Low-voltage ultrafast nonvolatile memory via direct charge injection through a threshold resistive-switching layer

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.

Ultrafast Non-Volatile Floating-Gate Memory Based on All-2D Materials

The explosive growth of massive-data storage and the demand for ultrafast data processing require innovative memory devices with exceptional performance. 2D materials and their van der Waal heterostructures with atomically sharp interfaces hold great promise for innovations in memory devices. Here, this work presents non-volatile, floating-gate memory devices with all functional layers made of 2D materials, achieving ultrafast programming/erasing speeds (20 ns), high extinction ratios (up to 108), and multi-bit storage capability. These devices also exhibit long-term data retention exceeding 10 years, facilitated by a high gate-coupling ratio (GCR) and atomically sharp interfaces between functional layers. Additionally, this work demonstrates the realization of an "OR" logic gate on a single-device unit by synergistic electrical and optical operations. The present results provide a solid foundation for next-generation ultrahigh-speed, ultralong lifespan, non-volatile memory devices, with a potential for scale-up manufacturing and flexible electronics applications.

High-Density, Nonvolatile, Flexible Multilevel Organic Memristor Using Multilayered Polymer Semiconductors

Nonvolatile organic memristors have emerged as promising candidates for next-generation electronics, emphasizing the need for vertical device fabrication to attain a high density. Herein, we present a comprehensive investigation of high-performance organic memristors, fabricated in crossbar architecture with PTB7/Al-AlOx-nanocluster/PTB7 embedded between Al electrodes. PTB7 films were fabricated using the Unidirectional Floating Film Transfer Method, enabling independent uniform film fabrication in the Layer-by-Layer (LbL) configuration without disturbing underlying films. We examined the charge transport mechanism of our memristors using the Hubbard model highlighting the role of Al-AlOx-nanoclusters in switching-on the devices, due to the accumulation of bipolarons in the semiconducting layer. By varying the number of LbL films in the device architecture, the resistance of resistive states was systematically altered, enabling the fabrication of novel multilevel memristors. These multilevel devices exhibited excellent performance metrics, including enhanced memory density, high on-off ratio (>108), remarkable memory retention (>105 s), high endurance (87 on-off cycles), and rapid switching (∼100 ns). Furthermore, flexible memristors were fabricated, demonstrating consistent performance even under bending conditions, with a radius of 2.78 mm for >104 bending cycles. This study not only demonstrates the fundamental understanding of charge transport in organic memristors but also introduces novel device architectures with significant implications for high-density flexible applications.

Gate Voltage- and Bias Voltage-Tunable Staggered-Gap to Broken-Gap Transition Based on WSe2/Ta2NiSe5 Heterostructure for Multimode Optoelectronic Logic Gate

Two-dimensional (2D) materials with superior properties exhibit tremendous potential in developing next-generation electronic and optoelectronic devices. Integrating various functions into one device is highly expected as that endows 2D materials great promise for more Moore and more-than-Moore device applications. Here, we construct a WSe2/Ta2NiSe5 heterostructure by stacking the p-type WSe2 and the n-type narrow gap Ta2NiSe5 with the aim to achieve a multifunction optoelectronic device. Owing to the large interface potential barrier, the heterostructure device reveals a prominent diode feature with a large rectify ratio (7.6 × 104) and a low dark current (10-12 A). Especially, gate voltage- and bias voltage-tunable staggered-gap to broken-gap transition is achieved on the heterostructure device, which enables gate voltage-tunable forward and reverse rectifying features. As results, the heterostructure device exhibits superior self-powered photodetection properties, including a high detectivity of 1.08 × 1010 Jones and a fast response time of 91 μs. Additionally, the intrinsic structural anisotropy of Ta2NiSe5 endows the heterostructure device with strong polarization-sensitive photodetection and high-resolution polarization imaging. Based on these characteristics, a multimode optoelectronic logic gate is realized on the heterostructure via synergistically modulating the light on/off, polarization angle, gate voltage, and bias voltage. This work shed light on the future development of constructing high-performance multifunctional optoelectronic devices.

Can 2D Semiconductors Be Game-Changers for Nanoelectronics and Photonics?

