An ultrathin memristor based on a two-dimensional WS2/MoS2 heterojunction

Sliding Memristor in Parallel-Stacked Hexagonal Boron Nitride

Sliding ferroelectricity in 2D materials, arising from interlayer sliding-induced interlayer hybridization and charge redistribution at the van der Waals interface, offers a means to manipulate spontaneous polarization at the atomic scale through various methods such as stacking order, interfacial contact, and electric field. However, the practical application of extending 2D sliding ferroelectricity remains challenging due to the contentious mechanisms and the complex device structures required for ferroelectric switching. Here, a sliding memristor based on a graphene/parallel-stacked hexagonal boron nitride/graphene tunneling device, featuring a stable memristive hysteresis induced by interfacial polarizations and barrier height modulations, is presented. As the tunneling current density increases, the memristive window broadens, achieving an on/off ratio of ≈103 and 2 order decrease of the trigger current density, attributed to the interlayer migration of positively charged boron ions and the formation of conductive filaments, as supported by the theoretical calculations. The findings open a path for exploring the sliding memristor via a tunneling device and bridge the gap between sliding ferroelectricity and memory applications.

Multilevel Conductance States of Vapor-Transport-Deposited Sb2S3 Memristors Achieved via Electrical and Optical Modulation

The pursuit of advanced brain-inspired electronic devices and memory technologies has led to explore novel materials by processing multimodal and multilevel tailored conductive properties as the next generation of semiconductor platforms, due to von Neumann architecture limits. Among such materials, antimony sulfide (Sb2S3) thin films exhibit outstanding optical and electronic properties, and therefore, they are ideal for applications such as thin-film solar cells and nonvolatile memory systems. This study investigates the conduction modulation and memory functionalities of Sb2S3 thin films deposited via the vapor transport deposition technique. Experimental results indicate that the Ag/Sb2S3/Pt device possesses properties suitable for memory applications, including low operational voltages, robust endurance, and reliable switching behavior. Further, the reproducibility and stability of these properties across different device batches validate the reliability of these devices for practical implementation. Moreover, Sb2S3-based memristors exhibit artificial neuroplasticity with prolonged stability, promising considerable advancements in neuromorphic computing. Leveraging the photosensitivity of Sb2S3 enables the Ag/Sb2S3/Pt device to exhibit significant low operating potential and conductivity modulation under optical stimulation for memory applications. This research highlights the potential applications of Sb2S3 in future memory devices and optoelectronics and in shaping electronics with versatility.

A synapse with low power consumption based on MoTe2/SnS2heterostructure

The use of two-dimensional materials and van der Waals heterostructures holds great potential for improving the performance of memristors Here, we present SnS2/MoTe2heterostructure synaptic transistors. Benefiting from the ultra-low dark current of the heterojunction, the power consumption of the synapse is only 19pJ per switching under 0.1 V bias, comparable to that of biological synapses. The synaptic device based on the SnS2/MoTe2demonstrates various synaptic functionalities, including short-term plasticity, long-term plasticity, and paired-pulse facilitation. In particular, the synaptic weight of the excitatory postsynaptic current can reach 109.8%. In addition, the controllability of the long-term potentiation and long-term depression are discussed. The dynamic range (Gmax/Gmin) and the symmetricity values of the synaptic devices are approximately 16.22 and 6.37, and the non-linearity is 1.79. Our study provides the possibility for the application of 2D material synaptic devices in the field of low-power information storage.

Enhancing the Uniformity of a Memristor Using a Bilayer Dielectric Structure

Resistive random access memory (RRAM) holds great promise for in-memory computing, which is considered the most promising strategy for solving the von Neumann bottleneck. However, there are still significant problems in its application due to the non-uniform performance of RRAM devices. In this work, a bilayer dielectric layer memristor was designed based on the difference in the Gibbs free energy of the oxide. We fabricated Au/Ta2O5/HfO2/Ta/Pt (S3) devices with excellent uniformity. Compared with Au/HfO2/Pt (S1) and Au/Ta2O5/Pt (S2) devices, the S3 device has a low reset voltage fluctuation of 2.44%, and the resistive coefficients of variation are 13.12% and 3.84% in HRS and LRS, respectively, over 200 cycles. Otherwise, the bilayer device has better linearity and more conductance states in multi-state regulation. At the same time, we analyze the physical mechanism of the bilayer device and provide a physical model of ion migration. This work provides a new idea for designing and fabricating resistive devices with stable performance.

