Toward a Reliable Synaptic Simulation Using Al-Doped HfO2 RRAM

Vanadium Dioxide by Atomic Layer Deposition: A Promising Material for Next-Generation Memory Devices

The synthesis of a vanadium dioxide (VO2) film using atomic layer deposition (ALD) with vanadium tetrachloride (VCl4) as a precursor for the realization of programmable memory devices is reported. X-ray diffraction analysis revealed the epitaxial growth of VO2 on c-Al2O3. The phase transition was monitored using resistivity measurements across varying temperatures, demonstrating a decrease of >4 orders of magnitude at the transition temperature, thereby confirming the high quality of the material. From this material, memristive devices are fabricated as resistive random-access memory (RRAM). On the basis of spiking voltage inputs, these RRAM exhibited cycle stability over 512 cycles and state retention stability for >450 s, showing <2% drift. With respect to synaptic-like applications, the RRAM devices were piloted through step patterns to enable multilevel memory states. These ALD-grown VO2-based devices demonstrate potential for use as synaptic connections with multiweight synapses, advancing scalability in neuromorphic applications.

In-Materia Annealing and Combinatorial Optimization Based on Vertical Memristive Array

Due to its area and energy efficiency, a memristive crossbar array (CBA) has been extensively studied for various combinatorial optimization applications, from network problems to circuit design. However, conventional approaches include heavily burdening software fine-tuning for the annealing process. Instead, this study introduces the "in-materia annealing" method, where the inter-layer interference of vertically stacked memristive CBA is utilized as an annealing method. When mapping combinatorial optimization problems into the configuration layer of the CBA, exponentially decaying annealing profiles are generated in nearby noise layers. Moreover, in-materia annealing profiles can be controlled by changing compliance current, read voltage, and read pulse width. Therefore, the annealing profiles can be arbitrarily controlled and generated individually for each cell, providing rich noise sources to solve the problem efficiently. Consequently, the experimental and simulation of Max-Cut and weighted Max-Cut problems achieve notable results with the minimum software burden.

A Zero-Voltage-Writing Artificial Nervous System Based on Biosensor Integrated on Ferroelectric Tunnel Junction

The artificial nervous system proves the great potential for the emulation of complex neural signal transduction. However, a more bionic system design for bio-signal transduction still lags behind that of physical signals, and relies on additional external sources. Here, this work presents a zero-voltage-writing artificial nervous system (ZANS) that integrates a bio-source-sensing device (BSSD) for ion-based sensing and power generation with a hafnium-zirconium oxide-ferroelectric tunnel junction (HZO-FTJ) for the continuously adjustable resistance state. The BSSD can use ion bio-source as both perception and energy source, and then output voltage signals varied with the change of ion concentrations to the HZO-FTJ, which completes the zero-voltage-writing neuromorphic bio-signal modulation. In view of in/ex vivo biocompatibility, this work shows the precise muscle control of a rabbit leg by integrating the ZANS with a flexible nerve stimulation electrode. The independence on external source enhances the application potential of ZANS in robotics and prosthetics.

Compliance-free, analog RRAM devices based on SnOx

Brain-inspired resistive random-access memory (RRAM) technology is anticipated to outperform conventional flash memory technology due to its performance, high aerial density, low power consumption, and cost. For RRAM devices, metal oxides are exceedingly investigated as resistive switching (RS) materials. Among different oxides, tin oxide (SnOx) received minimal attention, although it possesses excellent electronic properties. Herein, we demonstrate compliance-free, analog resistive switching behavior with several stable states in Ti/Pt/SnOx/Pt RRAM devices. The compliance-free nature might be due to the high internal resistance of SnOx films. The resistance of the films was modulated by varying Ar/O2 ratio during the sputtering process. The I-V characteristics revealed a well-expressed high resistance state (HRS) and low resistance states (LRS) with bipolar memristive switching mechanism. By varying the pulse amplitude and width, different resistance states have been achieved, indicating the analog switching characteristics of the device. Furthermore, the devices show excellent retention for eleven states over 1000 s with an endurance of > 100 cycles.