2D semiconductors have interesting physical and chemical attributes that have led them to become one of the most intensely investigated semiconductor families in recent history. They may play a crucial role in the next technological revolution in electronics as well as optoelectronics or photonics. In this Perspective, we explore the fundamental principles and significant advancements in electronic and photonic devices comprising 2D semiconductors. We focus on strategies aimed at enhancing the performance of conventional devices and exploiting important properties of 2D semiconductors that allow fundamentally interesting device functionalities for future applications. Approaches for the realization of emerging logic transistors and memory devices as well as photovoltaics, photodetectors, electro-optical modulators, and nonlinear optics based on 2D semiconductors are discussed. We also provide a forward-looking perspective on critical remaining challenges and opportunities for basic science and technology level applications of 2D semiconductors.

Hierarchical processing enabled by 2D ferroelectric semiconductor transistor for low-power and high-efficiency AI vision system

The growth of data and Internet of Things challenges traditional hardware, which encounters efficiency and power issues owing to separate functional units for sensors, memory, and computation. In this study, we designed an α-phase indium selenide (α-In2Se3) transistor, which is a two-dimensional ferroelectric semiconductor as the channel material, to create artificial optic-neural and electro-neural synapses, enabling cutting-edge processing-in-sensor (PIS) and computing-in-memory (CIM) functionalities. As an optic-neural synapse for low-level sensory processing, the α-In2Se3 transistor exhibits a high photoresponsivity (2855 A/W) and detectivity (2.91 × 1014 Jones), facilitating efficient feature extraction. For high-level processing tasks as an electro-neural synapse, it offers a fast program/erase speed of 40 ns/50 µs and ultralow energy consumption of 0.37 aJ/spike. An AI vision system using α-In2Se3 transistors has been demonstrated. It achieved an impressive recognition accuracy of 92.63% within 12 epochs owing to the synergistic combination of the PIS and CIM functionalities. This study demonstrates the potential of the α-In2Se3 transistor in future vision hardware, enhancing processing, power efficiency, and AI applications.

2D van der Waals Heterostructure with Tellurene Floating-Gate for Wide Range and Multi-Bit Optoelectronic Memory

Intensive research on optoelectronic memory (OEM) devices based on two-dimensional (2D) van der Waals heterostructures (vdWhs) is being conducted due to their distinctive advantages for electrical-optical writing and multilevel storage. These features make OEM a promising candidate for the logic of reconfigurable operations. However, the realization of nonvolatile OEM with broadband absorption (from visible to infrared) and a high switching ratio remains challenging. Herein, we report a nonvolatile OEM based on a heterostructure consisting of rhenium disulfide (ReS2), hexagonal boron nitride (hBN) and tellurene (2D Te). The 2D Te-based floating-gate (FG) device exhibits excellent performance metrics, including a high switching on/off ratio (∼106), significant endurance (>1000 cycles) and impressive retention (>104 s). In addition, the narrow band gap of 2D Te endows the device with broadband optical programmability from the visible to near-infrared regions at room temperature. Moreover, by applying different gate voltages, light wavelengths, and laser powers, multiple bits can be successfully generated. Additionally, the device is specifically designed to enable reconfigurable inverter logic circuits (including AND and OR gates) through controlled electrical and optical inputs. These significant findings demonstrate that the 2D vdWhs with a 2D Te FG are a valuable approach in the development of high-performance OEM devices.

Gradual conductance modulation by defect reorganization in amorphous oxide memristors

Amorphous oxides show great prospects in revolutionizing memristors benefiting from their abundant non-stoichiometric composition. However, an in-depth investigation of the memristive characteristics in amorphous oxides is inadequate and the resistive switching mechanism is still controversial. In this study, aiming to clearly understand the gradual conductance modulation that is deeply bound to the evolution of defects-mainly oxygen vacancies, forming-free memristors based on amorphous ZnAlSnO are fabricated, which exhibit high reproducibility with an initial low-resistance state. Pulse depression reveals the logarithmic-exponential mixed relaxation during RESET owing to the diffusion of oxygen vacancies in orthogonal directions. The remnants of conductive filaments formed through aggregation of oxygen vacancies induced by high-electric-field are identified using ex situ TEM. Especially, the conductance of the filament, including the remnant filament, is larger than that of the hopping conductive channel derived from the diffusion of oxygen vacancies. The Fermi level in the conduction band rationalizes the decay of the high resistance state. Rare oxidation-migration of Au occurs upon device failure, resulting in numerous gold nanoclusters in the functional layer. These comprehensive revelations on the reorganization of oxygen vacancies could provide original ideas for the design of memristors.

