Zero-static power radio-frequency switches based on MoS2 atomristors

Morphological Evolution of Atomic Layer Deposited Hafnium Oxide on Aligned Carbon Nanotube Arrays

Microscopic study of the nucleation and growth of atomic layer deposition (ALD) dielectrics onto carbon nanotubes (CNTs) is an essential while challenging task toward high-performance devices. Here, we capture the morphological evolution and growth behaviors of ALD-HfO2 onto SiO2/Si-supported aligned CNT arrays (A-CNTs) under three ALD recipes via cross-sectional high-resolution scanning transmission electron microscopy. The HfO2 in ALD I (200 °C) preferentially nucleates on the SiO2 substrate in heterogeneous growth mode, resulting in films with considerable pinholes, while ALD II (90 °C) and III (90 °C and extra H2O presoak) exhibit homogeneous growth with nucleation on both SiO2 and CNTs, yielding uniform films. Arrangement defects in A-CNTs exacerbate nonuniformity of HfO2 and tube-tube separation plays deterministic roles affecting the HfO2-CNT interfacial morphology. Electrical measurements from A-CNTs metaloxide-semiconductor devices validate these findings. Our investigation contributes valuable insights for optimizing ALD processes for enhanced dielectric integration on A-CNTs in next-generation electronics.

Customization of 2D Atomic-Molecular Heterojunction with Manipulatable Charge-Transfer and Band Structure

Manipulating the properties of 2D materials through meticulously engineered artificial heterojunctions holds great promise for novel device applications. However, existing research on the crucial charge-transfer interactions and energy profile regulation is predominantly focused on 2D van der Waals structures formed via weak van der Waals forces, limiting regulatory efficiency at high costs. Herein, a refined atomic-molecular heterojunction strategy featuring strong covalent bonds between organic molecule and 2D violet phosphorus (VP) atomic crystal is developed, which enables enhanced charge-transfer dynamics and customizable band structure regulation at the molecular level. Both experimentally and theoretically, it is demonstrated that grafting efficiency, charge redistribution, and energy gap regulation critically depend on organic electronegativity, providing a low-cost yet high-efficiency regulatory effect on a large scale. As a proof of concept, the novel VP-molecular heterojunctions exhibit optimized performance in diverse application domains, presenting a general platform for future high-performance device applications.

An overview of critical applications of resistive random access memory

The rapid advancement of new technologies has resulted in a surge of data, while conventional computers are nearing their computational limits. The prevalent von Neumann architecture, where processing and storage units operate independently, faces challenges such as data migration through buses, leading to decreased computing speed and increased energy loss. Ongoing research aims to enhance computing capabilities through the development of innovative chips and the adoption of new system architectures. One noteworthy advancement is Resistive Random Access Memory (RRAM), an emerging memory technology. RRAM can alter its resistance through electrical signals at both ends, retaining its state even after power-down. This technology holds promise in various areas, including logic computing, neural networks, brain-like computing, and integrated technologies combining sensing, storage, and computing. These cutting-edge technologies offer the potential to overcome the performance limitations of traditional architectures, significantly boosting computing power. This discussion explores the physical mechanisms, device structure, performance characteristics, and applications of RRAM devices. Additionally, we delve into the potential future adoption of these technologies at an industrial scale, along with prospects and upcoming research directions.

Insight into Facile Ion Diffusion in Resistive Switching Medium toward Low Operating Voltage Memory

The rapid increase in data storage worldwide demands a substantial amount of energy consumption annually. Studies looking at low power consumption accompanied by high-performance memory are essential for next-generation memory. Here, Graphdiyne oxide (GDYO), characterized by facile resistive switching behavior, is systematically reported toward a low switching voltage memristor. The intrinsic large, homogeneous pore-size structure in GDYO facilitates ion diffusion processes, effectively suppressing the operating voltage. The theoretical approach highlights the remarkably low diffusion energy of the Ag ion (0.11 eV) and oxygen functional group (0.6 eV) within three layers of GDYO. The Ag/GDYO/Au memristor exhibits an ultralow operating voltage of 0.25 V with a GDYO thickness of 5 nm; meanwhile, the thicker GDYO of 29 nm presents multilevel memory with an ON/OFF ratio of up to 104. The findings shed light on memory resistive switching behavior, facilitating future improvements in GDYO-based devices toward opto-memristors, artificial synapses, and neuromorphic applications.

High-performance flexible resistive random-access memory based on SnS2 quantum dots with a charge trapping/de-trapping effect

The application of resistive random-access memory (RRAM) in storage and neuromorphic computing has attracted widespread attention. Benefitting from the quantum effect, transition metal dichalcogenides (TMD) quantum dots (QDs) exhibit distinctive optical and electronic properties, which make them promising candidates for emerging RRAM. Here, we show a high-performance forming-free flexible RRAM based on high-quality tin disulfide (SnS2) QDs prepared by a facile liquid phase method. The RRAM device demonstrates high flexibility with a large on/off ratio of ∼106 and a long retention time of over 3 × 104 s. The excellent switching behavior of the memristor is elucidated by a charge trapping/de-trapping mechanism where the SnS2 QDs act as charge trapping centers. This study is of significance for the understanding and development of TMD QD-based flexible memristors.

Resistive Memory Devices at the Thinnest Limit: Progress and Challenges

The Si-based integrated circuits industry has been developing for more than half a century, by focusing on the scaling-down of transistor. However, the miniaturization of transistors will soon reach its physical limits, thereby requiring novel material and device technologies. Resistive memory is a promising candidate for in-memory computing and energy-efficient synaptic devices that can satisfy the computational demands of the future applications. However, poor cycle-to-cycle and device-to-device uniformities hinder its mass production. 2D materials, as a new type of semiconductor, is successfully employed in various micro/nanoelectronic devices and have the potential to drive future innovation in resistive memory technology. This review evaluates the potential of using the thinnest advanced materials, that is, monolayer 2D materials, for memristor or memtransistor applications, including resistive switching behavior and atomic mechanism, high-frequency device performances, and in-memory computing/neuromorphic computing applications. The scaling-down advantages of promising monolayer 2D materials including graphene, transition metal dichalcogenides, and hexagonal boron nitride are presented. Finally, the technical challenges of these atomic devices for practical applications are elaborately discussed. The study of monolayer-2D-material-based resistive memory is expected to play a positive role in the exploration of beyond-Si electronic technologies.

