Abstract
Memristive devices, which combine a resistor with memory functions such that voltage pulses can change their resistance (and hence their memory state) in a nonvolatile manner, are beginning to be implemented in integrated circuits for memory applications. However, memristive devices could have applications in many other technologies, such as non–von Neumann in-memory computing in crossbar arrays, random number generation for data security, and radio-frequency switches for mobile communications. Progress toward the integration of memristive devices in commercial solid-state electronic circuits and other potential applications will depend on performance and reliability challenges that still need to be addressed, as described here.
Putting memristors to work
Memristors, which are resistors that change conductivity and act as memories, are not only being used in commercial computing but have several application areas in computing and communications. Lanza
et al
. review how devices such as phase-change memories, resistive random-access memories, and magnetoresistive random-access memories are being integrated into silicon electronics. Memristors also are finding use in artificial intelligence when integrated in three-dimensional crossbar arrays for low-power, non–von Neuman architectures. Other applications include random-number generation for data encryption and radiofrequency switches for mobile communications. —PDS
A review explains how resistors with memory functions are being integrated into electronics and new computer architectures.
BACKGROUND
Memristive devices exhibit an electrical resistance that can be adjusted to two or more nonvolatile levels by applying electrical stresses. The core of the most advanced memristive devices is a metal/insulator/metal nanocell made of phase-change, metal-oxide, magnetic, or ferroelectric materials, which is often placed in series with other circuit elements (resistor, selector, transistor) to enhance their performance in array configurations (i.e., avoid damage during state transition, minimize intercell disturbance). The memristive effect was discovered in 1969 and the first commercial product appeared in 2006, consisting of a 4-megabit nonvolatile memory based on magnetic materials. In the past few years, the switching endurance, data retention time, energy consumption, switching time, integration density, and price of memristive nonvolatile memories has been remarkably improved (depending on the materials used, values up to ~10
15
cycles, >10 years, ~0.1 pJ, ~10 ns, 256 gigabits per die, and ≤$0.30 per gigabit have been achieved).
ADVANCES
As of 2021, memristive memories are being used as standalone memory and are also embedded in application-specific integrated circuits for the Internet of Things (smart watches and glasses, medical equipment, computers), and their market value exceeds $621 million. Recent studies have shown that memristive devices may also be exploited for advanced computation, data security, and mobile communication. Advanced computation refers to the hardware implementation of artificial neural networks by exploiting memristive attributes such as progressive conductance increase and decrease, vector matrix multiplication (in crossbar arrays), and spike timing–dependent plasticity; state-of-the-art developments have achieved >10 trillion operations per second per watt. Data encryption can be realized by exploiting the stochasticity inherent in the memristive effect, which manifests as random fluctuations (within a given range) of the switching voltages/times and state currents. For example, true random number generator and physical unclonable functions produce random codes when exposing a population of memristive devices to an electrical stress at 50% of switching probability (it is impossible to predict which devices will switch because that depends on their atomic structure). Mobile communication can also benefit from memristive devices because they could be employed as 5G and terahertz switches with low energy consumption owing to the nonvolatile nature of the resistive states; the current commercial technology is based on silicon transistors, but they are volatile and consume data both during switching and when idle. State-of-the-art developments have achieved cutoff frequencies of >100 THz with excellent insertion loss and isolation.
OUTLOOK
Consolidating memristive memories in the market and creating new commercial memristive technologies requires further enhancement of their performance, integration density, and cost, which may be achieved via materials and structure engineering. Market forecasts expect the memristive memories market to grow up to ~$5.6 billion by 2026, which will represent ~2% of the nearly $280 billion memory market. Phase-change and metal-oxide memristive memories should improve switching endurance and reduce energy consumption and variability, and the magnetic ones should offer improved integration density. Ferroelectric memristive memories still suffer low switching endurance, which is hindering commercialization. The figures of merit of memristive devices for advanced computation highly depend on the application, but maximizing endurance, retention, and conductance range while minimizing temporal conductance fluctuations are general goals. Memristive devices for data encryption and mobile communication require higher switching endurance, and two-dimensional materials prototypes are being investigated.
Part of
Science
’s coverage of the 75th anniversary of the discovery of the transistor
Fundamental memristive effects and their applications.
Memristive devices, in which electrical resistance can be adjusted to two or more nonvolatile levels, can be fabricated using different materials (top row). This allows adjusting their performance to fulfill the requirements of different technologies. Memristive memories are a reality, and important progress is being achieved in advanced computation, security systems, and mobile communication (bottom row).