Ag-doped non-imperfection-enabled uniform memristive neuromorphic device based on van der Waals indium phosphorus sulfide

Memristors are considered promising energy-efficient artificial intelligence hardware, which can eliminate the von Neumann bottleneck by parallel in-memory computing. The common imperfection-enabled memristors are plagued with critical variability issues impeding their commercialization. Reported approaches to reduce the variability usually sacrifice other performances, e.g., small on/off ratios and high operation currents. Here, we demonstrate an unconventional Ag-doped nonimperfection diffusion channel-enabled memristor in van der Waals indium phosphorus sulfide, which can combine ultralow variabilities with desirable metrics. We achieve operation voltage, resistance, and on/off ratio variations down to 3.8, 2.3, and 6.9% at their extreme values of 0.2 V, 1011 ohms, and 108, respectively. Meanwhile, the operation current can be pushed from 1 nA to 1 pA at the scalability limit of 6 nm after Ag doping. Fourteen Boolean logic functions and convolutional image processing are successfully implemented by the memristors, manifesting the potential for logic-in-memory devices and efficient non-von Neumann accelerators.

In Situ Unveiling of the Resistive Switching Mechanism of Halide Perovskite-Based Memristors

The organic-inorganic halide perovskite has become one of the most promising candidates for next-generation memory devices, i.e. memristors, with excellent performance and solution-processable preparation. Yet, the mechanism of resistive switching in perovskite-based memristors remains ambiguous due to a lack of in situ visualized characterization methods. Here, we directly observe the switching process of perovskite memristors with in situ photoluminescence (PL) imaging microscopy under an external electric field. Furthermore, the corresponding element composition of conductive filaments (CFs) is studied, indicating that the metallic CFs with respect to the activity of the top electrode are essential for device performance. Finally, electrochemical impedance spectroscopy (EIS) is conducted to reveal that the transition of ion states is associated with the formation of metallic CFs. This study provides in-depth insights into the switching mechanism of perovskite memristors, paving a pathway to develop and optimize high-performance perovskite memristors for large-scale applications.

A carbon conductive filament-induced robust resistance switching behavior for brain-inspired computing

Memristors have revolutionized the path forward for brain-inspired computing. However, the instability of the nucleation process of conductive filaments based on active metal electrodes leads to the discrete distribution of switching parameters, which hinders the realization of high-performance and low-power devices for neuromorphic computing. In response, a carbon conductive filament-induced robust memristor is demonstrated with variation coefficients as low as 3.9%/-1.18%, a threshold power as low as 10-9 W, and 3 × 106 s retention and 107 cycle endurance behaviors can be maintained. The recognition accuracy for Modified National Institute of Standards and Technology (MNIST) handwriting is as high as 96.87%, attributed to the high linearity of the iterative updating of synaptic weights. The demodulation and storage functions of the American Standard Code for Information Interchange (ASCII) are demonstrated by programmable pulse modulation. Notably, the transmission electron microscopy (TEM) images allow the observation of carbon conductive filament paths formed in the low resistance state. First-principles calculations analyze the energetics of defects involved in the diffusion of carbon atoms into MoTe2 films. This work presents a novel guideline for studying memristor-based neuromorphic computing.

Overcoming the Unfavorable Effects of "Boltzmann Tyranny:" Ultra-Low Subthreshold Swing in Organic Phototransistors via One-Transistor-One-Memristor Architecture

Organic phototransistors (OPTs), as photosensitive organic field-effect transistors (OFETs), have gained significant attention due to their pivotal roles in imaging, optical communication, and night vision. However, their performance is fundamentally limited by the Boltzmann distribution of charge carriers, which constrains the average subthreshold swing (SSave ) to a minimum of 60 mV/decade at room temperature. In this study, an innovative one-transistor-one-memristor (1T1R) architecture is proposed to overcome the Boltzmann limit in conventional OFETs. By replacing the source electrode in an OFET with a memristor, the 1T1R device exploits the memristor's sharp resistance state transitions to achieve an ultra-low SSave of 18 mV/decade. Consequently, the 1T1R devices demonstrate remarkable sensitivity to photo illumination, with a high specific detectivity of 3.9 × 109  cm W-1 Hz1/2 , outperforming conventional OPTs (4.9 × 104  cm W-1 Hz1/2 ) by more than four orders of magnitude. The 1T1R architecture presents a potentially universal solution for overcoming the detrimental effects of "Boltzmann tyranny," setting the stage for the development of ultra-low SSave devices in various optoelectronic applications.