First-Principles Prediction of High and Low Resistance States in Ta/h-BN/Ta Atomristor

Two-dimensional (2D) materials have received significant attention for their potential use in next-generation electronics, particularly in nonvolatile memory and neuromorphic computing. This is due to their simple metal-insulator-metal (MIM) sandwiched structure, excellent switching performance, high-density capability, and low power consumption. In this work, using comprehensive material simulations and device modeling, the thinnest monolayer hexagonal boron nitride (h-BN) atomristor is studied by using a MIM configuration with Ta electrodes. Our first-principles calculations predicted both a high resistance state (HRS) and a low resistance state (LRS) in this device. We observed that the presence of van der Waals (vdW) gaps between the Ta electrodes and monolayer h-BN with a boron vacancy (VB) contributes to the HRS. The combination of metal electrode contact and the adsorption of Ta atoms onto a single VB defect (TaB) can alter the interface barrier between the electrode and dielectric layer, as well as create band gap states within the band gap of monolayer h-BN. These band gap states can shorten the effective tunneling path for electron transport from the left electrode to the right electrode, resulting in an increase in the current transmission coefficient of the LRS. This resistive switching mechanism in monolayer h-BN atomristors can serve as a theoretical reference for device design and optimization, making them promising for the development of atomristor technology with ultra-high integration density and ultra-low power consumption.

Ultra-fast switching memristors based on two-dimensional materials

The ability to scale two-dimensional (2D) material thickness down to a single monolayer presents a promising opportunity to realize high-speed energy-efficient memristors. Here, we report an ultra-fast memristor fabricated using atomically thin sheets of 2D hexagonal Boron Nitride, exhibiting the shortest observed switching speed (120 ps) among 2D memristors and low switching energy (2pJ). Furthermore, we study the switching dynamics of these memristors using ultra-short (120ps-3ns) voltage pulses, a frequency range that is highly relevant in the context of modern complementary metal oxide semiconductor (CMOS) circuits. We employ statistical analysis of transient characteristics to gain insights into the memristor switching mechanism. Cycling endurance data confirms the ultra-fast switching capability of these memristors, making them attractive for next generation computing, storage, and Radio-Frequency (RF) circuit applications.

Volatile and Nonvolatile Resistive Switching Coexistence in Conductive Point Hexagonal Boron Nitride Monolayer

Recently, we demonstrated the nonvolatile resistive switching effects of metal-insulator-metal (MIM) atomristor structures based on two-dimensional (2D) monolayers. However, there are many remaining combinations between 2D monolayers and metal electrodes; hence, there is a need to further explore 2D resistance switching devices from material selections to future perspectives. This study investigated the volatile and nonvolatile switching coexistence of monolayer hexagonal boron nitride (h-BN) atomristors using top and bottom silver (Ag) metal electrodes. Utilizing an h-BN monolayer and Ag electrodes, we found that the transition between volatile and nonvolatile switching is attributed to the thickness/stiffness of chain-like conductive bridges between h-BN and Ag surfaces based on the current compliance and atomristor area. Computations indicate a "weak" bridge is responsible for volatile switching, while a "strong" bridge is formed for nonvolatile switching. The current compliance determines the number of Ag atoms that undergo dissociation at the electrode, while the atomristor area determines the degree of electric field localization that forms more stable conductive bridges. The findings of this study suggest that the h-BN atomristor using Ag electrodes shows promise as a potential solution to integrate both volatile neurons and nonvolatile synapses in a single neuromorphic crossbar array structure through electrical and dimensional designs.

Bipolar Resistive Switching in 2D MoSe2 Grown by Atmospheric Pressure Chemical Vapor Deposition

Two-dimensional (2D) transition metal dichalcogenides (TMDCs) are highly promising nanomaterials for various electronic devices such as field-effect transistors, junction diodes, tunneling devices, and, more recently, memristors. 2D MoSe2 stands out for having high electrical conductivity, charge carrier mobility, and melting point. While these features make it particularly appropriate as a switching layer in memristive devices, reliable and scalable production of large-area 2D MoSe2 still represents a challenge. In this study, we manufacture 2D MoSe2 films by atmospheric-pressure chemical vapor deposition and investigate them on the atomic scale. We selected and transferred MoSe2 bilayer to serve as a switching layer between asymmetric Au-Cu electrodes in miniaturized crossbar vertical memristors. The electrochemical metallization devices showed forming-free, bipolar resistive switching at low voltages, with clearly identifiable nonvolatile states. Other than low-power neuromorphic computing, low switching voltages approaching the range of biological action potentials could unlock hybrid biological interfaces.

Solution-Processed Robust Multifunctional Memristor of 2D Layered Material Thin Film

Memristors have gained significant attention recently due to their unique ability to exhibit functionalities for brain-inspired neuromorphic computing. Here, we demonstrate a high-performance multifunctional memristor using a thin film of liquid-phase exfoliated (LPE) 2D MoS2 pinched between two electrodes. Nanoscale inspection of a solution-processed MoS2 thin film using scanning electron and scanning probe microscopies revealed the high-quality and defect-free nature. Systematic current-voltage (I-V) characterizations depict a facile, nonvolatile resistive switching behavior of our 2D MoS2 thin film device with a current On/Off ratio of 103 and energy cost of only a few picojoules. Excellent performance metrics, including at least 103 cycle endurance, 104 s retention, and switching speed down to a few nanoseconds, reflect robust high-performance data storage capability. Charge carriers trapping and detrapping at the sulfur vacancy defect sites in MoS2 nanosheets mainly display the resistive switching property, supported by the impedance analysis and theoretical fitting results. Multifunctionality is leveraged through implementing two-input logic gate operations, edge computation, and crucial adaptive learning via a Pavlov's dogs experiment. Overall, our solution-processed MoS2 memristor has the potential for tremendous future opportunities in integrated circuits and different computing paradigms, including energy-efficient neuromorphic computing hardware in artificial intelligence.