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

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

Enhanced linear and symmetric synaptic weight update characteristics in a Pt/p-LiCoOx/p-NiO/Pt memristor through interface energy barrier modulation by Li ion redistribution

Artificial synaptic devices have been extensively investigated for neuromorphic computing systems, which require synaptic behaviors mimicking the biological ones. In particular, a highly linear and symmetric weight update with a conductance (or resistance) change for potentiation and depression operation is one of the essential requirements for energy-efficient neuromorphic computing; however, it is not sufficiently met. In this study, a memristor with a Pt/p-LiCoOx/p-NiO/Pt structure is investigated, where a low interface energy barrier between the Pt electrode and the NiO layer makes for a more linear and symmetric conductance change. In addition, the use of voltage-driven Li+ ion redistribution in the NiO layer facilitates the analog conductance change at a low voltage. Besides the linear and symmetric potentiation and depression weight updates, the memristor exhibits various synaptic characteristics such as the dependence of weight update on the pulse amplitude and number, paired pulse facilitation, and short-term and long-term plasticity. The conductance modulation is thought to be induced by a tunable interface energy barrier at the NiO layer and Pt bottom electrode, as a result of Li+ ion diffusion in NiO supplied from the LiCoOx layer and their redistribution. Thanks to the use of Li+ ion redistribution, the conductance change could be achieved at a voltage <4 V within the time of μs range. These results verify the potential of artificial synapses with the Pt/LiCoOx/NiO/Pt memristor operated by voltage-driven Li+ ion redistribution under the low interface energy barrier conditions, realizing a highly linear and symmetric weight update at a low voltage with a high speed for energy-efficient neuromorphic computing systems.

Study of resistive switching behavior in HfO2nanocrystals synthesized via a low temperature hydrothermal method

The resistive switching property in HfO2have attracted increasing interest in recent years. In this work, amorphous HfO2nanocrystals are synthesized by a facile hydrothermal method. Then, the as-synthesized nanocrystals are rapid thermal annealed in different atmospheres for improving the crystal quality, and monoclinic phase is determined as the main crystal structure of the annealed HfO2. Subsequently, metal-insulator-metal structure devices based on HfO2samples are fabricated. Electrical measurement indicates that 700 °C annealing processes in Air and Ar environments can slightly improve the bipolar resistive switching and retention behaviors. Higher annealed temperature (900 °C) will further improve the crystal quality of HfO2, while the resistive switching and retention behaviors of the devices continuously attenuate, which can be ascribed to the reduction of the conductive filaments induced by defects.

Role of oxygen vacancies in ferroelectric or resistive switching hafnium oxide

HfO2 shows promise for emerging ferroelectric and resistive switching (RS) memory devices owing to its excellent electrical properties and compatibility with complementary metal oxide semiconductor technology based on mature fabrication processes such as atomic layer deposition. Oxygen vacancy (Vo), which is the most frequently observed intrinsic defect in HfO2-based films, determines the physical/electrical properties and device performance. Vo influences the polymorphism and the resulting ferroelectric properties of HfO2. Moreover, the switching speed and endurance of ferroelectric memories are strongly correlated to the Vo concentration and redistribution. They also strongly influence the device-to-device and cycle-to-cycle variability of integrated circuits based on ferroelectric memories. The concentration, migration, and agglomeration of Vo form the main mechanism behind the RS behavior observed in HfO2, suggesting that the device performance and reliability in terms of the operating voltage, switching speed, on/off ratio, analog conductance modulation, endurance, and retention are sensitive to Vo. Therefore, the mechanism of Vo formation and its effects on the chemical, physical, and electrical properties in ferroelectric and RS HfO2 should be understood. This study comprehensively reviews the literature on Vo in HfO2 from the formation and influencing mechanism to material properties and device performance. This review contributes to the synergetic advances of current knowledge and technology in emerging HfO2-based semiconductor devices.

