A High-On/Off-Ratio Floating-Gate Memristor Array on a Flexible Substrate via CVD-Grown Large-Area 2D Layer Stacking

Versatile Nanoscale Three-Terminal Memristive Switch Enabled by Gating

A three-terminal memristor with an ultrasmall footprint of only 0.07 μm2 and critical dimensions of 70 nm × 10 nm × 6 nm is introduced. The device's feature is the presence of a gate contact, which enables two operation modes: either tuning the set voltage or directly inducing a resistance change. In I-V mode, we demonstrate that by changing the gate voltages between ±1 V one can shift the set voltage by 69%. In pulsing mode, we show that resistance change can be triggered by a gate pulse. Furthermore, we tested the device endurance under a 1 kHz operation. In an experiment with 2.6 million voltage pulses, we found two distinct resistance states. The device response to a pseudorandom bit sequence displays an open eye diagram and a success ratio of 97%. Our results suggest that this device concept is a promising candidate for a variety of applications ranging from Internet-of-Things to neuromorphic computing.

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.

Hydrogel-Gated FETs in Neuromorphic Computing to Mimic Biological Signal: A Review

Hydrogel-gated synaptic transistors offer unique advantages, including biocompatibility, tunable electrical properties, being biodegradable, and having an ability to mimic biological synaptic plasticity. For processing massive data with ultralow power consumption due to high parallelism and human brain-like processing abilities, synaptic transistors have been widely considered for replacing von Neumann architecture-based traditional computers due to the parting of memory and control units. The crucial components mimic the complex biological signal, synaptic, and sensing systems. Hydrogel, as a gate dielectric, is the key factor for ionotropic devices owing to the excellent stability, ultra-high linearity, and extremely low operating voltage of the biodegradable and biocompatible polymers. Moreover, hydrogel exhibits ionotronic functions through a hybrid circuit of mobile ions and mobile electrons that can easily interface between machines and humans. To determine the high-efficiency neuromorphic chips, the development of synaptic devices based on organic field effect transistors (OFETs) with ultra-low power dissipation and very large-scale integration, including bio-friendly devices, is needed. This review highlights the latest advancements in neuromorphic computing by exploring synaptic transistor developments. Here, we focus on hydrogel-based ionic-gated three-terminal (3T) synaptic devices, their essential components, and their working principle, and summarize the essential neurodegenerative applications published recently. In addition, because hydrogel-gated FETs are the crucial members of neuromorphic devices in terms of cutting-edge synaptic progress and performances, the review will also summarize the biodegradable and biocompatible polymers with which such devices can be implemented. It is expected that neuromorphic devices might provide potential solutions for the future generation of interactive sensation, memory, and computation to facilitate the development of multimodal, large-scale, ultralow-power intelligent systems.

High current treated-passivated graphene (CTPG) towards stable nanoelectronic and spintronic circuits

Achieving enhanced and stable electrical quality of scalable graphene is crucial for practical graphene device applications. Accordingly, encapsulation has emerged as an approach for improving electrical transport in graphene. In this study, we demonstrate high-current treatment of graphene passivated by AlOx nanofilms as a new means to enhance the electrical quality of graphene for its scalable utilization. Our experiments and electrical measurements on large-scale chemical vapor-deposited (CVD) graphene devices reveal that high-current treatment causes persistent and irreversible de-trapping density in both bare graphene and graphene covered by AlOx. Strikingly, despite possible interfacial defects in graphene covered with AlOx, the high-current treatment enhances its carrier mobility by up to 200% in contrast to bare graphene samples, where mobility decreases. Spatially resolved Raman spectroscopy mapping confirms that surface passivation by AlOx, followed by the current treatment, reduces the number of sp3 defects in graphene. These results suggest that for current treated-passivated graphene (CTPG), the high-current treatment considerably reduces charged impurity and trapped charge densities, thereby reducing Coulomb scattering while mitigating any electromigration of carbon atoms. Our study unveils CTPG as an innovative system for practical utilization in graphene nanoelectronic and spintronic integrated circuits.

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.

Evaluation of Nanostructured NiS2 Thin Films from a Single-Source Precursor for Flexible Memristive Devices

Herein, we report the first demonstration of a single-step, in situ growth of NiS2 nanostructures from a single-source precursor onto a flexible substrate as a versatile platform for an effective nonvolatile memristor. The low temperature, solution-processed deposition of NiS2 thin films exhibits a wide band gap range, spherical-flower-like morphology with high surface area and porosity, and negligible surface roughness. Moreover, the fabricated Au/NiS2/ITO/PET memristor device reveals reproducible bipolar resistive switching (RS) at low operational voltages under both flat and bending conditions. The flexible device shows stable RS behavior for multiple cycles with a good memory window (∼102) and data retention of up to 104 s. The switching of a device between a high-resistance state and a low-resistance state is attributed to the filamentary conduction based on sulfur ion migration and sulfur vacancies and plays a key role in the outstanding memristive performance of the device. Consequently, this work provides a simple, scalable, solution-processed route to fabricate a flexible device with potential applications in next-generation neuromorphic computing and wearable electronics.