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.

Improved resistive switching performance and realized electric control of exchange bias in a NiO/HfO2 bilayer structure

The fluctuation of switching parameters is unavoidable in conductive filaments (CFs)-type resistive switching (RS) devices, which restricts the application in resistive random-access memory. Here, we employed an uninsulated antiferromagnetic (AFM) NiO layer adhered to a well-insulating HfO2 layer to effectively suppress the RS fluctuation by achieving forming-free, narrower set voltage distribution, a more stable on/off ratio, and better endurance in comparison with single-HfO2-layer based RS devices. The conduction scaling behavior indicates that the NiO/HfO2 bilayer has a smaller scale parameter S0 (lateral dimension of the bottleneck for the CFs). Besides this, considering some preexisting conductive paths in the NiO layer, the electric fields and the formation/rupture of CFs can be highly localized, leading to reduced switching fluctuation and improved RS performance in the NiO/HfO2-based RS devices. Moreover, asymmetric I-V curves measured in a high resistance state (HRS) in positively and negatively biased regions and the electric modulation of exchange bias (EB) arising from the Co-NiO interfacial coupling are favorable for revealing the inherent mechanism for RS. The coexistence of RS and EB is also useful to the design of novel multifunctional memory devices.

Broadband sensory networks with locally stored responsivities for neuromorphic machine vision

As the most promising candidates for the implementation of in-sensor computing, retinomorphic vision sensors can constitute built-in neural networks and directly implement multiply-and-accumulation operations using responsivities as the weights. However, existing retinomorphic vision sensors mainly use a sustained gate bias to maintain the responsivity due to its volatile nature. Here, we propose an ion-induced localized-field strategy to develop retinomorphic vision sensors with nonvolatile tunable responsivity in both positive and negative regimes and construct a broadband and reconfigurable sensory network with locally stored weights to implement in-sensor convolutional processing in spectral range of 400 to 1800 nanometers. In addition to in-sensor computing, this retinomorphic device can implement in-memory computing benefiting from the nonvolatile tunable conductance, and a complete neuromorphic visual system involving front-end in-sensor computing and back-end in-memory computing architectures has been constructed, executing supervised and unsupervised learning tasks as demonstrations. This work paves the way for the development of high-speed and low-power neuromorphic machine vision for time-critical and data-intensive applications.

Effect of long chain fatty acids on the memory switching behavior of tetraindolyl derivatives

Non-volatile memory devices using organic materials have attracted much attention due to their excellent scalability, fast switching speed, low power consumption, low cost etc. Here, we report both volatile as well as non-volatile resistive switching behavior of p-di[3,3'-bis(2-methylindolyl)methane]benzene (Indole2) and its mixture with stearic acid (SA). Previously, we have reported the bipolar resistive switching (BRS) behavior using 1,4-bis(di(1H-indol-3-yl)methyl)benzene (Indole1) molecules under ambient conditions [Langmuir 37 (2021) 4449-4459] and complementary resistive switching (CRS) behavior when the device was exposed to 353 K or higher temperature [Langmuir 38 (2022) 9229-9238]. However, the present study revealed that when the H of -NH group of Indole1 is replaced by -CH3, the resultant Indole2 molecule-based device showed volatile threshold switching behaviour. On the other hand, when Indole2 is mixed with SA at a particular mole fraction, dynamic evolution of an Au/Indole2-SA/ITO device from volatile to non-volatile switching occurred with very good device stability (>285 days), memory window (6.69 × 102), endurance (210 times), data retention (6.8 × 104 s) and device yield of the order of 78.5%. Trap controlled SCLC as well as electric field driven conduction was the key behind the observed switching behaviour of the devices. In the active layer, trap centers due to the SA network may be responsible for non-volatile characteristics of the device. Observed non-volatile switching may be a potential candidate for write once read many (WORM) memory applications in future.