Photoluminescence Enhancement of Monolayer WS2 by n-Doping with an Optically Excited Gold Disk

In nanophotonics and quantum optics, we aim to control and manipulate light with tailored nanoscale structures. Hybrid systems of nanostructures and atomically thin materials are of interest here, as they offer rich physics and versatility due to the interaction between photons, plasmons, phonons, and excitons. In this study, we explore the optical and electronic properties of a hybrid system, a naturally n-doped monolayer WS2 covering a gold disk. We demonstrate that the nonresonant excitation of the gold disk in the high absorption regime efficiently generates hot carriers via localized surface plasmon excitation, which n-dope the monolayer WS2 and enhance the photoluminescence emission by regulating the multiexciton population and stabilizing the neutral exciton emission. The results are relevant to the further development of nanotransistors in photonic circuits and optoelectronic applications.

0D van der Waals interfacial ferroelectricity

The dimensional limit of ferroelectricity has been long explored. The critical contravention is that the downscaling of ferroelectricity leads to a loss of polarization. This work demonstrates a zero-dimensional ferroelectricity by the atomic sliding at the restrained van der Waals interface of crossed tungsten disufilde nanotubes. The developed zero-dimensional ferroelectric diode in this work presents not only non-volatile resistive memory, but also the programmable photovoltaic effect at the visible band. Benefiting from the intrinsic dimensional limitation, the zero-dimensional ferroelectric diode allows electrical operation at an ultra-low current. By breaking through the critical size of depolarization, this work demonstrates the ultimately downscaled interfacial ferroelectricity of zero-dimensional, and contributes to a branch of devices that integrates zero-dimensional ferroelectric memory, nano electro-mechanical system, and programmable photovoltaics in one.

Non-volatile resistive switching mechanism in single-layer MoS2 memristors: insights from ab initio modelling of Au and MoS2 interfaces

Non-volatile memristive devices based on two-dimensional (2D) layered materials provide an attractive alternative to conventional flash memory chips. Single-layer semiconductors, such as monolayer molybdenum disulphide (ML-MoS2), enable the aggressive downscaling of devices towards greater system integration density. The "atomristor", the most compact device to date, has been shown to undergo a resistive switching between its high-resistance (HRS) and low-resistance (LRS) states of several orders of magnitude. The main hypothesis behind its working mechanism relies on the migration of sulphur vacancies in the proximity of the metal contact during device operation, thus inducing the variation of the Schottky barrier at the metal-semiconductor interface. However, the interface physics is not yet fully understood: other hypotheses were proposed, involving the migration of metal atoms from the electrode. In this work, we aim to elucidate the mechanism of the resistive switching in the atomristor. We carry out density functional theory (DFT) simulations on model Au and ML-MoS2 interfaces with and without the presence of point defects, either vacancies or substitutions. To construct realistic interfaces, we combine DFT with Green's function surface simulations. Our findings reveal that it is not the mere presence of S vacancies but rather the migration of Au atoms from the electrode to MoS2 that modulate the interface barrier. Indeed, Au atoms act as conductive "bridges", thus facilitating the flow of charge between the two materials.

Criticality and Neuromorphic Sensing in a Single Memristor

Resistive random access memory (RRAM) is an important technology for both data storage and neuromorphic computation, where the dynamics of nanoscale conductive filaments lies at the core of the technology. Here, we analyze the current noise of various silicon-based memristors that involves the creation of a percolation path at the intermediate phase of filament growth. Remarkably, we find that these atomic switching events follow scale-free avalanche dynamics with exponents satisfying the criteria for criticality. We further prove that the switching dynamics are universal and show little dependence on device sizes or material features. Utilizing criticality in memristors, we simulate the functionality of hair cells in auditory sensory systems by observing the frequency selectivity of input stimuli with tunable characteristic frequency. We further demonstrate a single-memristor-based sensing primitive for representation of input stimuli that exceeds the theoretical limits dictated by the Nyquist-Shannon theorem.

Nonlinear restructuring of patterned thin films by residual stress engineering into out-of-plane wavy-shaped electrostatic microactuators for high-performance radio-frequency switches

Electrostatic microelectromechanical (MEMS) switches are the basic building blocks for various radio-frequency (RF) transceivers. However, conventional cantilever-based designs of MEMS switches require a large actuation voltage, exhibit limited RF performance, and suffer from many performance tradeoffs due to their flat geometries restricted in two dimensions (2D). Here, by leveraging the residual stress in thin films, we report a novel development of three-dimensional (3D) wavy microstructures, which offer the potential to serve as high-performance RF switches. Relying on standard IC-compatible metallic materials, we devise a simple fabrication process to repeatedly manufacture out-of-plane wavy beams with controllable bending profiles and yields reaching 100%. We then demonstrate the utility of such metallic wavy beams as RF switches achieving both extremely low actuation voltage and improved RF performance owing to their unique geometry, which is tunable in three dimensions and exceeds the capabilities of current state-of-the-art flat-cantilever switches with 2D-restricted topology. As such, the wavy cantilever switch presented in this work actuates at voltages as low as 24 V while simultaneously exhibiting RF isolation and insertion loss of 20 dB and 0.75 dB, respectively, for frequencies up to 40 GHz. Wavy switch designs with 3D geometries break through the design limits set by traditional flat cantilevers and provide an additional degree of freedom or control knob in the switch design process, which could enable further optimization of switching networks used in current 5G and upcoming 6G communication scenarios.

Research progress in architecture and application of RRAM with computing-in-memory

The development of new technologies has led to an explosion of data, while the computation ability of traditional computers is approaching its upper limit. The dominant system architecture is the von Neumann architecture, with the processing and storage units working independently. The data migrate between them via buses, reducing computing speed and increasing energy loss. Research is underway to increase computing power, such as developing new chips and adopting new system architectures. Computing-in-memory (CIM) technology allows data to be computed directly on the memory, changing the current computation-centric architecture and designing a new storage-centric architecture. Resistive random access memory (RRAM) is one of the advanced memories which has appeared in recent years. RRAM can change its resistance with electrical signals at both ends, and the state will be preserved after power-down. It has potential in logic computing, neural networks, brain-like computing, and fused technology of sense-storage-computing. These advanced technologies promise to break the performance bottleneck of traditional architectures and dramatically increase computing power. This paper introduces the basic concepts of computing-in-memory technology and the principle and applications of RRAM and finally gives a conclusion about these new technologies.