Artificial Neuron Devices

Efforts to design devices emulating complex cognitive abilities and response processes of biological systems have long been a coveted goal. Recent advancements in flexible electronics, mirroring human tissue's mechanical properties, hold significant promise. Artificial neuron devices, hinging on flexible artificial synapses, bioinspired sensors, and actuators, are meticulously engineered to mimic the biological systems. However, this field is in its infancy, requiring substantial groundwork to achieve autonomous systems with intelligent feedback, adaptability, and tangible problem-solving capabilities. This review provides a comprehensive overview of recent advancements in artificial neuron devices. It starts with fundamental principles of artificial synaptic devices and explores artificial sensory systems, integrating artificial synapses and bioinspired sensors to replicate all five human senses. A systematic presentation of artificial nervous systems follows, designed to emulate fundamental human nervous system functions. The review also discusses potential applications and outlines existing challenges, offering insights into future prospects. We aim for this review to illuminate the burgeoning field of artificial neuron devices, inspiring further innovation in this captivating area of research.

Adaptive Neural Activation and Neuromorphic Processing via Drain-Injection Threshold-Switching Float Gate Transistor Memory

Hetero-modulated neural activation is vital for adaptive information processing and learning that occurs in brain. To implement brain-inspired adaptive processing, previously various neurotransistors oriented for synaptic functions are extensively explored, however, the emulation of nonlinear neural activation and hetero-modulated behaviors are not possible due to the lack of threshold switching behavior in a conventional transistor structure. Here, a 2D van der Waals float gate transistor (FGT) that exhibits steep threshold switching behavior, and the emulation of hetero-modulated neuron functions (integrate-and-fire, sigmoid type activation) for adaptive sensory processing, are reported. Unlike conventional FGTs, the threshold switching behavior stems from impact ionization in channel and the coupled charge injection to float gate. When a threshold is met, a sub-30 mV dec-1 increase of transistor conductance by more than four orders is triggered with a typical switch time of approximately milliseconds. Essentially, by feeding light sensing signal as the modulation input, it is demonstrated that two typical tasks that rely on adaptive neural activation, including collision avoidance and adaptive visual perception, can be realized. These results may shed light on the emulation of rich hetero-modulating behaviors in biological neurons and the realization of biomimetic neuromorphic processing at low hardware cost.

Porous crystalline materials for memories and neuromorphic computing systems

Porous crystalline materials usually include metal-organic frameworks (MOFs), covalent organic frameworks (COFs), hydrogen-bonded organic frameworks (HOFs) and zeolites, which exhibit exceptional porosity and structural/composition designability, promoting the increasing attention in memory and neuromorphic computing systems in the last decade. From both the perspective of materials and devices, it is crucial to provide a comprehensive and timely summary of the applications of porous crystalline materials in memory and neuromorphic computing systems to guide future research endeavors. Moreover, the utilization of porous crystalline materials in electronics necessitates a shift from powder synthesis to high-quality film preparation to ensure high device performance. This review highlights the strategies for preparing porous crystalline materials films and discusses their advancements in memory and neuromorphic electronics. It also provides a detailed comparative analysis and presents the existing challenges and future research directions, which can attract the experts from various fields (e.g., materials scientists, chemists, and engineers) with the aim of promoting the applications of porous crystalline materials in memory and neuromorphic computing systems.

2D materials readiness for the transistor performance breakthrough

As the size of the transistor scales down, this strategy has confronted challenges because of the fundamental limits of silicon materials. Besides, more and more energy and time are consumed by the data transmission out of transistor computing because of the speed mismatching between the computing and memory. To meet the energy efficiency demands of big data computing, the transistor should have a smaller feature size and store data faster to overcome the energy burden of computing and data transfer. Electron transport in two-dimensional (2D) materials is constrained within a 2D plane and different materials are assembled by the van der Waals force. Owning to the atomic thickness and dangling-bond-free surface, 2D materials have demonstrated advantages in transistor scaling-down and heterogeneous structure innovation. In this review, from the performance breakthrough of 2D transistors, we discuss the opportunities, progress and challenges of 2D materials in transistor applications.

Pseudo-transistors for emerging neuromorphic electronics

Artificial synaptic devices are the cornerstone of neuromorphic electronics. The development of new artificial synaptic devices and the simulation of biological synaptic computational functions are important tasks in the field of neuromorphic electronics. Although two-terminal memristors and three-terminal synaptic transistors have exhibited significant capabilities in the artificial synapse, more stable devices and simpler integration are needed in practical applications. Combining the configuration advantages of memristors and transistors, a novel pseudo-transistor is proposed. Here, recent advances in the development of pseudo-transistor-based neuromorphic electronics in recent years are reviewed. The working mechanisms, device structures and materials of three typical pseudo-transistors, including tunneling random access memory (TRAM), memflash and memtransistor, are comprehensively discussed. Finally, the future development and challenges in this field are emphasized.

Metal-Organic Frameworks-Based Memristors: Materials, Devices, and Applications

Facing the explosive growth of data, a number of new micro-nano devices with simple structure, low power consumption, and size scalability have emerged in recent years, such as neuromorphic computing based on memristor. The selection of resistive switching layer materials is extremely important for fabricating of high performance memristors. As an organic-inorganic hybrid material, metal-organic frameworks (MOFs) have the advantages of both inorganic and organic materials, which makes the memristors using it as a resistive switching layer show the characteristics of fast erasing speed, outstanding cycling stability, conspicuous mechanical flexibility, good biocompatibility, etc. Herein, the recent advances of MOFs-based memristors in materials, devices, and applications are summarized, especially the potential applications of MOFs-based memristors in data storage and neuromorphic computing. There also are discussions and analyses of the challenges of the current research to provide valuable insights for the development of MOFs-based memristors.