Research on electronic synaptic simulation of HfO2-based memristor by embedding Al2O3

The potential of neuromorphic computing in synaptic simulation has led to a renewed interest in memristor. However, the demand for multilevel resistive switching with high reliability and low power consumption is still a great resistance in this application. In this work, the electronic synaptic plasticity and simulated bipolar switching behavior of Pt/Al2O3(2 nm)/HfO2(10 nm)/Al2O3(2 nm)/Ti tri-layer memristor is investigated. The effect of Al2O3layer embedded at the top electrode and the bottom electrode on the resistive performance of the memristor was studied. It is found that both of them can effectively improve the reliability of the device (104cycles), the resistive window (>103), the tunable synaptic linearity and reduce of the operating voltage. RRAM with Al2O3embedded at the top electrode have higher uniformity and LTP linearity, while those with Al2O3embedded at the bottom electrode significantly reduce the operating current (∼10μA) and improve LTD linearity. Electron transport mechanisms were compared between single-layer HfO2and tri-layer Al2O3/HfO2/Al2O3samples under DC scanning. The results showed that the thin Al2O3layer at the top electrode led to Fowler Northeim tunneling in the low-resistance state, while the thin Al2O3layer at the bottom electrode led to Schottky emission in the high-resistance state. The Al2O3/HfO2/Al2O3memristors were successfully used to achieve synaptic properties, including enhancement, inhibition, and spike time-dependent plasticity, demonstrating an important role in high-performance neuromorphic computing applications.

Artificial Synapse Emulated by Indium Tin Oxide/SiN/TaN Resistive Switching Device for Neuromorphic System

In this paper, we fabricate an ITO/SiN/TaN memristor device and analyze its electrical characteristics for a neuromorphic system. The device structure and chemical properties are investigated using transmission electron microscopy and X-ray photoelectron spectroscopy. Uniform bipolar switching is achieved through DC sweep under a compliance current of 5 mA. Also, the analog reset phenomenon is observed by modulating the reset voltage for long-term memory. Additionally, short-term memory characteristics are obtained by controlling the strength of the pulse response. Finally, bio-inspired synaptic characteristics are emulated using Hebbian learning rules such as spike-rate-dependent plasticity (SRDP) and spike-timing-dependent plasticity (STDP). As a result, we believe that the coexistence of short-term and long-term memories in the ITO/SiN/TaN device can provide flexibility in device design in future neuromorphic applications.

Mimicking biological synapses with a-HfSiOx-based memristor: implications for artificial intelligence and memory applications

Memristors, owing to their uncomplicated structure and resemblance to biological synapses, are predicted to see increased usage in the domain of artificial intelligence. Additionally, to augment the capacity for multilayer data storage in high-density memory applications, meticulous regulation of quantized conduction with an extremely low transition energy is required. In this work, an a-HfSiOx-based memristor was grown through atomic layer deposition (ALD) and investigated for its electrical and biological properties for use in multilevel switching memory and neuromorphic computing systems. The crystal structure and chemical distribution of the HfSiOx/TaN layers were analyzed using X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS), respectively. The Pt/a-HfSiOx/TaN memristor was confirmed by transmission electron microscopy (TEM) and showed analog bipolar switching behavior with high endurance stability (1000 cycles), long data retention performance (104 s), and uniform voltage distribution. Its multilevel capability was demonstrated by restricting current compliance (CC) and stopping the reset voltage. The memristor exhibited synaptic properties, such as short-term plasticity, excitatory postsynaptic current (EPSC), spiking-rate-dependent plasticity (SRDP), post-tetanic potentiation (PTP), and paired-pulse facilitation (PPF). Furthermore, it demonstrated 94.6% pattern accuracy in neural network simulations. Thus, a-HfSiOx-based memristors have great potential for use in multilevel memory and neuromorphic computing systems.

Proton-Gated Synaptic Transistors, Based on an Electron-Beam Patterned Nafion Electrolyte

Neuromorphic processors using artificial neural networks are the center of attention for energy-efficient analog computing. Artificial synapses act as building blocks in such neural networks for parallel information processing and data storage. Herein we describe the fabrication of a proton-gated synaptic transistor using a Nafion electrolyte thin film, which is patterned by electron-beam lithography (EBL). The device has an active channel of indium-zinc-oxide (IZO) between the source and drain electrodes, which shows Ohmic behavior with a conductance level on the order of 100 μS. Under voltage applications to the gate electrode, the channel conductance is changed due to the injection and extraction of protons between the IZO channel and the Nafion electrolyte, emulating various synaptic functions with short-term and long-term plasticity. When positive (negative) gate voltage pulses are consecutively applied, the device exhibits long-term potentiation (depression) at the same number of steps as the number of input pulses. Based on these characteristics, an artificial neural network using this transistor shows ∼84% image recognition accuracy for handwritten digits. The subject transistor also successfully mimics paired-pulse facilitation and depression, Hebbian spike-timing-dependent plasticity, and Pavlovian associative learning followed by extinction activities. Finally, dynamical pattern image memorization is demonstrated in a 5 × 5 array of these synaptic transistors. The results indicate that EBL patternable Nafion electrolytes have great potential for use in the fabrication and circuit-level integration of synaptic devices for neuromorphic computing applications.