Fully Optical in Operando Investigation of Ambient Condition Electrical Switching in MoS2 Nanodevices

MoS₂ nanoswitches have shown superb ultralow switching energies without excessive leakage currents. However, the debate about the origin and volatility of electrical switching is unresolved due to the lack of adequate nanoimaging of devices in operando. Here, three optical techniques are combined to perform the first noninvasive in situ characterization of nanosized MoS₂ devices. This study reveals volatile threshold resistive switching due to the intercalation of metallic atoms from electrodes directly between Mo and S atoms, without the assistance of sulfur vacancies. A "semi-memristive" effect driven by an organic adlayer adjacent to MoS₂ is observed, which suggests that nonvolatility can be achieved by careful interface engineering. These findings provide a crucial understanding of nanoprocess in vertically biased MoS₂ nanosheets, which opens new routes to conscious engineering and optimization of 2D electronics.

Reconfigurable Low-Voltage Hexagonal Boron Nitride Nonvolatile Switches for Millimeter-Wave Wireless Communications

Recently, nonvolatile resistive switching memory effects have been actively studied in two-dimensional (2D) transition metal dichalcogenides and boron nitrides to advance future memory and neuromorphic computing applications. Here, we report on radiofrequency (RF) switches utilizing hexagonal boron nitride (h-BN) memristors that afford operation in the millimeter-wave (mmWave) range. Notably, silver (Ag) electrodes to h-BN offer outstanding nonvolatile bipolar resistive switching characteristics with a high ON/OFF switching ratio of 10¹¹ and low switching voltage below 0.34 V. In addition, the switch exhibits a low insertion loss of 0.50 dB and high isolation of 23 dB across the D-band spectrum (110 to 170 GHz). Furthermore, the S₂₁ insertion loss can be tuned through five orders of current compliance magnitude, which increases the application prospects for atomic switches. These results can enable the switch to become a key component for future reconfigurable wireless and 6G communication systems.

Electronic metadevices for terahertz applications

The evolution of electronics has largely relied on downscaling to meet the continuous needs for faster and highly integrated devices¹. As the channel length is reduced, however, classic electronic devices face fundamental issues that hinder exploiting materials to their full potential and, ultimately, further miniaturization². For example, the carrier injection through tunnelling junctions dominates the channel resistance³, whereas the high parasitic capacitances drastically limit the maximum operating frequency⁴. In addition, these ultra-scaled devices can only hold a few volts due to the extremely high electric fields, which limits their maximum delivered power^5,6. Here we challenge such traditional limitations and propose the concept of electronic metadevices, in which the microscopic manipulation of radiofrequency fields results in extraordinary electronic properties. The devices operate on the basis of electrostatic control of collective electromagnetic interactions at deep subwavelength scales, as an alternative to controlling the flow of electrons in traditional devices, such as diodes and transistors. This enables a new class of electronic devices with cutoff frequency figure-of-merit well beyond ten terahertz, record high conductance values, extremely high breakdown voltages and picosecond switching speeds. This work sets the stage for the next generation of ultrafast semiconductor devices and presents a new paradigm that potentially bridges the gap between electronics and optics.

Hexagonal Boron Nitride for Next-Generation Photonics and Electronics

Hexagonal boron nitride (h-BN), an insulating 2D layered material, has recently attracted tremendous interest motivated by the extraordinary properties it shows across the fields of optoelectronics, quantum optics, and electronics, being exotic material platforms for various applications. At an early stage of h-BN research, it is explored as an ideal substrate and insulating layers for other 2D materials due to its atomically flat surface that is free of dangling bonds and charged impurities, and its high thermal conductivity. Recent discoveries of structural and optical properties of h-BN have expanded potential applications into emerging electronics and photonics fields. h-BN shows a very efficient deep-ultraviolet band-edge emission despite its indirect-bandgap nature, as well as stable room-temperature single-photon emission over a wide wavelength range, showing a great potential for next-generation photonics. In addition, h-BN is extensively being adopted as active media for low-energy electronics, including nonvolatile resistive switching memory, radio-frequency devices, and low-dielectric-constant materials for next-generation electronics.

Integrated Memory Devices Based on 2D Materials

With the advent of the Internet of Things and big data, massive data must be rapidly processed and stored within a short timeframe. This imposes stringent requirements on memory hardware implementation in terms of operation speed, energy consumption, and integration density. To fulfill these demands, 2D materials, which are excellent electronic building blocks, provide numerous possibilities for developing advanced memory device arrays with high performance, smart computing architectures, and desirable downscaling. Over the past few years, 2D-material-based memory-device arrays with different working mechanisms, including defects, filaments, charges, ferroelectricity, and spins, have been increasingly developed. These arrays can be used to implement brain-inspired computing or sensing with extraordinary performance, architectures, and functionalities. Here, recent research into integrated, state-of-the-art memory devices made from 2D materials, as well as their implications for brain-inspired computing are surveyed. The existing challenges at the array level are discussed, and the scope for future research is presented.

Two-dimensional devices and integration towards the silicon lines

Despite technical efforts and upgrades, advances in complementary metal-oxide-semiconductor circuits have become unsustainable in the face of inherent silicon limits. New materials are being sought to compensate for silicon deficiencies, and two-dimensional materials are considered promising candidates due to their atomically thin structures and exotic physical properties. However, a potentially applicable method for incorporating two-dimensional materials into silicon platforms remains to be illustrated. Here we try to bridge two-dimensional materials and silicon technology, from integrated devices to monolithic 'on-silicon' (silicon as the substrate) and 'with-silicon' (silicon as a functional component) circuits, and discuss the corresponding requirements for material synthesis, device design and circuitry integration. Finally, we summarize the role played by two-dimensional materials in the silicon-dominated semiconductor industry and suggest the way forward, as well as the technologies that are expected to become mainstream in the near future.

Neuromorphic device based on silicon nanosheets

Silicon is vital for its high abundance, vast production, and perfect compatibility with the well-established CMOS processing industry. Recently, artificially stacked layered 2D structures have gained tremendous attention via fine-tuning properties for electronic devices. This article presents neuromorphic devices based on silicon nanosheets that are chemically exfoliated and surface-modified, enabling self-assembly into hierarchical stacking structures. The device functionality can be switched between a unipolar memristor and a feasibly reset-able synaptic device. The memory function of the device is based on the charge storage in the partially oxidized SiNS stacks followed by the discharge activated by the electric field at the Au-Si Schottky interface, as verified in both experimental and theoretical means. This work further inspired elegant neuromorphic computation models for digit recognition and noise filtration. Ultimately, it brings silicon - the most established semiconductor - back to the forefront for next-generation computations.