Ultrafast-Programmable 2D Homojunctions Based on van der Waals Heterostructures on a Silicon Substrate

The development of electrically ultrafast-programmable semiconductor homojunctions can lead to transformative multifunctional electronic devices. However, silicon-based homojunctions are not programmable so that alternative materials need to be explored. Here 2D, multi-functional, lateral homojunctions made of van der Waals heterostructures with a semi-floating-gate configuration on a p++ Si substrate feature atomically sharp interfaces and can be electrostatically programmed in nanoseconds, more than seven orders of magnitude faster than other 2D-based homojunctions. By applying voltage pulses with different polarities, lateral p-n, n+ -n and other types of homojunctions can be formed, varied, and reversed. The p-n homojunctions possess a high rectification ratio of up to ≈105 and can be dynamically switched between four distinct conduction states with the current spanning over nine orders of magnitude, enabling them to function as logic rectifiers, memories, and multi-valued logic inverters. Built on a p++ Si substrate, which acts as the control gate, the devices are compatible with Si technology.

A Light-Programmed Rewritable Lattice-Mediated Multistate Memory for High-Density Data Storage

Mainstream non-volatile memory (NVM) devices based on floating gate structures or phase-change/ferroelectric materials face inherent limitations that compromise their suitability for long-term data storage. To address this challenge, a novel memory device based on light-programmed lattice engineering of thin rhenium disulfide (ReS2 ) flakes is proposed. By inducing sulfur vacancies in the ReS2 channel through light illumination, the device's electrical conductivity is modified accordingly and multiple conductance states for data storage therefore are generated. The device exhibits more than 128 distinct states with linearly increasing conductance, corresponding to a sevenfold increase in storage density. Through further optimization to achieve atomic-level precision in defect creation, it is possible to achieve even higher storage densities. These states are extremely stable in vacuum or inert ambient showing long retention of >10 years, while they can be erased upon exposure to the air. The ReS2 memory device can maintain its stability over multiple program-erase operation cycles and shows superior wavelength discrimination capability for incident light in the range of 405-785 nm. This device represents a significant contribution to NVM technology by offering the ability to store information in multistate memory and enabling filter-free color image recorder applications.

Recent progress in neuromorphic and memory devices based on graphdiyne

Graphdiyne (GDY) is an emerging two-dimensional carbon allotrope featuring a direct bandgap and fascinating physical and chemical properties, and it has demonstrated its promising potential in applications of catalysis, energy conversion and storage, electrical/optoelectronic devices, etc. In particular, the recent breakthrough in the synthesis of large-area, high-quality and ultrathin GDY films provides a feasible approach to developing high-performance electrical devices based on GDY. Recently, various GDY-based electrical and optoelectronic devices including multibit optoelectronic memories, ultrafast nonvolatile memories, artificial synapses and memristors have been proposed, in which GDY plays a crucial role. It is essential to summarize the recent breakthrough of GDY in device applications as a guidance, especially considering that the existing GDY-related reviews mainly focus on the applications in catalysis and energy-related fields. Herein, we review GDY-based novel memory and neuromorphic devices and their applications in neuromorphic computing and artificial visual systems. This review will provide an insight into the design and preparation of GDY-based devices and broaden the application fields of GDY.

Graphdiyne and Its Derivatives as Efficient Charge Reservoirs and Transporters in Semiconductor Devices

2D graphdiyne (GDY), which is composed of sp and sp² hybridized carbon atoms, is a promising semiconductor material with a unique porous lamellar structure. It has high carrier mobility, tunable bandgap, high density of states, and strong electrostatic interaction ability with ions and organic functional units. In recent years, interests in applying GDYs (GDY and its derivatives) in semiconductor devices have been growing rapidly, and great achievements have been made. Attractively, GDYs could act as efficient reservoirs and transporters for both carriers and ions, which endows them with enormous potential in future novel optoelectronics. In this review, the progress in this field is systematically summarized, aiming to bring an in-depth insight into the GDYs' intrinsic uniqueness. Particularly, the effects of GDYs on carrier dynamics and ionic interactions in various semiconductor devices are succinctly described, analyzed, and concluded.

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.