Progress and Challenges for Memtransistors in Neuromorphic Circuits and Systems

Due to the increasing importance of artificial intelligence (AI), significant recent effort has been devoted to the development of neuromorphic circuits that seek to emulate the energy-efficient information processing of the brain. While non-volatile memory (NVM) based on resistive switches, phase-change memory, and magnetic tunnel junctions has shown potential for implementing neural networks, additional multi-terminal device concepts are required for more sophisticated bio-realistic functions. Of particular interest are memtransistors based on low-dimensional nanomaterials, which are capable of electrostatically tuning memory and learning behavior at the device level. Herein, a conceptual overview of the memtransistor is provided in the context of neuromorphic circuits. Recent progress is surveyed for memtransistors and related multi-terminal NVM devices including dual-gated floating-gate memories, dual-gated ferroelectric transistors, and dual-gated van der Waals heterojunctions. The different materials systems and device architectures are classified based on the degree of control and relative tunability of synaptic behavior, with an emphasis on device concepts that harness the reduced dimensionality, weak electrostatic screening, and phase-changes properties of nanomaterials. Finally, strategies for achieving wafer-scale integration of memtransistors and multi-terminal NVM devices are delineated, with specific attention given to the materials challenges for practical neuromorphic circuits.

The Road for 2D Semiconductors in the Silicon Age

Continued reduction in transistor size can improve the performance of silicon integrated circuits (ICs). However, as Moore's law approaches physical limits, high-performance growth in silicon ICs becomes unsustainable, due to challenges of scaling, energy efficiency, and memory limitations. The ultrathin layers, diverse band structures, unique electronic properties, and silicon-compatible processes of 2D materials create the potential to consistently drive advanced performance in ICs. Here, the potential of fusing 2D materials with silicon ICs to minimize the challenges in silicon ICs, and to create technologies beyond the von Neumann architecture, is presented, and the killer applications for 2D materials in logic and memory devices to ease scaling, energy efficiency bottlenecks, and memory dilemmas encountered in silicon ICs are discussed. The fusion of 2D materials allows the creation of all-in-one perception, memory, and computation technologies beyond the von Neumann architecture to enhance system efficiency and remove computing power bottlenecks. Progress on the 2D ICs demonstration is summarized, as well as the technical hurdles it faces in terms of wafer-scale heterostructure growth, transfer, and compatible integration with silicon ICs. Finally, the promising pathways and obstacles to the technological advances in ICs due to the integration of 2D materials with silicon are presented.

A Single-Molecule Memristor based on an Electric-Field-Driven Dynamical Structure Reconfiguration

A robust single-molecule memristor is prepared by covalently integrating one phenol molecule with multiple binding sites into nanogapped graphene electrodes. Multilevel resistance switching is realized by the electric-field-manipulated reconfiguration of the acyl moiety on the phenol center, that is, the Fries rearrangement. In situ measurements of the reaction trajectories with an initial single substrate and an intermediate break through the limitation of macroscopic experiments, therefore unveiling both intramolecular and intermolecular mechanistic pathways (a long-term controversy) as well as comprehensive dynamic information. Based on this advance, high-performance single-molecule memristors in both the solution and solid states are achieved successively, providing a new understanding of memristive systems and neural network computing.

Insights and Implications of Intricate Surface Charge Transfer and sp3-Defects in Graphene/Metal Oxide Interfaces

Adherence of metal oxides to graphene is of fundamental significance to graphene nanoelectronic and spintronic interfaces. Titanium oxide and aluminum oxide are two widely used tunnel barriers in such devices, which offer optimum interface resistance and distinct interface conditions that govern transport parameters and device performance. Here, we reveal a fundamental difference in how these metal oxides interface with graphene through electrical transport measurements and Raman and photoelectron spectroscopies, combined with ab initio electronic structure calculations of such interfaces. While both oxide layers cause surface charge transfer induced p-type doping in graphene, in sharp contrast to TiO_x, the AlO_x/graphene interface shows the presence of appreciable sp³ defects. Electronic structure calculations disclose that significant p-type doping occurs due to a combination of sp³ bonds formed between C and O atoms at the interface and possible slightly off-stoichiometric defects of the aluminum oxide layer. Furthermore, the sp³ hybridization at the AlO_x/graphene interface leads to distinct magnetic moments of unsaturated bonds, which not only explicates the widely observed low spin-lifetimes in AlO_x barrier graphene spintronic devices but also suggests possibilities for new hybrid resistive switching and spin valves.