Interface-Modulated Resistive Switching in Mo-Irradiated ReS2 for Neuromorphic Computing

Coupling charge impurity scattering effects and charge-carrier modulation by doping can offer intriguing opportunities for atomic-level control of resistive switching (RS). Nonetheless, such effects have remained unexplored for memristive applications based on 2D materials. Here a facile approach is reported to transform an RS-inactive rhenium disulfide (ReS₂ ) into an effective switching material through interfacial modulation induced by molybdenum-irradiation (Mo-i) doping. Using ReS₂ as a model system, this study unveils a unique RS mechanism based on the formation/dissolution of metallic β-ReO₂ filament across the defective ReS₂ interface during the set/reset process. Through simple interfacial modulation, ReS₂ of various thicknesses are switchable by modulating the Mo-irradiation period. Besides, the Mo-irradiated ReS₂ (Mo-ReS₂ ) memristor further exhibits a bipolar non-volatile switching ratio of nearly two orders of magnitude, programmable multilevel resistance states, and long-term synaptic plasticity. Additionally, the fabricated device can achieve a high MNIST learning accuracy of 91% under a non-identical pulse train. The study's findings demonstrate the potential for modulating RS in RS-inactive 2D materials via the unique doping-induced charged impurity scattering property.

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

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.

Wafer-Scale Synthesis of WS2 Films with In Situ Controllable p-Type Doping by Atomic Layer Deposition

Wafer-scale synthesis of p-type TMD films is critical for its commercialization in next-generation electro/optoelectronics. In this work, wafer-scale intrinsic n-type WS₂ films and in situ Nb-doped p-type WS₂ films were synthesized through atomic layer deposition (ALD) on 8-inch α-Al₂O₃/Si wafers, 2-inch sapphire, and 1 cm² GaN substrate pieces. The Nb doping concentration was precisely controlled by altering cycle number of Nb precursor and activated by postannealing. WS₂ n-FETs and Nb-doped p-FETs with different Nb concentrations have been fabricated using CMOS-compatible processes. X-ray photoelectron spectroscopy, Raman spectroscopy, and Hall measurements confirmed the effective substitutional doping with Nb. The on/off ratio and electron mobility of WS₂ n-FET are as high as 10⁵ and 6.85 cm² V⁻¹ s⁻¹, respectively. In WS₂ p-FET with 15-cycle Nb doping, the on/off ratio and hole mobility are 10 and 0.016 cm² V⁻¹ s⁻¹, respectively. The p-n structure based on n- and p- type WS₂ films was proved with a 10⁴ rectifying ratio. The realization of controllable in situ Nb-doped WS₂ films paved a way for fabricating wafer-scale complementary WS₂ FETs.

Atomic Electrostatic Maps of Point Defects in MoS2

In this study, we use differential phase contrast images obtained by scanning transmission electron microscopy combined with computer simulations to map the atomic electrostatic fields of MoS₂ monolayers and investigate the effect of sulfur monovacancies and divancancies on the atomic electric field and total charge distribution. A significant redistribution of the electric field in the regions containing defects is observed, with a progressive decrease in the strength of the projected electric field for each sulfur atom removed from its position. The electric field strength at the sulfur monovacancy sites is reduced by approximately 50% and nearly vanishes at the divacancy sites, where it drops to around 15% of the original value, demonstrating the tendency of these defects to attract positively charged ions or particles. In addition, the absence of the sulfur atoms leads to an inversion in the polarity of the total charge distribution in these regions.

Stimuli-Responsive Memristive Materials for Artificial Synapses and Neuromorphic Computing

Neuromorphic computing holds promise for building next-generation intelligent systems in a more energy-efficient way than the conventional von Neumann computing architecture. Memristive hardware, which mimics biological neurons and synapses, offers high-speed operation and low power consumption, enabling energy- and area-efficient, brain-inspired computing. Here, recent advances in memristive materials and strategies that emulate synaptic functions for neuromorphic computing are highlighted. The working principles and characteristics of biological neurons and synapses, which can be mimicked by memristive devices, are presented. Besides device structures and operation with different external stimuli such as electric, magnetic, and optical fields, how memristive materials with a rich variety of underlying physical mechanisms can allow fast, reliable, and low-power neuromorphic applications is also discussed. Finally, device requirements are examined and a perspective on challenges in developing memristive materials for device engineering and computing science is given.

Towards High-Performance Resistive Switching Behavior through Embedding a D-A System into 2D Imine-Linked Covalent Organic Frameworks

Developing new materials for the fabrication of resistive random-access memory is of great significance in this period of big data. Herein, we present a novel design strategy of embedding donor (D) and acceptor (A) fragments into imine-linked frameworks to construct resistive switching covalent organic frameworks (COFs) for high-performance memristors. Two D-A-type two-dimensional COFs, COF-BT-TT and COF-TT-TVT, were designed and synthesized using a conventional solvothermal approach, and high-quality thin films of these materials deposited on ITO substrate exhibited great potential as an active layer for memristors. Rewritable memristors based on 100 nm thick COF-TT-BT and COF-TT-TVT films showed a high ON/OFF current ratio (ca. 10⁵ and 10⁴ ) and low driving voltage (1.30 and 1.60 V). The cycle period and retention time for COF-TT-BT-based rewritable devices were as high as 319 cycles and 3.3×10⁴  s at a constant voltage of 0.1 V (160 cycles and 1.2×10⁴  s for the COF-TT-TVT memristor).

A Scalable Artificial Neuron Based on Ultrathin Two-Dimensional Titanium Oxide

A spiking neural network consists of artificial synapses and neurons and may realize human-level intelligence. Unlike the widely reported artificial synapses, the fabrication of large-scale artificial neurons with good performance is still challenging due to the lack of a suitable material system and integration method. Here, we report an ultrathin (less than10 nm) and inch-size two-dimensional (2D) oxide-based artificial neuron system produced by a controllable assembly of solution-processed 2D monolayer TiO_x nanosheets. Artificial neuron devices based on such 2D TiO_x films show a high on/off ratio of 10⁹ and a volatile resistance switching phenomenon. The devices can not only emulate the leaky integrate-and-fire activity but also self-recover without additional circuits for sensing and reset. Moreover, the artificial neuron arrays are fabricated and exhibited good uniformity, indicating their large-area integration potential. Our results offer a strategy for fabricating large-scale and ultrathin 2D material-based artificial neurons and 2D spiking neural networks.