Organic iontronic memristors for artificial synapses and bionic neuromorphic computing

To tackle the current crisis of Moore's law, a sophisticated strategy entails the development of multistable memristors, bionic artificial synapses, logic circuits and brain-inspired neuromorphic computing. In comparison with conventional electronic systems, iontronic memristors offer greater potential for the manifestation of artificial intelligence and brain-machine interaction. Organic iontronic memristive materials (OIMs), which possess an organic backbone and exhibit stoichiometric ionic states, have emerged as pivotal contenders for the realization of high-performance bionic iontronic memristors. In this review, a comprehensive analysis of the progress and prospects of OIMs is presented, encompassing their inherent advantages, diverse types, synthesis methodologies, and wide-ranging applications in memristive devices. Predictably, the field of OIMs, as a rapidly developing research subject, presents an exciting opportunity for the development of highly efficient neuro-iontronic systems in areas such as in-sensor computing devices, artificial synapses, and human perception.

Controllable Resistive Switching in ReS2 /WS2 Heterostructure for Nonvolatile Memory and Synaptic Simulation

Memristors with nonvolatile storage performance and simulated synaptic functions are regarded as one of the critical devices to overcome the bottleneck in traditional von Neumann computer architecture. 2D van der Waals heterostructures have paved a new way for the development of advanced memristors by integrating the intriguing features of different materials and offering additional controllability over their optoelectronic properties. Herein, planar memristors with both electrical and optical tunability based on ReS2 /WS2 van der Waals heterostructure are demonstrated. The devices show unique unipolar nonvolatile behavior with high Roff /Ron ratio of up to 106 , desirable endurance, and retention, which are superior to pure ReS2 and WS2 devices. When decreasing the channel length, the set voltage can be notably reduced while the high Roff /Ron ratios are retained. By introducing electrostatic doping through the gate control, the set voltage can be tailored in a wide range from 4.50 to 0.40 V. Furthermore, biological synaptic functions and plasticity, including spike rate-dependent plasticity and paired-pulse facilitation, are successfully realized. By employing optical illumination, resistive switching can also be modulated, which is dependent on the illumination energy and power. A mechanism related to the interlayer charge transfer controlled by optical excitation is revealed.

Performance Regulation of a ZnO/WOx-Based Memristor and Its Application in an Emotion Circuit

The development of a memristor is very important for artificial intelligence and new electronic circuits. In this work, Ag(Al)/ZnO/WO_x/FTO memristors are fabricated by magnetron sputtering, and the device performance is further improved through annealing and oxygen supply during sputtering. The experimental data show that the FTO/WO_x/ZnO-O₂/Ag memristor has the largest high resistance state (HRS)/low resistance state (LRS) resistance ratio and the best durability. Through data fitting and analysis, the switching mechanism of memristors with different top electrodes is investigated. Furthermore, the physical model of the best performance memristor was established by Simulink, and an emotion-monitoring circuit was constructed on this basis. The circuit can be used to monitor and record the mood changes, and the feedback of the emotion monitoring can be fed back to the user to help them adjust the mood.

A review of memristor: material and structure design, device performance, applications and prospects

With the booming growth of artificial intelligence (AI), the traditional von Neumann computing architecture based on complementary metal oxide semiconductor devices are facing memory wall and power wall. Memristor based in-memory computing can potentially overcome the current bottleneck of computer and achieve hardware breakthrough. In this review, the recent progress of memory devices in material and structure design, device performance and applications are summarized. Various resistive switching materials, including electrodes, binary oxides, perovskites, organics, and two-dimensional materials, are presented and their role in the memristor are discussed. Subsequently, the construction of shaped electrodes, the design of functional layer and other factors influencing the device performance are analyzed. We focus on the modulation of the resistances and the effective methods to enhance the performance. Furthermore, synaptic plasticity, optical-electrical properties, the fashionable applications in logic operation and analog calculation are introduced. Finally, some critical issues such as the resistive switching mechanism, multi-sensory fusion, system-level optimization are discussed.