2D materials: increscent quantum flatland with immense potential for applications

Quantum flatland i.e., the family of two dimensional (2D) quantum materials has become increscent and has already encompassed elemental atomic sheets (Xenes), 2D transition metal dichalcogenides (TMDCs), 2D metal nitrides/carbides/carbonitrides (MXenes), 2D metal oxides, 2D metal phosphides, 2D metal halides, 2D mixed oxides, etc. and still new members are being explored. Owing to the occurrence of various structural phases of each 2D material and each exhibiting a unique electronic structure; bestows distinct physical and chemical properties. In the early years, world record electronic mobility and fractional quantum Hall effect of graphene attracted attention. Thanks to excellent electronic mobility, and extreme sensitivity of their electronic structures towards the adjacent environment, 2D materials have been employed as various ultrafast precision sensors such as gas/fire/light/strain sensors and in trace-level molecular detectors and disease diagnosis. 2D materials, their doped versions, and their hetero layers and hybrids have been successfully employed in electronic/photonic/optoelectronic/spintronic and straintronic chips. In recent times, quantum behavior such as the existence of a superconducting phase in moiré hetero layers, the feasibility of hyperbolic photonic metamaterials, mechanical metamaterials with negative Poisson ratio, and potential usage in second/third harmonic generation and electromagnetic shields, etc. have raised the expectations further. High surface area, excellent young's moduli, and anchoring/coupling capability bolster hopes for their usage as nanofillers in polymers, glass, and soft metals. Even though lab-scale demonstrations have been showcased, large-scale applications such as solar cells, LEDs, flat panel displays, hybrid energy storage, catalysis (including water splitting and CO₂ reduction), etc. will catch up. While new members of the flatland family will be invented, new methods of large-scale synthesis of defect-free crystals will be explored and novel applications will emerge, it is expected. Achieving a high level of in-plane doping in 2D materials without adding defects is a challenge to work on. Development of understanding of inter-layer coupling and its effects on electron injection/excited state electron transfer at the 2D-2D interfaces will lead to future generation heterolayer devices and sensors.

Recent Advances on Tuning the Interlayer Coupling and Properties in van der Waals Heterostructures

2D van der Waals (vdW) heterostructures are receiving increasing research attention due to the theoretically amazing properties and unprecedented application potential. However, the as-synthesized heterostructures are generally underperforming due to the weak interlayer coupling, which inspires the researchers to find ways to modulate the interlayer coupling and properties, realizing the tailored performance for actual applications. There have been a lot of publications regarding the controllable regulation of the structures and properties of 2D vdW heterostructures in the past few years, while a review work summarizing the current advances is not yet available, though it is significant. This paper conducts a state-of-the-art review regarding the current research progress of performance modulation of vdW heterostructures by different techniques. First, the general synthesis methods of vdW heterostructures are summarized. Then, different performance modulation techniques, that is, mechanical-based, external fields-assisted, and particle beam irradiation-based methods, are discussed and compared in detail. Some of the newly proposed concepts are described. Thereafter, applications of vdW heterostructures with tailored properties are reviewed for the application prospects of the topic around this area. Moreover, the future research challenges and prospects are discussed, aiming at triggering more research interest and device applications around this topic.

Nanostructured perovskites for nonvolatile memory devices

Perovskite materials have driven tremendous advances in constructing electronic devices owing to their low cost, facile synthesis, outstanding electric and optoelectronic properties, flexible dimensionality engineering, and so on. Particularly, emerging nonvolatile memory devices (eNVMs) based on perovskites give birth to numerous traditional paradigm terminators in the fields of storage and computation. Despite significant exploration efforts being devoted to perovskite-based high-density storage and neuromorphic electronic devices, research studies on materials' dimensionality that has dominant effects on perovskite electronics' performances are paid little attention; therefore, a review from the point of view of structural morphologies of perovskites is essential for constructing perovskite-based devices. Here, recent advances of perovskite-based eNVMs (memristors and field-effect-transistors) are reviewed in terms of the dimensionality of perovskite materials and their potentialities in storage or neuromorphic computing. The corresponding material preparation methods, device structures, working mechanisms, and unique features are showcased and evaluated in detail. Furthermore, a broad spectrum of advanced technologies (e.g., hardware-based neural networks, in-sensor computing, logic operation, physical unclonable functions, and true random number generator), which are successfully achieved for perovskite-based electronics, are investigated. It is obvious that this review will provide benchmarks for designing high-quality perovskite-based electronics for application in storage, neuromorphic computing, artificial intelligence, information security, etc.

A Study of the Applicability of Existing Compact Models to the Simulation of Memristive Structures Characteristics on Low-Dimensional Materials

The use of low-dimensional materials is a promising approach to improve the key characteristics of memristors. The development process includes modeling, but the question of the most common compact model applicability to the modeling of device characteristics with the inclusion of low-dimensional materials remains open. In this paper, a comparative analysis of linear and nonlinear drift as well as threshold models was conducted. For this purpose, the assumption of the relationship between the results of the optimization of the volt–ampere characteristic loop and the descriptive ability of the model was used. A global random search algorithm was used to solve the optimization problem, and an error function with the inclusion of a regularizer was developed to estimate the loop features. Based on the characteristic features derived through meta-analysis, synthetic volt–ampere characteristic contours were built and the results of their approximation by different models were compared. For every model, the quality of the threshold voltage estimation was evaluated, the forms of the memristor potential functions and dynamic attractors associated with experimental contours on graphene oxide were calculated.

