Resistive Switching Memory Behavior Research Articles

An Electrically Resistive Switching Nonvolatile Memory System Based on PEDOT:PSS

The current density–voltage (J–V) curves of poly(3,4‐ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) are examined at room temperature, which reveal nonlinear behavior and hysteresis loop‐like patterns. Herein, the potential of the material for nonvolatile applications requiring resistive random access memory (ReRAM) is demonstrated. The resistive switching effect is explained using a Schottky barrier and the space‐charge‐limited conduction model. Additionally, dielectric and electrical characteristics are analyzed in the frequency range from 20 Hz to 10 MHz. The impedance, electric modulus, dielectric loss tangent, and AC conductivity are explored through On‐ and Off‐states of resistive switching. A modified Debye function and Jonscher's power law are used for data fitting. The resistive switching memory behavior of PEDOT:PSS are studied using J–V and chemical impedance spectroscopy (CIS) measurements. The Cu/PEDOT:PSS/Cu sandwich‐type devices show bipolar switching behavior, and an equivalent circuit model based on the impedance spectra is proposed to describe the CIS response in both states. The switching process is attributed to the electrical‐field‐induced effect of dipolar reorientation on the electrical conductivity of PEDOT:PSS at grain boundaries.

CsPbBr3 Perovskite Quantum Dots Embedded in Polystyrene-poly2-vinyl Pyridine Copolymer for Robust and Light-Tunable Memristors

The development of a reliable optoelectronic memristor is crucial for the success of neuromorphic vision systems, but current devices are limited by stochastic resistance switching and uncontrollable ion dynamics. To address these challenges, a core–shell nanosphere composite was synthesized using CsPbBr3 quantum dots and block copolymer polystyrene-poly2-vinyl pyridine. This memristor exhibits both negative differential resistance and resistive switching memory behavior and has demonstrated exceptional stability, withstanding over 5000 cycles and remaining stable for over 5 million seconds. It is also tunable by light irradiation, making it ideal for optoelectronic logic operations and multi-derivative state applications. The memory behavior is attributed to an electrochemical metalization mechanism involving the formation and annihilation of pyridine groups, conductive metal filaments, and bromide ion vacancies in S2VP filaments. This work presents an effective method for fabricating robust multi-derivative perovskite optoelectronic devices for neuromorphic computing systems. Additionally, machine learning algorithms have demonstrated accurate digital image classification and recognition using photoelectric pulse-driven neuromorphic computation with an accuracy of over 97%.

A magnetic field controlled memristor towards the design of an implantable detector

Memristors, which combine the behaviors of memory and resistive switching (RS), have a wide application prospect in information processing and artificial neural networks. The RS memory behaviors of memristors are primarily determined by the functional layer materials, device structure, and working conditions. Herein, a CuMnO2 nanomaterial with the manganese copper ore structure was prepared on a Ti substrate by hydrothermal method, and a memristor with the Ag/CuMnO2/Ti sandwich structure was developed. The RS memory behavior of the as-prepared memristor can be regulated through a low magnetic field (MF), and thus the resistance value of device shows a multi-level resistance states. Compared with other regulation factors, the MF can remotely adjust and control the RS characteristics of memristor, which is a non-invasive and non-destructive regulatory means. The MF regulated memristor can not only be used for multi-level high-density information storage, but also it can protect the health of special populations by identifying the MF intensity of the surrounding environment. When the device is operated in an MF environment, the change of resistance value of the device in both high resistance state (HRS) and low resistance state (LRS) is mainly attributed to the influence of Loren magnetic force on conductive ions.

Nonvolatile resistive switching memory behavior in WOx/BiFeOy heterojunction based memristor

Memristors with a two-terminal structure are considered to be one of the most promising electronic devices capable of overcoming the Von Neumann bottleneck, which is highly anticipated in the post-Moore era and next-generation artificial intelligence applications. In this work, a memristive device was fabricated using a WOx/BiFeOy heterojunction as functional layer on F-doped SnO2 (FTO) substrate by magnetron sputtering. The Ag/WOx/BiFeOy/FTO device exhibits enhanced bipolar nonvolatile resistive switching (RS) memory behavior compared with single-layer BiFeOy-based memristors, which can meet the requirements of high-density information storage. By performing a comprehensive conductivity analysis on the current-voltage (I-V) curve, it was proposed a reasonable physical model to explain the RS memory behavior of the device based on space-charge-limited current (SCLC) mechanism and the Schottky emission. Therefore, this work indicates that the bilayer WOx/BiFeOy heterojunction as functional layer can effectively improve the performance of memristive devices, which will further expand the application of ferroelectric/metal oxide heterojunction in the field of memristors.

A Flexible Memristor Model With Electronic Resistive Switching Memory Behavior and Its Application in Spiking Neural Network.