Effect of Y-doping on switching mechanisms and impedance spectroscopy of HfOx-based RRAM devices

Y-doping can effectively improve the performance of HfO_x-based resistive random-access memory (RRAM) devices, but the underlying physical mechanism of Y-doping affecting the performance of HfO_x-based memristors is still missing and unclear. Although impedance spectroscopy (IS) has been widely used to investigate impedance characteristics and switching mechanisms of RRAM devices, there is less IS analysis on Y-doped HfO_x-based RRAM devices as well as devices at different temperatures. Here, the effect of Y-doping on the switching mechanism of HfO_x-based RRAM devices with a Ti/HfO_x/Pt structure were reported using current-voltage characteristics and IS. The results indicated that doping Y into HfO_xfilms could decrease the forming/operate voltage and improve the RS uniform. Both doped and undoped HfO_x-based RRAM devices obeyed the oxygen vacancies (V_O) conductive filament model along the grain boundary (GB). Additionally, the GB resistive activation energy of the Y-doped device was inferior to that of the undoped device. It exhibited a shift of theV_Otrap level towards the conduction band bottom after Y-doping in the HfO_xfilm, which was the main reason for the improved RS performance.

Investigation of Different Oxygen Partial Pressures on MgGa2O4-Resistive Random-Access Memory

Different oxygen partial-pressure MgGa₂O₄-resistive RAMs (RRAMs) are fabricated to investigate the resistive switching behaviors. The X-ray photoelectron spectroscopy results, set voltage, reset voltage, cycling endurance, and retention time are drawn for comparison. With the increasing oxygen ratio gas flow, the resistive switching characteristics of MgGa₂O₄ RRAM are drastically elevated by changing the fabrication conditions of the RS layer. Moreover, we portray a filament model to explain the most likely mechanism associated with the generation and rupture of conductive filaments composed of oxygen vacancies. The formation of the interfacial layer (AlO _x ) and the participation of the Joule heating effect are included to explain the highly distributed high-resistance state (HRS). The high randomness among switching cycles for memory application should be prevented, but it is suitable for the physical unclonable function. The relationship between HRS and the next time set voltage shows a strong correlation, and the conduction mechanisms of the low-resistance state (LRS) and HRS correspond to ohmic conduction and space charge-limited conduction, respectively. Meanwhile, the RRAM undergoes 10,000 s retention tests, and the two resistance states can be distinguished without obvious alternation or degradation. A favorable cycling endurance and retention time achieved by optimizing the fabrication parameters of Al/MgGa₂O₄/Pt RRAM have the potential for nonvolatile memristors and information security applications.

Enhancement of Resistive Switching Performance in Hafnium Oxide (HfO2) Devices via Sol-Gel Method Stacking Tri-Layer HfO2/Al-ZnO/HfO2 Structures

Resistive random-access memory (RRAM) is a promising candidate for next-generation non-volatile memory. However, due to the random formation and rupture of conductive filaments, RRMS still has disadvantages, such as small storage windows and poor stability. Therefore, the performance of RRAM can be improved by optimizing the formation and rupture of conductive filaments. In this study, a hafnium oxide-/aluminum-doped zinc oxide/hafnium oxide (HfO₂/Al-ZnO/HfO₂) tri-layer structure device was prepared using the sol-gel method. The oxygen-rich vacancy Al-ZnO layer was inserted into the HfO₂ layers. The device had excellent RS properties, such as an excellent switch ratio of 10⁴, retention of 10⁴ s, and multi-level storage capability of six resistance states (one low-resistance state and five high-resistance states) and four resistance states (three low-resistance states and one high-resistance state) which were obtained by controlling stop voltage and compliance current, respectively. Mechanism analysis revealed that the device is dominated by ohmic conduction and space-charge-limited current (SCLC). We believe that the oxygen-rich vacancy concentration of the Al-ZnO insertion layer can improve the formation and rupture behaviors of conductive filaments, thereby enhancing the resistive switching (RS) performance of the device.