Dual-Tunable Memristor Based on Carbon Nanotubes and Graphene Quantum Dots

Nanocarbon materials have the advantages of biocompatibility, thermal stability and chemical stability and have shown excellent electrical properties in electronic devices. In this study, Al/MWCNT:GQD/ITO memristors with rewritable nonvolatile properties were prepared based on composites consisting of multiwalled carbon nanotubes (MWCNTs) and graphene quantum dots (GQDs). The switching current ratio of such a device can be tuned in two ways. Due to the ultraviolet light sensitivity of GQDs, when the dielectric material is illuminated by ultraviolet light, the charge capture ability of the GQDs decreases with an increasing duration of illumination, and the switching current ratio of the device also decreases with an increasing illumination duration (10³–10). By exploiting the charge capture characteristics of GQDs, the trap capture level can be increased by increasing the content of GQDs in the dielectric layer. The switching current ratio of the device increases with increasing GQD content (10–10³). The device can be programmed and erased more than 100 times; the programmable switching state can withstand 10⁵ read pulses, and the retention time is more than 10⁴ s. This memristor has a simple structure, low power consumption, and enormous application potential for data storage, artificial intelligence, image processing, artificial neural networks, and other applications.

Ultrafast non-volatile flash memory based on van der Waals heterostructures

Flash memory has become a ubiquitous solid-state memory device widely used in portable digital devices, computers and enterprise applications. The development of the information age has demanded improvements in memory speed and retention performance. Here we demonstrate an ultrafast non-volatile flash memory based on MoS₂/hBN/multilayer graphene van der Waals heterostructures, which achieves an ultrafast writing/erasing speed of 20 ns through two-triangle-barrier modified Fowler-Nordheim tunnelling. Using detailed theoretical analysis and experimental verification, we postulate that a suitable barrier height, gate coupling ratio and clean interface are the main reasons for the breakthrough writing/erasing speed of our flash memory devices. Because of its non-volatility this ultrafast flash memory could provide the foundation for the next generation of high-speed non-volatile memory.

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.

Design and tailoring of two-dimensional Schottky, PN and tunnelling junctions for electronics and optoelectronics

Owing to their superior carrier mobility, strong light-matter interactions, and flexibility at the atomically thin thickness, two-dimensional (2D) materials are attracting wide interest for application in electronic and optoelectronic devices, including rectifying diodes, transistors, memory, photodetectors, and light-emitting diodes. At the heart of these devices, Schottky, PN, and tunneling junctions are playing an essential role in defining device function. Intriguingly, the ultrathin thickness and unique van der Waals (vdW) interlayer coupling in 2D materials has rendered enormous opportunities for the design and tailoring of various 2D junctions, e.g. using Lego-like hetero-stacking, surface decoration, and field-effect modulation methods. Such flexibility has led to marvelous breakthroughs during the exploration of 2D electronics and optoelectronic devices. To advance further, it is imperative to provide an overview of existing strategies for the engineering of various 2D junctions for their integration in the future. Thus, in this review, we provide a comprehensive survey of previous efforts toward 2D Schottky, PN, and tunneling junctions, and the functional devices built from them. Though these junctions exhibit similar configurations, distinct strategies have been developed for their optimal figures of merit based on their working principles and functional purposes.

Controlling Native Oxidation of HfS2 for 2D Materials Based Flash Memory and Artificial Synapse

Two-dimensional (2D) materials based artificial synapses are important building blocks for the brain-inspired computing systems that are promising in handling large amounts of informational data with high energy-efficiency in the future. However, 2D devices usually rely on deposited or transferred insulators as the dielectric layer, resulting in various challenges in device compatibility and fabrication complexity. Here, we demonstrate a controllable and reliable oxidation process to turn 2D semiconductor HfS₂ into native oxide, HfO_x, which shows good insulating property and clean interface with HfS₂. We then incorporate the HfO_x/HfS₂ heterostructure into a flash memory device, achieving a high on/off current ratio of ∼10⁵, a large memory window over 60 V, good endurance, and a long retention time over 10³ seconds. In particular, the memory device can work as an artificial synapse to emulate basic synaptic functions and feature good linearity and symmetry in conductance change during long-term potentiation/depression processes. A simulated artificial neural network based on our synaptic device achieves a high accuracy of ∼88% in MNIST pattern recognition. Our work provides a simple and effective approach for integrating high-k dielectrics into 2D material-based memory and synaptic devices.

Recent Process of Flexible Transistor-Structured Memory

Flexible transistor-structured memory (FTSM) has attracted great attention for its important role in flexible electronics. For nonvolatile information storage, FTSMs with floating-gate, charge-trap, and ferroelectric mechanisms have been developed. By introducing an optical sensory module, FTSM can be operated by optical inputs to function as an optical memory transistor. As a special type of FTSM, transistor-structured artificial synapse emulates important functions of a biological synapse to mimic brain-inspired memory behaviors and nervous signal transmissions. This work reviews the recent development of the above mentioned FTSMs, with a focus on working mechanism and materials, and flexibility.