Resistance Switching and Failure Behavior of the MoOx/Mo2C Heterostructure

With the rapid demand for high-performance and power-efficient memristive and synaptic systems, more 2D heterostructures with improved resistance switching (RS) properties are still urgently in need for next-generation devices. Here, we report the RS behaviors of vertical MoO_x/Mo₂C heterostructures fabricated by controllable thermal oxidation and uncover the failure behavior for the first time. It is found that the MoO_x/Mo₂C heterostructure exhibits bipolar RS with a low set/reset voltage of +0.5/-0.3 V, an ultralow power consumption of 5 × 10^-8 W, and an on/off ratio of 10², which is ascribed to the transport of the internal oxygen ions of MoO_x. Furthermore, the failure behavior of RS behaviors of the MoO_x/Mo₂C heterostructure under a higher work voltage is revealed. It indicates that the amorphization of the pristine crystalline MoO_x layer could block the movement of the internal oxygen ions in the vertical direction. The excellent RS performance induced by the synergy of MoO_x and Mo₂C and the demonstration of the failure behavior enable the potential applications of the 2D heterostructure in related memory devices and biological neural networks.

Realization of a non-markov chain in a single 2D mineral RRAM

The non-Markov process exists widely in thermodymanic process, while it usually requires the packing of many transistors and memories with great system complexity in a traditional device structure to minic such functions. Two-dimensional (2D) material-based resistive random access memory (RRAM) devices have the potential for next-generation computing systems with much-reduced complexity. Here, we achieve a non-Markov chain in an individual RRAM device based on 2D mineral material mica with a vertical metal/mica/metal structure. We find that the potassium ions (K⁺) in 2D mica gradually move in the direction of the applied electric field, making the initially insulating mica conductive. The accumulation of K⁺ is changed by an electric field, and the 2D-mica RRAM has both single and double memory windows, a high on/off ratio, decent stability, and repeatability. This is the first time a non-Markov chain process has been established in a single RRAM, in which the movement of K⁺ is dependent on the stimulated voltage as well as their past states. This work not only uncovers an intrinsic inner ionic conductivity of 2D mica, but also opens the door for the production of such RRAM devices with numerous functions and applications.

Recent developments in 2D transition metal dichalcogenides: phase transition and applications of the (quasi-)metallic phases

The advent of two-dimensional transition metal dichalcogenides (2D-TMDs) has led to an extensive amount of interest amongst scientists and engineers alike and an intensive amount of research has brought about major breakthroughs in the electronic and optical properties of 2D materials. This in turn has generated considerable interest in novel device applications. With the polymorphic structural features of 2D-TMDs, this class of materials can exhibit both semiconducting and metallic (quasi-metallic) properties in their respective phases. This polymorphic property further increases the interest in 2D-TMDs both in fundamental research and for their potential utilization in novel high-performance device applications. In this review, we highlight the unique structural properties of few-layer and monolayer TMDs in the metallic 1T- and quasi-metallic 1T'-phases, and how these phases dictate their electronic and optical properties. An overview of the semiconducting-to-(quasi)-metallic phase transition of 2D-TMD systems will be covered along with a discussion on the phase transition mechanisms. The current development in the applications of (quasi)-metallic 2D-TMDs will be presented ranging from high-performance electronic and optoelectronic devices to energy storage, catalysis, piezoelectric and thermoelectric devices, and topological insulator and neuromorphic computing applications. We conclude our review by highlighting the challenges confronting the utilization of TMD-based systems and projecting the future developmental trends with an outlook of the progress needed to propel this exciting field forward.

Low-Power Memristive Logic Device Enabled by Controllable Oxidation of 2D HfSe2 for In-Memory Computing

Memristive logic device is a promising unit for beyond von Neumann computing systems and 2D materials are widely used because of their controllable interfacial properties. Most of these 2D memristive devices, however, are made from semiconducting chalcogenides which fail to gate the off-state current. To this end, a crossbar device using 2D HfSe2 is fabricated, and then the top layers are oxidized into "high-k" dielectric HfSex Oy via oxygen plasma treatment, so that the cell resistance can be remarkably increased. This two-terminal Ti/HfSex Oy /HfSe2 /Au device exhibits excellent forming-free resistive switching performance with high switching speed (<50 ns), low operation voltage (<3 V), large switching window (103 ), and good data retention. Most importantly, the operation current and the power consumption reach 100 pA and 0.1 fJ to 0.1 pJ, much lower than other HfO based memristors. A functionally complete low-power Boolean logic is experimentally demonstrated using the memristive device, allowing it in the application of energy-efficient in-memory computing.

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

Memristors are regarded as one of the key devices to break through the traditional Von Neumann computer architecture due to their capability of simulating the function of neural synapses. Among various memristive materials, two-dimensional (2D) materials are promising candidates to build advanced memristors with extremely high integration density and low power consumption. However, memristors based on 2D materials usually suffer from poor endurance and retention due to their vulnerability to material degradation during the formation/fusing processes of conductive filament channels within the switching media of 2D materials. Here, a new memristor architecture based on a WS2/MoS2 2D semiconducting heterojunction (metal/heterojunction/metal, MHM) is proposed, which is completely different from the conventional metal/insulator/metal (MIM) sandwich structure. Through the introduction of a type-II 2D heterojunction, a resistance switching mechanism based on band modulation rather than the conductive filaments can be realized to eliminate the material degradation during the set/reset processes. A prototype MHM memristor based on the WS2/MoS2 heterojunction is successfully developed with a large switching on/off ratio up to 104 and a clearly extended endurance over 120 switching cycles, showing the advantage of the 2D WS2/MoS2 heterojunction over the individual MoS2 or WS2 layers in memristive performance. The proposed method for the MHM-type 2D memristor has the potential to achieve a large-scale integrated memristor matrix with low power consumption and high integration density, which is promising for future artificial intelligence and brain-like computing systems.