Ag/HfOx/Pt Unipolar Memristor for High-Efficiency Logic Operation

Unipolar resistive switching (URS) behavior, known as the SET and RESET operating in a single voltage sweep direction, has shown great potential in the simplification of the peripheral circuit. The URS memristor always involves complicated interfacial engineering and structural design. In this work, a reliable URS behavior is realized using a simple Ag/HfO_x/Pt memristor structure. The memristor displays a retention time of >10⁴ s, an ON/OFF ratio of >10³, and a good operation voltage. Synergy and competition between the Ag conductive filament formed by redox reaction and the migration of an oxygen vacancy are responsible for the observed URS. By comparison, a 35% power consumption is reduced during the logical operation from 0 to 1 to 0. The operation strategy is demonstrated by exhibiting the ACSII code of the capital letter denoted by eight logic states. This work provides a low-power concept for ultrahigh data storage using the URS memristor.

Aliovalent Ta-Doping-Engineered Oxygen Vacancy Configurations for Ultralow-Voltage Resistive Memory Devices: A DFT-Supported Experimental Study

Alteration of transport properties of any material, especially metal oxides, by doping suitable impurities is not straightforward as it may introduce multiple defects like oxygen vacancies (V_o) in the system. It plays a decisive role in controlling the resistive switching (RS) performance of metal oxide-based memory devices. Therefore, a judicious choice of dopants and their atomic concentrations is crucial for achieving an optimum V_o configuration. Here, we show that the rational designing of RS memory devices with cationic dopants (Ta), in particular, Au/Ti_1-xTa_xO_2-δ/Pt devices, is promising for the upcoming non-volatile memory technology. Indeed, a current window of ∼10⁴ is realized at an ultralow voltage as low as 0.25 V with significant retention (∼10⁴ s) and endurance (∼10⁵ cycles) of the device by considering 1.11 at % Ta doping. The obtained device parameters are compared with those in the available literature to establish its excellent performance. Furthermore, using detailed experimental analyses and density functional theory (DFT)-based first-principles calculations, we comprehend that the meticulous presence of V_o configurations and the columnar-like dendritic structures is crucial for achieving ultralow-voltage bipolar RS characteristics. In fact, the dopant-mediated V_o interactions are found to be responsible for the enhancement in local current conduction, as evidenced from the DFT-simulated electron localization function plots, and these, in turn, augment the device performance. Overall, the present study on cationic-dopant-controlled defect engineering could pave a neoteric direction for future energy-efficient oxide memristors.

Review of electrical stimulus methods of in situ transmission electron microscope to study resistive random access memory

Resistive random access memory (RRAM) devices have been demonstrated to be a promising solution for the implementation of a neuromorphic system with high-density synapses due to the simple device structure, nanoscale dimension, high switching speed, and low power consumption. Various electrical stimuli applied to RRAM devices could cause various working modes of the bionic synapses. The application of RRAM devices needs to understand the micromechanism of the resistive switching process, which is inseparable from advanced characterization techniques. In situ transmission electron microscopy (TEM) with high-resolution imaging and versatile external fields plays an important role in the static characterization and dynamic manipulation of nanoscale devices. Focused on in situ TEM techniques, this review article introduces in situ TEM setups and the corresponding sample fabrication process for RRAM research. Then, the electrical stimulating methodologies including pulse and direct current voltage applied to RRAM are introduced, followed by the summary of electron holography to characterize the electrical potential distribution. By applying various electrical stimuli to the RRAM samples, the working mode of bionic synapses could be changed according to the requirement. Finally, the outlook of the RRAM study with in situ TEM is proposed. This review demonstrates the electrical stimulus capability of in situ TEM to understand the physical mechanism of various types of RRAM devices.