High-bandwidth light inputting multilevel photoelectric memory based on thin-film transistor with a floating gate of CsPbBr3/CsPbI3 blend quantum dots

The electronic-photonic convergent systems can overcome the data transmission bottleneck for microchips by enabling processor and memory chips with high-bandwidth optical input/output. However, current silicon-based electronic-photonic systems require various functional devices/components to convert high-bandwidth optical signals into electrical ones, thus making further integrations of sophisticated systems rather difficult. Here, we demonstrate thin-film transistor-based photoelectric memories employing CsPbBr₃/CsPbI₃ blend perovskite quantum dots (PQDs) as a floating gate, and multilevel memory cells are achieved under programming and erasing modes, respectively, by imputing high-bandwidth optical signals. For different bandwidth light input (i.e. 500-550, 575-650 and 675-750 nm) with the same intensity, three levels of programming window (i.e. 3.7, 1.9 and 0.8 V) and erasing window (i.e. -1.9, -0.6 and -0.1 V) are obtained under electrical pulses, respectively. This is because the blend PQDs have two different bandgaps, and different amounts of photo-generated carriers can be produced for different wavelength optical inputs. It is noticed that the 675-750 nm light inputs have no effects on both programming and erasing windows because of no photo-carriers generation. Four memory states are demonstrated, showing enough large gaps (1.12-5.61 V) between each other, good data retention and programming/erasing endurance. By inputting different optical signals, different memory states can be switched easily. Therefore, this work directly demonstrates high-bandwidth light inputting multilevel memory cells for novel electronic-photonic systems.

The capabilities of nanoelectronic 2-D materials for bio-inspired computing and drug delivery indicate their significance in modern drug design

Remarkable advancements in the computational techniques and nanoelectronics have attracted considerable interests for development of highly-sophisticated materials (Ms) including the theranostics with optimal characteristics and innovative delivery systems. Analyzing the huge amounts of multivariate data and solving the newly-emerged complicated problems including the healthcare-related ones have created increasing demands for improving the computational speed and minimizing the consumption of energy. Shifting towards the non-von Neumann approaches enables performing specific computational tasks and optimizing the processing of signals. Besides usefulness for neuromorphic computing and increasing the efficiency of computation energy, 2-D electronic Ms are capable of optical sensing with ultra-fast and ultra-sensitive responses, mimicking the neurons, detection of pathogens or biomolecules, and prediction of the progression of diseases, assessment of the pharmacokinetics/pharmacodynamics of therapeutic candidates, mimicking the dynamics of the release of neurotransmitters or fluxes of ions that might provide a deeper knowledge about the computations and information flow in the brain, and development of more effective treatment protocols with improved outcomes. 2-D Ms appear as the major components of the next-generation electronically-enabled devices for highly-advanced computations, bio-imaging, diagnostics, tissue engineering, and designing smart systems for site-specific delivery of therapeutics that might result in the reduced adverse effects of drugs and improved patient compliance. This manuscript highlights the significance of 2-D Ms in the neuromorphic computing, optimizing the energy efficiency of the multi-step computations, providing novel architectures or multi-functional systems, improved performance of a variety of devices and bio-inspired functionalities, and delivery of theranostics.

Growth and Interlayer Engineering of 2D Layered Semiconductors for Future Electronics

Layered materials that do not form a covalent bond in a vertical direction can be prepared in a few atoms to one atom thickness without dangling bonds. This distinctive characteristic of limiting thickness around the sub-nanometer level allowed scientists to explore various physical phenomena in the quantum realm. In addition to the contribution to fundamental science, various applications were proposed. Representatively, they were suggested as a promising material for future electronics. This is because (i) the dangling-bond-free nature inhibits surface scattering, thus carrier mobility can be maintained at sub-nanometer range; (ii) the ultrathin nature allows the short-channel effect to be overcome. In order to establish fundamental discoveries and utilize them in practical applications, appropriate preparation methods are required. On the other hand, adjusting properties to fit the desired application properly is another critical issue. Hence, in this review, we first describe the preparation method of layered materials. Proper growth techniques for target applications and the growth of emerging materials at the beginning stage will be extensively discussed. In addition, we suggest interlayer engineering via intercalation as a method for the development of artificial crystal. Since infinite combinations of the host-intercalant combination are possible, it is expected to expand the material system from the current compound system. Finally, inevitable factors that layered materials must face to be used as electronic applications will be introduced with possible solutions. Emerging electronic devices realized by layered materials are also discussed.

Stimuli-Enabled Artificial Synapses for Neuromorphic Perception: Progress and Perspectives

Brain-inspired neuromorphic computing is intended to provide effective emulation of the functionality of the human brain via the integration of electronic components. Recent studies of synaptic plasticity, which represents one of the most significant neurochemical bases of learning and memory, have enhanced the general comprehension of how the brain functions and have thereby eased the development of artificial neuromorphic devices. An understanding of the synaptic plasticity induced by various types of stimuli is essential for neuromorphic system construction. The realization of multiple stimuli-enabled synapses will be important for future neuromorphic computing applications. In this Review, state-of-the-art synaptic devices with particular emphasis on their synaptic behaviors under excitation by a variety of external stimuli are summarized, including electric fields, light, magnetic fields, pressure, and temperature. The switching mechanisms of these synaptic devices are discussed in detail, including ion migration, electron/hole transfer, phase transition, redox-based resistive switching, and other mechanisms. This Review aims to provide a comprehensive understanding of the operating mechanisms of artificial synapses and thus provides the principles required for design of multifunctional neuromorphic systems with parallel processing capabilities.

Two-dimensional materials for next-generation computing technologies

Rapid digital technology advancement has resulted in a tremendous increase in computing tasks imposing stringent energy efficiency and area efficiency requirements on next-generation computing. To meet the growing data-driven demand, in-memory computing and transistor-based computing have emerged as potent technologies for the implementation of matrix and logic computing. However, to fulfil the future computing requirements new materials are urgently needed to complement the existing Si complementary metal-oxide-semiconductor technology and new technologies must be developed to enable further diversification of electronics and their applications. The abundance and rich variety of electronic properties of two-dimensional materials have endowed them with the potential to enhance computing energy efficiency while enabling continued device downscaling to a feature size below 5 nm. In this Review, from the perspective of matrix and logic computing, we discuss the opportunities, progress and challenges of integrating two-dimensional materials with in-memory computing and transistor-based computing technologies.