Printed Electronics Based on 2D Material Inks: Preparation, Properties, and Applications toward Memristors

Printed electronics, which fabricate electrical components and circuits on various substrates by leveraging functional inks and advanced printing technologies, have recently attracted tremendous attention due to their capability of large-scale, high-speed, and cost-effective manufacturing and also their great potential in flexible and wearable devices. To further achieve multifunctional, practical, and commercial applications, various printing technologies toward smarter pattern-design, higher resolution, greater production flexibility, and novel ink formulations toward multi-functionalities and high quality have been insensitively investigated. 2D materials, possessing atomically thin thickness, unique properties and excellent solution-processable ability, hold great potential for high-quality inks. Besides, the great variety of 2D materials ranging from metals, semiconductors to insulators offers great freedom to formulate versatile inks to construct various printed electronics. Here, a detailed review of the progress on 2D material inks formulation and its printed applications has been provided, specifically with an emphasis on emerging printed memristors. Finally, the challenges facing the field and prospects of 2D material inks and printed electronics are discussed.

Advances in Emerging Photonic Memristive and Memristive-Like Devices

Possessing the merits of high efficiency, low consumption, and versatility, emerging photonic memristive and memristive-like devices exhibit an attractive future in constructing novel neuromorphic computing and miniaturized bionic electronic system. Recently, the potential of various emerging materials and structures for photonic memristive and memristive-like devices has attracted tremendous research efforts, generating various novel theories, mechanisms, and applications. Limited by the ambiguity of the mechanism and the reliability of the material, the development and commercialization of such devices are still rare and in their infancy. Therefore, a detailed and systematic review of photonic memristive and memristive-like devices is needed to further promote its development. In this review, the resistive switching mechanisms of photonic memristive and memristive-like devices are first elaborated. Then, a systematic investigation of the active materials, which induce a pivotal influence in the overall performance of photonic memristive and memristive-like devices, is highlighted and evaluated in various indicators. Finally, the recent advanced applications are summarized and discussed. In a word, it is believed that this review provides an extensive impact on many fields of photonic memristive and memristive-like devices, and lay a foundation for academic research and commercial applications.

Reliable Memristor Based on Ultrathin Native Silicon Oxide

Memristors based on two-dimensional (2D) materials can exhibit great scalability and ultralow power consumption, yet the structural and thickness inhomogeneity of ultrathin electrolytes lowers the production yield and reliability of devices. Here, we report that the self-limiting amorphous SiO_x (∼2.7 nm) provides a perfect atomically thin electrolyte with high uniformity, featuring a record high production yield. With the guidance of physical modeling, we reveal that the atomic thickness of SiO_x enables anomalous resistive switching with a transition to an analog quasi-reset mode, where the filament stability can be further enhanced using Ag-Au nanocomposite electrodes. Such a picojoule memristor shows record low switching variabilities (C2C and D2D variation down to 1.1 and 2.6%, respectively), good retention at a few microsiemens, and high conductance-updating linearity, constituting key metrics for analog neural networks. In addition, the stable high-resistance state is found to be an excellent source for true random numbers of Gaussian distribution. This work opens up opportunities in mass production of Si-compatible memristors for ultradense neuromorphic and security hardware.

Memristive Devices Based on Two-Dimensional Transition Metal Chalcogenides for Neuromorphic Computing

Two-dimensional (2D) transition metal chalcogenides (TMC) and their heterostructures are appealing as building blocks in a wide range of electronic and optoelectronic devices, particularly futuristic memristive and synaptic devices for brain-inspired neuromorphic computing systems. The distinct properties such as high durability, electrical and optical tunability, clean surface, flexibility, and LEGO-staking capability enable simple fabrication with high integration density, energy-efficient operation, and high scalability. This review provides a thorough examination of high-performance memristors based on 2D TMCs for neuromorphic computing applications, including the promise of 2D TMC materials and heterostructures, as well as the state-of-the-art demonstration of memristive devices. The challenges and future prospects for the development of these emerging materials and devices are also discussed. The purpose of this review is to provide an outlook on the fabrication and characterization of neuromorphic memristors based on 2D TMCs.