Hafnium Oxide (HfO2 ) - A Multifunctional Oxide: A Review on the Prospect and Challenges of Hafnium Oxide in Resistive Switching and Ferroelectric Memories

Hafnium oxide (HfO₂ ) is one of the mature high-k dielectrics that has been standing strong in the memory arena over the last two decades. Its dielectric properties have been researched rigorously for the development of flash memory devices. In this review, the application of HfO₂ in two main emerging nonvolatile memory technologies is surveyed, namely resistive random access memory and ferroelectric memory. How the properties of HfO₂ equip the former to achieve superlative performance with high-speed reliable switching, excellent endurance, and retention is discussed. The parameters to control HfO₂ domains are further discussed, which can unleash the ferroelectric properties in memory applications. Finally, the prospect of HfO₂ materials in emerging applications, such as high-density memory and neuromorphic devices are examined, and the various challenges of HfO₂ -based resistive random access memory and ferroelectric memory devices are addressed with a future outlook.

Improved Performance of NbOx Resistive Switching Memory by In-Situ N Doping

Valence change memory (VCM) attracts numerous attention in memory applications, due to its high stability and low energy consumption. However, owing to the low on/off ratio of VCM, increasing the difficulty of information identification hinders the development of memory applications. We prepared N-doped NbO_x:N films (thickness = approximately 15 nm) by pulsed laser deposition at 200 °C. N-doping significantly improved the on/off ratio, retention time, and stability of the Pt/NbO_x:N/Pt devices, thus improving the stability of data storage. The Pt/NbO_x:N/Pt devices also achieved lower and centralized switching voltage distribution. The improved performance was mainly attributed to the formation of oxygen vacancy (V_O) + 2N clusters, which greatly reduced the ionic conductivity and total energy of the system, thus increasing the on/off ratio and stability. Moreover, because of the presence of Vo + 2N clusters, the conductive filaments grew in more localized directions, which led to a concentrated distribution of SET and RESET voltages. Thus, in situ N-doping is a novel and effective approach to optimize device performances for better information storage and logic circuit applications.

Tunable biological nonvolatile multilevel data storage devices

The speed with which electronic products are updated is continuously increasing. Consequently, since waste electronic products can cause serious environmental pollution, the demand for electronic products made of biological materials is becoming increasingly urgent. Although biological memristors have significant advantages, their electrical characteristics still do not meet the requirements to be used in future nonvolatile memories. Therefore, how to control their electrical characteristics has become a popular topic of research. In this study, tunable biomemristors with an Al/tussah blood (TB)-carbon nanotube (CNT)/indium tin oxide (ITO)/glass structure were fabricated. Such a device exhibits stable bipolar resistance switching behavior and good retention characteristics (10⁴ s). Experimental results show that the ON/OFF current ratio can be effectively controlled by modifying the CNT concentration in the TB-CNT composite film. Multilevel (8 levels, 3 bits per cell) storage capabilities can be achieved in the device by controlling its compliance current in order to achieve high-density storage. The resistance switching behavior originates from the formation and rupture of conductive oxygen vacancy filaments. TB is a promising natural biomaterial in the field of green electronics, and this research could blaze a new trail for the development of biological memory devices. Biomemristors with multilevel resistance states can be used as electronic synapses and are one of the choices for simulating biological synapses.

Ternary Conductance Switching Realized by a Pillar[5]arene-Functionalized Two-Dimensional Imine Polymer Film

Nowadays, most manufacturing memory devices are based on materials with electrical bistability (i. e., "0" and "1") in response to an applied electric field. Memory devices with multilevel states are highly desired so as to produce high-density and efficient memory devices. Herein, we report the first multichannel strategy to realize a ternary-state memristor. We make use of the intrinsic sub-nanometer channel of pillar[5]arene and nanometer channel of a two-dimensional imine polymer to construct an active layer with multilevel channels for ternary memory devices. Low threshold voltage, long retention time, clearly distinguishable resistance states, high ON/OFF ratio (OFF/ON1/ON2=1 : 10 : 10³ ), and high ternary yield (75 %) were obtained. In addition, the flexible memory device based on 2DP_TPAZ+TAPB can maintain its stable ternary memory performance after being bent 500 times. The device also exhibits excellent thermal stability and can tolerate a temperature as high as 300 °C. It is envisioned that the results of this work will open up possibilities for multistate, flexible resistive memories with good thermal stability and low energy consumption, and broaden the application of pillar[n]arene.