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.

Artificial Synapse Based on van der Waals Heterostructures with Tunable Synaptic Functions for Neuromorphic Computing

Two-dimensional (2D) materials and van der Waals heterostructures have attracted tremendous attention because of their appealing electronic, mechanical, and optoelectronic properties, which offer the possibility to extend the range of functionalities for diverse potential applications. Here, we fabricate a novel multiterminal device with dual-gate based on 2D material van der Waals heterostructures. Such a multiterminal device exhibited excellent nonvolatile multilevel resistance switching performance controlled by the source-drain voltage and back-gate voltage. Based on these features, heterosynaptic plasticity, in which the synaptic weight can be tuned by another modulatory interneuron, has been mimicked. A tunable analogue weight update (both on/off ratio and update nonlinearity) of synapse with high speed (50 ns) and low energy (∼7.3 fJ) programming has been achieved. These results demonstrate the great potential of the artificial synapse based on van der Waals heterostructures for neuromorphic computing.

Clean Interface Contact Using a ZnO Interlayer for Low-Contact-Resistance MoS2 Transistors

Two-dimensional transition metal dichalcogenides (TMDCs) have emerged as promising materials for next-generation electronics due to their excellent semiconducting properties. However, high contact resistance at the metal-TMDC interface plagues the realization of high-performance devices. Here, an effective metal-interlayer-semiconductor (MIS) contact is demonstrated, wherein an ultrathin ZnO interlayer is inserted between the metal electrode and MoS₂, providing damage-free and clean interfaces at electrical contacts. Using TEM imaging, we show that the contact interfaces were atomically clean without any apparent damages. Compared to conventional Ti/MoS₂ contacts, the MoS₂ devices with a Ti/ZnO/MoS₂ contact exhibit a very low contact resistance of 0.9 kΩ μm. These improvements are attributed to the following mechanisms: (a) Fermi-level depinning at the metal/MoS₂ interface by reducing interface disorder and (b) presence of interface dipole at the metal/ZnO interface, consequently reducing the Schottky barrier and contact resistance. Further, the contact resistivity of a Ti/ZnO/MoS₂ contact is insensitive to the variation of ZnO thickness, which facilitates large-scale production. Our work not only elucidates the underlying mechanisms for the operation of the MIS contact but also provides a simple and damage-free strategy for conventional aggressive metal deposition that is potentially useful for the realization of large-scale 2D electronics with low-resistance contacts.

Flexible full two-dimensional memristive synapses of graphene/WSe2−xOy/graphene

van der Waals heterostructures realized by stacking different two-dimensional materials offer the possibility to design new devices with atomic-level precision.

MoS2 Memtransistors Fabricated by Localized Helium Ion Beam Irradiation

Two-dimensional (2D) layered semiconductors have recently emerged as attractive building blocks for next-generation low-power nonvolatile memories. However, challenges remain in the controllable fabrication of bipolar resistive switching circuit components from these materials. Here, the experimental realization of lateral memtransistors from monolayer single-crystal molybdenum disulfide (MoS₂) utilizing a focused helium ion beam is reported. Site-specific irradiation with the focused probe of a helium ion microscope creates a nanometer-scale defect-rich region, bisecting the MoS₂ lattice. The reversible drift of these defects in the applied electric field modulates the resistance of the channel, enabling versatile memristive functionality. The device can reliably retain its resistance ratios and set/reset biases for 1180 switching cycles. Long-term potentiation and depression with sharp habituation are demonstrated. This work establishes the feasibility of ion irradiation for controllable fabrication of 2D memristive devices with promising key performance parameters, such as low power consumption. The applicability of these devices for synaptic emulation may address the demands of future neuromorphic architectures.

Bridging Biological and Artificial Neural Networks with Emerging Neuromorphic Devices: Fundamentals, Progress, and Challenges

As the research on artificial intelligence booms, there is broad interest in brain-inspired computing using novel neuromorphic devices. The potential of various emerging materials and devices for neuromorphic computing has attracted extensive research efforts, leading to a large number of publications. Going forward, in order to better emulate the brain's functions, its relevant fundamentals, working mechanisms, and resultant behaviors need to be re-visited, better understood, and connected to electronics. A systematic overview of biological and artificial neural systems is given, along with their related critical mechanisms. Recent progress in neuromorphic devices is reviewed and, more importantly, the existing challenges are highlighted to hopefully shed light on future research directions.

Complex Optical Conductivity of Two-Dimensional MoS2: A Striking Layer Dependency

The complex optical conductivities of two-dimensaionl (2D) materials are fundamental for extended applications of related optoelectronic devices. Here, we systematically investigate the layer-dependent evolutions in the complex optical conductivities of 1-6 layer 2D MoS₂ over an ultrawide spectral range (0.73-6.42 eV) by spectroscopic ellipsometry. We identify five feature peaks (A-E) in the optical conductivity spectra, which present interesting layer dependencies due to the scaling effect. Results suggest that the center energies of peaks A and B are nearly layer-independent, while those of peaks C and D exhibit redshifts as the layer increases. We interpret these layer-dependent evolutions as the competition between the decreasing exciton effect and the prominent band shrinkage with the increasing layer number. Additionally, the applicability of the classical slab model and the surface current model in evaluating the optical conductivities of 2D MoS₂ with different layers is discussed from an experimental perspective.