Perspectives on Atomic-Scale Switches for High-Frequency Applications Based on Nanomaterials

Nanomaterials science is becoming the foundation stone of high-frequency applications. The downscaling of electronic devices and components allows shrinking chip’s dimensions at a more-than-Moore rate. Many theoretical limits and manufacturing constraints are yet to be taken into account. A promising path towards nanoelectronics is represented by atomic-scale materials. In this manuscript, we offer a perspective on a specific class of devices, namely switches designed and fabricated using two-dimensional or nanoscale materials, like graphene, molybdenum disulphide, hexagonal boron nitride and ultra-thin oxides for high-frequency applications. An overview is provided about three main types of microwave and millimeter-wave switch: filament memristors, nano-ionic memristors and ferroelectric junctions. The physical principles that govern each switch are presented, together with advantages and disadvantages. In the last part we focus on zirconium-doped hafnium oxide ferroelectrics (HfZrO) tunneling junctions (FTJ), which are likely to boost the research in the domain of atomic-scale materials applied in engineering sciences. Thanks to their Complementary Metal-Oxide Semiconductor (CMOS) compatibility and low-voltage tunability (among other unique physical properties), HfZrO compounds have the potential for large-scale applicability. As a practical case of study, we present a 10 GHz transceiver in which the switches are FTJs, which guarantee excellent isolation and ultra-fast switching time.

A Library of Atomically Thin 2D Materials Featuring the Conductive-Point Resistive Switching Phenomenon

Non-volatile resistive switching (NVRS) is a widely available effect in transitional metal oxides, colloquially known as memristors, and of broad interest for memory technology and neuromorphic computing. Until recently, NVRS was not known in other transitional metal dichalcogenides (TMDs), an important material class owing to their atomic thinness enabling the ultimate dimensional scaling. Here, various monolayer or few-layer 2D materials are presented in the conventional vertical structure that exhibit NVRS, including TMDs (MX₂ , M = transitional metal, e.g., Mo, W, Re, Sn, or Pt; X = chalcogen, e.g., S, Se, or Te), TMD heterostructure (WS₂ /MoS₂ ), and an atomically thin insulator (h-BN). These results indicate the universality of the phenomenon in 2D non-conductive materials, and feature low switching voltage, large ON/OFF ratio, and forming-free characteristic. A dissociation-diffusion-adsorption model is proposed, attributing the enhanced conductance to metal atoms/ions adsorption into intrinsic vacancies, a conductive-point mechanism supported by first-principle calculations and scanning tunneling microscopy characterizations. The results motivate further research in the understanding and applications of defects in 2D materials.

In Situ Resistive Switching Effect Scrutinization on Co-Designed Graphene Sensor

Resistive switching (RS), an electric property based on the forming and rupture of conductive filaments in metal-insulator-metal structures, has attracted intensive attention due to its potential application in next generation energy-efficient and area-efficient memory devices. In situ studies of the RS effect are urgently needed for its mechanism understanding and memristive performance improvement. Here investigations of both the RS effect as well as the gate tunable conductance quantization effect are realized by co-designing an Ag/SiO₂ based memory structure on a graphene local sensor. This design enables self-monitoring of the working states of the memristor in real-time by virtue of the graphene sensor. These findings pave the way for further investigations of on-chip electronics and quantum physics.

Observation of single-defect memristor in an MoS2 atomic sheet

Non-volatile resistive switching, also known as memristor¹ effect, where an electric field switches the resistance states of a two-terminal device, has emerged as an important concept in the development of high-density information storage, computing and reconfigurable systems^2-9. The past decade has witnessed substantial advances in non-volatile resistive switching materials such as metal oxides and solid electrolytes. It was long believed that leakage currents would prevent the observation of this phenomenon for nanometre-thin insulating layers. However, the recent discovery of non-volatile resistive switching in two-dimensional monolayers of transition metal dichalcogenide^10,11 and hexagonal boron nitride¹² sandwich structures (also known as atomristors) has refuted this belief and added a new materials dimension owing to the benefits of size scaling^10,13. Here we elucidate the origin of the switching mechanism in atomic sheets using monolayer MoS₂ as a model system. Atomistic imaging and spectroscopy reveal that metal substitution into a sulfur vacancy results in a non-volatile change in the resistance, which is corroborated by computational studies of defect structures and electronic states. These findings provide an atomistic understanding of non-volatile switching and open a new direction in precision defect engineering, down to a single defect, towards achieving the smallest memristor for applications in ultra-dense memory, neuromorphic computing and radio-frequency communication systems^2,3,11.

Roadmap on emerging hardware and technology for machine learning

Recent progress in artificial intelligence is largely attributed to the rapid development of machine learning, especially in the algorithm and neural network models. However, it is the performance of the hardware, in particular the energy efficiency of a computing system that sets the fundamental limit of the capability of machine learning. Data-centric computing requires a revolution in hardware systems, since traditional digital computers based on transistors and the von Neumann architecture were not purposely designed for neuromorphic computing. A hardware platform based on emerging devices and new architecture is the hope for future computing with dramatically improved throughput and energy efficiency. Building such a system, nevertheless, faces a number of challenges, ranging from materials selection, device optimization, circuit fabrication and system integration, to name a few. The aim of this Roadmap is to present a snapshot of emerging hardware technologies that are potentially beneficial for machine learning, providing the Nanotechnology readers with a perspective of challenges and opportunities in this burgeoning field.

Resistance state evolution under constant electric stress on a MoS2 non-volatile resistive switching device

MoS₂ has been reported to exhibit a resistive switching phenomenon in a vertical metal–insulator–metal (MIM) structure and has attracted much attention due to its ultra-thin active layer thickness. Here, the resistance evolutions in the high resistance state (HRS) and low resistance state (LRS) are investigated under constant voltage stress (CVS) or constant current stress (CCS) on MoS₂ resistive switching devices. Interestingly, compared with bulk transition metal oxides (TMO), MoS₂ exhibits an opposite characteristic in the fresh or pre-RESET device in the “HRS” wherein the resistance will increase to an even higher resistance after applying CVS, a unique phenomenon only accessible in 2D-based resistive switching devices. It is inferred that instead of in the highest resistance state, the fresh or pre-RESET devices are in an intermediate state with a small amount of Au embedded in the MoS₂ film. Inspired by the capability of both bipolar and unipolar operation, positive and negative CVS measurements are performed and show similar characteristics. In addition, it is observed that the resistance state transition is faster when using higher electric stress. Numerical simulations have been performed to study the temperature effect with small-area integration capability. These results can be explained by a modified conductive-bridge-like model based on Au migration, uncovering the switching mechanisms in the ultrathin 2D materials and inspiring future studies in this area.

