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. Description 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 ~1015 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).

Memristive technologies for data storage, computation, encryption, and radio-frequency communication

This work has been supported by the generous Baseline funding program of the King Abdullah University of Science and Technology (KAUST).

Standards for the Characterization of Endurance in Resistive Switching Devices.

In this study, by inserting a buffer layer of TiOx between the SiOx:Ag layer and the bottom electrode, we have developed a memristor device with a simple structure of Ag/SiOx:Ag/TiOx/p++-Si by a physical vapor deposition process, in which the filament growth and rupture can be efficiently controlled during analog switching. The synaptic characteristics of the memristor device with a wide range of resistance change for weight modulation by implementing positive or negative pulse trains have been investigated extensively. Several learning and memory functions have been achieved simultaneously, including potentiation/depression, paired-pulse-facilitation (PPF), short-term plasticity (STP), and STP-to-LTP (long-term plasticity) transition controlled by repeating pulses more than a rehearsal operation, and spike-time-dependent-plasticity (STDP) as well. Based on the analysis of logarithmic I-V characteristics, it has been found that the controlled evolution/dissolution of conductive Ag-filaments across the dielectric layers can improve the performance of the testing memristor device.

/pdf/analog-switching-and-artificial-synaptic-behavior-of-ag-sio-3hb5onazlh.pdf

Analog Switching and Artificial Synaptic Behavior of Ag/SiO x :Ag/TiO x /p ++ -Si Memristor Device

One common challenge highlighted in almost every review article on organic resistive memory is the lack of areal switching uniformity. This, in fact, is a puzzle because a molecular switching mechanism should ideally be isotropic and produce homogeneous current switching free from electroforming. Such a demonstration, however, remains elusive to date. The reports attempting to characterize a nanoscopic picture of switching in molecular films show random current spikes, just opposite to the expectation. Here, this longstanding conundrum is resolved by demonstrating 100% spatially homogeneous current switching (driven by molecular redox) in memristors based on Ru-complexes of azo-aromatic ligands. Through a concurrent nanoscopic spatial mapping using conductive atomic force microscopy and in operando tip-enhanced Raman spectroscopy (both with resolution <7 nm), it is shown that molecular switching in the films is uniform from hundreds of micrometers down to the nanoscale and that conductance value exactly correlates with spectroscopically determined molecular redox states. This provides a deterministic molecular route to obtain spatially homogeneous, forming-free switching that can conceivably overcome the chronic problems of robustness, consistency, reproducibility, and scalability in organic memristors.

Nanometer-Scale Uniform Conductance Switching in Molecular Memristors

Resistive switching (RS) devices are metal/insulator/metal cells that can change their electrical resistance when electrical stimuli are applied between the electrodes, and they can be used to store and compute data. Planar crossbar arrays of RS devices can offer a high integration density (>108 devices mm−2) and this can be further enhanced by stacking them three‐dimensionally. The advantage of using layered materials (LMs) in RS devices compared to traditional phase‐change materials and metal oxides is that their electrical properties can be adjusted with a higher precision. Here, the key figures‐of‐merit and procedures to implement LM‐based RS devices are defined. LM‐based RS devices fabricated using methods compatible with industry are identified and discussed. The focus is on small devices (size < 9 µm2) arranged in crossbar structures, since larger devices may be affected by artifacts, such as grain boundaries and flake junctions. How to enhance device performance, so to accelerate the development of this technology, is also discussed.

Resistive Switching Crossbar Arrays Based on Layered Materials

Memristors or memristive devices are two-terminal nanoionic systems whose resistance switching effects are induced by ion transport and redox reactions in confined spaces down to nanometer or even atomic scales. Understanding such localized and inhomogeneous electrochemical processes is a challenging but crucial task for continued applications of memristors in nonvolatile memory, reconfigurable logic, and brain inspired computing. Here we give a survey for two of the most powerful technologies that are capable of probing the resistance switching mechanisms at the nanoscale – transmission electron microscopy, especially in situ, and scanning tunneling microscopy, for memristive systems based on both electrochemical metallization and valence changes. These studies yield rich information about the size, morphology, composition, chemical state and growth/dissolution dynamics of conducting filaments and even individual metal nanoclusters, and have greatly facilitated the understanding of the underlying mechanisms of memristive switching. Further characterization of cyclic operations leads to additional insights into the degradation in performance, which is important for continued device optimization towards practical applications.

/pdf/probing-electrochemistry-at-the-nanoscale-in-situ-tem-and-2tgmu12hf7.pdf

Probing electrochemistry at the nanoscale: in situ TEM and STM characterizations of conducting filaments in memristive devices

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Probing electrochemistry at the nanoscale: in situ TEM and STM characterizations of conducting filaments in memristive devices