Memristive devices based on emerging two-dimensional materials beyond graphene

With the explosion of data in the information universe and the approaching of fundamental limits in silicon-based flash memories, the exploration of new device architectures and alternative materials is necessary for next-generation memory technology. Accordingly, emerging two-dimensional (2D) material-based memristive devices have attracted increasing attention due to their unique properties and great potential in flexible and wearable devices, and even neuromorphic computing systems. Herein, we provide an overview of the recent progress on memristive devices based on 2D materials beyond graphene. The device structures and choice of active materials and electrodes materials are summarized for various types of 2D material-based memristive devices. Following the discussion and classification on the device performances and mechanisms, the challenges and perspectives on future research based on 2D materials are also presented.

Gate tunable giant anisotropic resistance in ultra-thin GaTe

Anisotropy in crystals arises from different lattice periodicity along different crystallographic directions, and is usually more pronounced in two dimensional (2D) materials. Indeed, in the emerging 2D materials, electrical anisotropy has been one of the recent research focuses. However, key understandings of the in-plane anisotropic resistance in low-symmetry 2D materials, as well as demonstrations of model devices taking advantage of it, have proven difficult. Here, we show that, in few-layered semiconducting GaTe, electrical conductivity anisotropy between x and y directions of the 2D crystal can be gate tuned from several fold to over 10³. This effect is further demonstrated to yield an anisotropic non-volatile memory behavior in ultra-thin GaTe, when equipped with an architecture of van der Waals floating gate. Our findings of gate-tunable giant anisotropic resistance effect pave the way for potential applications in nanoelectronics such as multifunctional directional memories in the 2D limit.

Some atomically thin crystals feature crystallographic anisotropy, but demonstrations of electrical anisotropy are scarce. Here, the authors show that the electrical conductivity of few-layered GaTe along the x and y directions can be widely gate tuned up to 10³, and demonstrate anisotropic non-volatile memory behavior.

Nonvolatile Memories Based on Graphene and Related 2D Materials

The pervasiveness of information technologies is generating an impressive amount of data, which need to be accessed very quickly. Nonvolatile memories (NVMs) are making inroads into high-capacity storage to replace hard disk drives, fuelling the expansion of the global storage memory market. As silicon-based flash memories are approaching their fundamental limit, vertical stacking of multiple memory cell layers, innovative device concepts, and novel materials are being investigated. In this context, emerging 2D materials, such as graphene, transition metal dichalcogenides, and black phosphorous, offer a host of physical and chemical properties, which could both improve existing memory technologies and enable the next generation of low-cost, flexible, and wearable storage devices. Herein, an overview of graphene and related 2D materials (GRMs) in different types of NVM cells is provided, including resistive random-access, flash, magnetic and phase-change memories. The physical and chemical mechanisms underlying the switching of GRM-based memory devices studied in the last decade are discussed. Although at this stage most of the proof-of-concept devices investigated do not compete with state-of-the-art devices, a number of promising technological advancements have emerged. Here, the most relevant material properties and device structures are analyzed, emphasizing opportunities and challenges toward the realization of practical NVM devices.

A nanofluidic memristor based on ion concentration polarization

The very first nanofluidic memristor based on the principle of ion concentration polarization (ICP).

Doping engineering and functionalization of two-dimensional metal chalcogenides

Two-dimensional (2D) layered metal chalcogenides (MXs) have significant potential for use in flexible transistors, optoelectronics, sensing and memory devices beyond the state-of-the-art technology. To pursue ultimate performance, precisely controlled doping engineering of 2D MXs is desired for tailoring their physical and chemical properties in functional devices. In this review, we highlight the recent progress in the doping engineering of 2D MXs, covering that enabled by substitution, exterior charge transfer, intercalation and the electrostatic doping mechanism. A variety of novel doping engineering examples leading to Janus structures, defect curing effects, zero-valent intercalation and deliberately devised floating gate modulation will be discussed together with their intriguing application prospects. The choice of doping strategies and sources for functionalizing MXs will be provided to facilitate ongoing research in this field toward multifunctional applications.

Dendrite Integration Mimicked on Starch-Based Electrolyte-Gated Oxide Dendrite Transistors

Emulation of dendrite integration on brain-inspired hardware devices is of great significance for neuromorphic engineering. Here, solution-processed starch-based electrolyte films are fabricated, demonstrating strong proton gating activities. Starch gated oxide dendrite transistors with multigates are fabricated, exhibiting good electrical performances. Most importantly, dendrite modulation, spatiotemporal dendrite integration, and linear/superlinear dendrite algorithm are demonstrated on the proposed dendrite transistor. Furthermore, a low energy consumption of ∼1.2 pJ is obtained for triggering a synaptic response on the dendrite transistor. Accordingly, the signal-to-noise ratio is still as high as ∼2.9, indicating a high sensitivity of ∼4.6 dB. Such artificial dendrite transistors have potential applications in brain-inspired neuromorphic platforms.