Memristive technologies are attractive due to their non-volatility, high-density, low-power and compatibility with CMOS. For memristive devices, a model corresponding to practical behavioral characteristics is highly favorable for the realization of its neuromorphic system and applications. This paper presents a novel flexible memristor model with electronic resistive switching memory behavior. Firstly, the Ag-Au / MoSe2-doped Se / Au-Ag memristor is prepared using hydrothermal synthesis method and magnetron sputtering method, and its performance test is conducted on an electrochemical workstation. Then, the mathematical model and SPICE circuit model of the Ag-Au / MoSe2-doped Se / Au-Ag memristor are constructed. The model accuracy is verified by using the electrochemical data derived from the performance test. Furthermore, the proposed model is applied to the circuit implementation of spiking neural network with biological mechanism. Finally, computer simulations and analysis are carried out to verify the validity and effectiveness of the entire scheme.

Multiphotoconductance Levels of the Organic Semiconductor of Polyimide-Based Memristor Induced by Interface Charges.

A memristor with Au/polyimide (PI)/Au structure is prepared by magnetron sputtering to investigate the multiphotoconductance resistive switching (RS) memory behavior. The PI-based memristor presents stable bipolar RS memory and is sensitive to visible light. Four discrete conductance states in both high-resistance state (HRS) and low-resistance state (LRS) are obtained when illuminating by 365, 550, 590, and 780 nm light. Electron trapping and detrapping from the defects distributed at interfaces and the PI switching layer are responsible for the observed RS memory behavior. The enhanced trapping and detrapping process by light illumination is responsible for the multiconductance states. This work provides the possibility for further development of neuromorphic vision sensors using an organic semiconductor-based memristor.

Second-order associative memory circuit hardware implemented by the evolution from battery-like capacitance to resistive switching memory

SummaryMemristor-based Pavlov associative memory circuit presented today only realizes the simple condition reflex process. The secondary condition reflex endows the simple condition reflex process with more bionic, but it is only demonstrated in design and involves the large number of redundant circuits. A FeOx-based memristor exhibits an evolution process from battery-like capacitance (BLC) state to resistive switching (RS) memory as the I-V sweeping increase. The BLC is triggered by the active metal ion and hydroxide ion originated from water molecule splitting at different interfaces, while the RS memory behavior is dominated by the diffusion and migration of ion in the FeOx switching function layer. The evolution processes share the nearly same biophysical mechanism with the second-order conditioning. It enables a hardware-implemented second-order associative memory circuit to be feasible and simple. This work provides a novel path to realize the associative memory circuit with the second-order conditioning at hardware level.

Self-selective analogue FeOx-based memristor induced by the electron transport in the defect energy level

A Fe2O3 film homojunction was orderly prepared by magnetron sputtering and a hydrothermal method. The Fe2O3 homojunction-based memristor exhibits an obvious self-selective effect as well as a typical analogue resistive switching (RS) memory behavior. A desirable self-rectifying voltage range (−1 to 1 V), stable resistance ratio, good cycling endurance (>104 cycles), and long retention time (>104 s) can be obtained from the Fe2O3 homojunction-based memristor. Oxygen vacancies (Vo) are inevitably generated during the growth of the Fe2O3 film. The self-selective analogue RS memory behavior is ascribed to the electron tunneling behavior between the potential barrier generated by the FeOx contact and the electron filling dynamic in the Vo-based traps. This work provides a simple method to prepare a self-selective analogue memristor and lays the foundation for the core device of neuromorphic computing.

A physics-oriented memristor model with the coexistence of NDR effect and RS memory behavior for bio-inspired computing

Bio-inspired computing promises fundamentally different ways to advances in artificial intelligence with extreme energy efficiency. Memristive technologies due to the non-volatility, high density, low-power, and synaptic bionic properties can help in realizing bio-inspired architecture and its hardware implementation. This paper proposes a novel physics-oriented memristor model with coexistence of negative differential resistance (NDR) effect and resistive switching (RS) memory behavior for bio-inspired computing. Firstly, an Ag/TiOx/FTO memristor is fabricated using sol-gel and magnetron sputtering method, and its performance test demonstrates that the coexistence of NDR effect and RS memory behavior can be modulated by the moisture. Then, a physical-oriented memristor model is constructed, which provides the possibility to explore the dynamics of the coexistence of NDR effect and RS memory behavior in simulation. Furthermore, a memristor-based affective computing circuit emulating the process of human affective associative learning is designed. The experiment demonstrates that the coexistence of NDR effect and RS memory behavior can change the memory time without additional circuit and cost, which is expected to realize the automatic conversion from short-term memory to long-term memory in bio-inspired computing.

Investigation of multi-photoconductance state induced by light-sensitive defect in TiOx-based memristor

A TiOx switching layer with a thickness of ∼83 nm is prepared on a F-doped SnO2 (FTO) substrate by the sol-gel method to fabricate the Ag/TiOx/FTO memristor. The resistive switching memory behavior observed in the developed memristor can be efficiently modulated by the light. After modulating the light-intensity from 2.5 to 12.5 mW/mm2, five discrete photoconductance states can be obtained. The competition and synergy of the oxygen vacancy and Ag atom-based filament are responsible for the resistance switching (RS) memory behavior. The multi-photoconductance states are ascribed to the electron excited by the external light transports along the conduction filament. The programmable multi-photoconductance states provide a realistic RS memory behavior to mimic the function of a visual system.