Bioresistive Random-Access Memory with Gold Nanoparticles that Generate the Coulomb Blocking Effect Can Realize Multilevel Data Storage and Synapse Simulation

Gold nanoparticles (Au NPs) have good biocompatibility and special quantum effects. In this Letter, we embedded Au NPs into silkworm hemolymph (SH) to improve the performance of the device and fabricated Al/SH:Au NPs/indium tin oxide (ITO)/glass resistive random access memory. The device exhibits a bipolar switching behavior with a retention time of 10⁴ s. Compared with the Al/SH/ITO device without Au NPs, the device has a higher ON/OFF current ratio (>10⁵) and a smaller V_reset. The improvement in device performance is attributed to the fact that Au NPs act as the electron-trapping center in the device; a Coulomb blockade occurs after electrons are trapped, thereby increasing the resistance of the device in the high-resistance state. Using optimized devices can realize multilevel data storage and can also simulate synaptic characteristics such as potentiation and depression. The device is expected to be applied to high-density, low-cost, degradable, and biocompatible storage devices and neuromorphic computing in the future.

Wide range modulation of synaptic weight in thin-film transistors with hafnium oxide gate insulator and indium-zinc oxide channel layer for artificial synapse application

Wide range synaptic weight modulation with a tunable drain current was demonstrated in thin-film transistors (TFTs) with a hafnium oxide (HfO2-x) gate insulator and an indium-zinc oxide (IZO) channel layer for application to artificial synapses in neuromorphic systems. The drain current in these TFTs was reduced significantly by four orders of magnitude on application of a negative gate bias, then could be restored to its original value by applying a positive bias. The reduced drain current under negative biasing is interpreted as being caused by voltage-driven oxygen ion migration from the HfO2-x gate insulator to the IZO channel, which reduces the oxygen vacancy concentration in the IZO channel. In addition to emulating the analog-type potentiation and depression motions in artificial synapses, the tunable drain current presents paired-pulse facilitation and short-term and long-term plasticity behaviors. These wide-ranging and nonvolatile synaptic behaviors with tunable drain currents are indicative of the potential of the proposed TFTs for artificial synapse applications.

Multi-Level Switching of Al-Doped HfO2 RRAM with a Single Voltage Amplitude Set Pulse

In this paper, the resistive switching characteristics in a Ti/HfO2: Al/Pt sandwiched structure are investigated for gradual conductance tuning inherent functions. The variation in conductance of the device under different amplitudes and voltage pulse widths is studied. At the same time, it was found that the variation in switching parameters in resistive random-access memory (RRAM) under impulse response is impacted by the initial conductance states. The device was brought to a preset resistance value range by energizing a single voltage amplitude pulse with a different number of periodicities. This is an efficient and simple programming algorithm to simulate the strength change observed in biological synapses. It exhibited an on/off of about 100, an endurance of over 500 cycles, and a lifetime (at 85 °C) of around 105 s. This multi-level switching two-terminal device can be used for neuromorphic applications to simulate the gradual potentiation (increasing conductance) and inhibition (decreasing conductance) in an artificial synapse.

Advances of RRAM Devices: Resistive Switching Mechanisms, Materials and Bionic Synaptic Application

Resistive random access memory (RRAM) devices are receiving increasing extensive attention due to their enhanced properties such as fast operation speed, simple device structure, low power consumption, good scalability potential and so on, and are currently considered to be one of the next-generation alternatives to traditional memory. In this review, an overview of RRAM devices is demonstrated in terms of thin film materials investigation on electrode and function layer, switching mechanisms and artificial intelligence applications. Compared with the well-developed application of inorganic thin film materials (oxides, solid electrolyte and two-dimensional (2D) materials) in RRAM devices, organic thin film materials (biological and polymer materials) application is considered to be the candidate with significant potential. The performance of RRAM devices is closely related to the investigation of switching mechanisms in this review, including thermal-chemical mechanism (TCM), valance change mechanism (VCM) and electrochemical metallization (ECM). Finally, the bionic synaptic application of RRAM devices is under intensive consideration, its main characteristics such as potentiation/depression response, short-/long-term plasticity (STP/LTP), transition from short-term memory to long-term memory (STM to LTM) and spike-time-dependent plasticity (STDP) reveal the great potential of RRAM devices in the field of neuromorphic application.