Constant voltage and current stress were applied on MoS₂ resistive switching devices, showing unique behaviors explained by a modified conductive-bridge-like model.

Understanding of multiple resistance states by current sweeping in MoS2-based non-volatile memory devices

Recently, various two-dimensional materials have been reported to exhibit non-volatile resistance switching phenomenon. The atomristors, featuring memristor effect in atomically thin nanomaterials such as monolayer transition metal dichalcogenides and hexagonal boron nitride, have drawn much attention due to the extremely thin active layer thickness with the advantages of forming-free characteristic, large on/off resistance ratio and fast switching speed. To investigate the switching mechanisms in the 2D monolayers, we introduced an electrical characterization method by current sweeping to illustrate the detailed information hidden in the commonly used voltage-sweep curves. Multiple transition steps have been observed in the SET process of MoS₂-based resistance switching devices. The different behaviors of transition steps were attributed to the number of defects or vacancies associated with the switching phenomenon, which is consistent with the previously reported conductive-bridge-like model for 2D atomristors. This work provides an approach using current sweeping to precisely characterize the resistance switching effect and inspires further research to optimize the defect distribution in 2D materials for the applications in multi-bit non-volatile memory and neuromorphic computing.

Machine Learning-Enabled Design of Point Defects in 2D Materials for Quantum and Neuromorphic Information Processing

Engineered point defects in two-dimensional (2D) materials offer an attractive platform for solid-state devices that exploit tailored optoelectronic, quantum emission, and resistive properties. Naturally occurring defects are also unavoidably important contributors to material properties and performance. The immense variety and complexity of possible defects make it challenging to experimentally control, probe, or understand atomic-scale defect-property relationships. Here, we develop an approach based on deep transfer learning, machine learning, and first-principles calculations to rapidly predict key properties of point defects in 2D materials. We use physics-informed featurization to generate a minimal description of defect structures and present a general picture of defects across materials systems. We identify over one hundred promising, unexplored dopant defect structures in layered metal chalcogenides, hexagonal nitrides, and metal halides. These defects are prime candidates for quantum emission, resistive switching, and neuromorphic computing.

Composition-Gradient-Mediated Semiconductor-Metal Transition in Ternary Transition-Metal-Dichalcogenide Bilayers

The semiconductor-metal transition (SMT) enables multiple applications of one single material, especially in modern devices. How to control it remains one of the most intriguing questions in material physics/chemistry, especially in two-dimensional layered materials. In this work, we report realization of SMT in MoS_2-xO_x bilayers, driven by the concentration gradient of the chalcogen atom across the van der Waals (vdW) gap of the disordered bilayers. Using the cluster expansion method, we determined that either semiconducting (stable) or metallic states (metastable) can be realized in MoS_2-xO_x bilayers with the same composition. Machine learning analysis revealed that the concentration gradient of the chalcogen atom across the vdW gap is the leading fingerprint of SMT, with structural distortion induced by atom mixing being a significant secondary factor. The electronic origin of the SMT is the broadening of the Mo d_z² and O p_z bands, accompanied by the redistribution of the d electrons. This in-vdW-gap composition-gradient-driven SMT phenomenon also applies to MoSe_2-xO_x and MoTe_2-xO_x bilayers. The present work provides an alternative mechanism of SMT and demonstrates that the composition gradient across the vdW gap in the bilayer materials can be another degree of freedom to tune the band gaps without introducing extrinsic elements. Our findings will benefit the material design for small-scale and energy-efficient electronic devices.

Programmable electronic synapse and nonvolatile resistive switches using MoS2 quantum dots

Brain-inspired computation that mimics the coordinated functioning of neural networks through multitudes of synaptic connections is deemed to be the future of computation to overcome the classical von Neumann bottleneck. The future artificial intelligence circuits require scalable electronic synapse (e-synapses) with very high bit densities and operational speeds. In this respect, nanostructures of two-dimensional materials serve the purpose and offer the scalability of the devices in lateral and vertical dimensions. In this work, we report the nonvolatile bipolar resistive switching and neuromorphic behavior of molybdenum disulfide (MoS2) quantum dots (QD) synthesized using liquid-phase exfoliation method. The ReRAM devices exhibit good resistive switching with an On-Off ratio of 104, with excellent endurance and data retention at a smaller read voltage as compared to the existing MoS2 based memory devices. Besides, we have demonstrated the e-synapse based on MoS2 QD. Similar to our biological synapse, Paired Pulse Facilitation / Depression of short-term memory has been observed in these MoS2 QD based e-synapse devices. This work suggests that MoS2 QD has potential applications in ultra-high-density storage as well as artificial intelligence circuitry in a cost-effective way.

Memtransistors Based on Nanopatterned Graphene Ferroelectric Field-Effect Transistors

The ultimate memristor, which acts as resistive memory and an artificial neural synapse, is made from a single atomic layer. In this manuscript, we present experimental evidence of the memristive properties of a nanopatterned ferroelectric graphene field-effect transistor (FET). The graphene FET has, as a channel, a graphene monolayer transferred onto an HfO₂-based ferroelectric material, the channel being nanopatterned with an array of holes with a diameter of 20 nm.

Interface engineering of two-dimensional transition metal dichalcogenides towards next-generation electronic devices: recent advances and challenges

Over the past decade, two-dimensional (2D) transition metal dichalcogenides (TMDCs) have attracted tremendous research interest for future electronics owing to their atomically thin thickness, compelling properties and various potential applications. However, interface engineering including contact optimization and channel modulations for 2D TMDCs represents fundamental challenges in ultimate performance of ultrathin electronics. This article provides a comprehensive overview of the basic understanding of contacts and channel engineering of 2D TMDCs and emerging electronics benefiting from these varying approaches. In particular, we elucidate multifarious contact engineering approaches such as edge contact, phase engineering and metal transfer to suppress the Fermi level pinning effect at the metal/TMDC interface, various channel treatment avenues such as van der Waals heterostructures, surface charge transfer doping to modulate the device properties, and as well the novel electronics constructed by interface engineering such as diodes, circuits and memories. Finally, we conclude this review by addressing the current challenges facing 2D TMDCs towards next-generation electronics and offering our insights into future directions of this field.