRAMs over the past decade Second, both inorganic and organic materials used in RRAMs are summarized, and their respective advantages and shortcomings are discussed Third, the important switching mechanisms are discussed in depth and are classified into ion migration, charge trapping/de-trapping, thermochemical reaction, exclusive mechanisms in inorganics, and exclusive mechanisms in organics Fourth, attention is given to the application of RRAMs for data storage, including their current performance, methods for performance enhancement, sneak-path issue and possible solutions, and demonstrations of 2-D and 3-D crossbar arrays Fifth, prospective applications of RRAMs in unconventional computing, as well as logic devices and multi-functionalization of RRAMs, are comprehensively summarized and thoroughly discussed The present review article ends with a short discussion concerning the challenges and future prospects of the RRAMs

Recent progress in resistive random access memories: Materials, switching mechanisms, and performance

The emergence of new nonvolatile memory (NVM) technologies—such as phase change memory, resistive, and spin-torque-transfer magnetic RAM—has been motivated by exciting applications such as storage class memory, embedded nonvolatile memory, enhanced solid-state disks, and neuromorphic computing. Many of these applications call for such NVM devices to be packed densely in vast “crosspoint” arrays offering many gigabytes if not terabytes of solid-state storage. In such arrays, access to any small subset of the array for accurate reading or low-power writing requires a strong nonlinearity in the IV characteristics, so that the currents passing through the selecteddevices greatly exceed the residual leakage through the nonselecteddevices. This nonlinearity can either be included explicitly, by adding a discrete access device at each crosspoint, or implicitly with an NVM device which also exhibits a highly nonlinear IV characteristic. This article reviews progress made toward implementing such access device functionality, focusing on the need to stack such crosspoint arrays vertically above the surface of a silicon wafer for increased effective areal density. The authors start with a brief overview of circuit-level considerations for crosspoint memory arrays, and discuss the role of the access device in minimizing leakage through the many nonselected cells, while delivering the right voltages and currents to the selected cell. The authors then summarize the criteria that an access device must fulfill in order to enable crosspoint memory. The authors review current research on various discrete access device options, ranging from conventional silicon-based semiconductor devices, to oxide semiconductors, threshold switch devices, oxide tunnel barriers, and devices based on mixed-ionic-electronic-conduction. Finally, the authors discuss various approaches for self-selected nonvolatile memories based on Resistive RAM.

Access devices for 3D crosspoint memorya)

Passive crossbar resistive random access memory (RRAM) arrays require select devices with nonlinear I-V characteristics to address the sneak-path problem. Here, we present a systematical analysis to evaluate the performance requirements of select devices during the read operation of RRAM arrays for the proposed one-selector-one-resistor (1S1R) configuration with serially connected selector/storage element. We found high selector current density is critical and the selector nonlinearity (ON/OFF) requirement can be relaxed at present. Different read schemes were analyzed to achieve high read margin and low power consumption. Design optimizations of the sense resistance and the storage elements are also discussed.

Crossbar RRAM Arrays: Selector Device Requirements During Read Operation

In this letter, we demonstrated a new type of threshold selector with excellent electrical characteristics for cross-point memory array. The proposed Ag/TiO2-based threshold selector device showed high selectivity ( $\sim 10^{\mathrm {\mathbf {7}}}$ ) and steep slope ( $ mV/decade). The observed threshold switching in programmable metallization cell device occurred due to the spontaneous rupturing of silver (Ag) filament. The Ag ionization to minimize the steric repulsion between Ag and surrounding TiO2 electrolyte was the main origin of the spontaneous rupture.

Threshold Selector With High Selectivity and Steep Slope for Cross-Point Memory Array

We propose an epitaxial punchthrough diode for bipolar resistance RAM (RRAM) selector application. Epitaxial Si:C process is used to deposit n+/p/n+ layers which are fabricated into 300-nm-diameter vertical punchthrough diodes. High on-current density of >; 1 MA/cm2 and high on/off current ratio of >; 250 and >; 4700 (at opposite polarities) are observed. A switching speed of <; 10 ns is measured. On-voltage designability is demonstrated by tuning the p-region doping and length. The comparison of experimental IV with Sentaurus TCAD-simulated IV characteristics confirms the punchthrough mechanism. Comparison with other bipolar RRAM selector technologies highlights the overall advantages of punchthrough-based selector.

Punchthrough-Diode-Based Bipolar RRAM Selector by Si Epitaxy

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Punchthrough-Diode-Based Bipolar RRAM Selector by Si Epitaxy