Ternary resistive switching memory behavior of polycarbazole:TiO2 nanoparticles-based device

In this paper, the donor-acceptor copolymer poly[2,7–9- (heptadecan-9-yl)-9H-carbazole-co-12H-benzo[5,6]isoindolo[2,1-a]benzimidazole-12-one] (PCz-BI) was synthesized by Suzuki reaction. Devices based on PCz-BI and titanium dioxide (TiO2) nanoparticles composite as the active layer were prepared by a spin coating method and showed ternary resistance switching storage properties. It was shown that the addition of metal oxide nanoparticles improves memory storage performances. The optimum TiO2 content was 6 wt% and this device had the lowest SET voltage of -0.5 V and the best switching current ratio of 1:101.6:104.8. Moreover, the developed device proved as highly stable during 103 cycles. The conductivity and the structural basis for the storage mechanism were studied using electrochemical measurements, ultraviolet-visible spectroscopy, and quantum chemical calculations.

RRAM and WORM memory devices using Protamine Sulfate and Graphene Oxide

Biomaterials are extensively exploited as the resistive switching materials since last decade. Biomaterials such as proteins, DNA, enzymes, polysaccharides, starch, natural materials are being used as the active layer for the resistive switching memory devices. In this report we have investigated the Resistive Switching (RS) Memory behavior of a biomolecule Protamine Sulfate (PS), Graphene Oxide (GO) and their mixture. It has been observed that RS device having pure PS or GO as the active layer showed non-volatile memory behavior suitable for Write Once Read Many (WORM) memory applications. Dynamic transition of switching behavior from WORM to bipolar switching observed in the device designed with PS + GO mixed system. In case of the mixed film the set and reset power is found to be less than the individuals which is advantageous with respect to the power consumption. The memory window is also found to be increased multiple times.

Superlow Power Consumption Artificial Synapses Based on WSe2 Quantum Dots Memristor for Neuromorphic Computing.

As the emerging member of zero-dimension transition metal dichalcogenide, WSe2 quantum dots (QDs) have been applied to memristors and exhibited better resistance switching characteristics and miniaturization size. However, low power consumption and high reliability are still challenges for WSe2 QDs-based memristors as synaptic devices. Here, we demonstrate a high-performance, superlow power consumption memristor device with the structure of Ag/WSe2 QDs/La0.3Sr0.7MnO3/SrTiO3. The device displays excellent resistive switching memory behavior with a ROFF/RON ratio of ~5 × 103, power consumption per switching as low as 0.16 nW, very low set, and reset voltage of ~0.52 V and~ -0.19 V with excellent cycling stability, good reproducibility, and decent data retention capability. The superlow power consumption characteristic of the device is further proved by the method of density functional theory calculation. In addition, the influence of pulse amplitude, duration, and interval was studied to gradually modulating the conductance of the device. The memristor has also been demonstrated to simulate different functions of artificial synapses, such as excitatory postsynaptic current, spike timing-dependent plasticity, long-term potentiation, long-term depression, and paired-pulse facilitation. Importantly, digit recognition ability based on the WSe2 QDs device is evaluated through a three-layer artificial neural network, and the digit recognition accuracy after 40 times of training can reach up to 94.05%. This study paves a new way for the development of memristor devices with advanced significance for future low power neuromorphic computing.

Refining the Negative Differential Resistance Effect in a TiOx-Based Memristor.

The N-type negative difference resistance (NDR) is characterized by the peak/valley voltage (Vp/Vv) and the corresponding current (Ip/Iv). The N-type NDR is observed in the resistive switching (RS) memory device of Ag|TiO2|F-doped SnO2 at room temperature. After the TiO2 film is equipped with a nanoporous array, the ∼1.2 V gap voltage between Vp and Vv is effectively downscaled to ∼0.5 V, and the gap current of ∼7.23 mA between Ip and Iv is improved to ∼30 mA. It demonstrates that a lower power consumption and faster switching time of the NDR can be obtained in the memristor. Compensations and synergies among the nanoscale conduction filaments (OH-, Ag+, and Vo) are responsible for the refining NDR behavior in our devices. This work provides an efficient method to construct a high-performance N-type NDR effect at room temperature and gives a new horizon on the coexistence of this type of NDR effect and RS memory behaviors.

Negative Photoconductance Effect: An Extension Function of the TiOx‐Based Memristor

AbstractThe negative photoconductance (NPC) effect, defined as an increase in resistance upon exposure to illumination, holds great potential for application in photoelectric devices. A prepared memristor with the structure of Ag|graphene quantum dots (GQDs)|TiOx|F‐doped SnO2 exhibits typical bipolar resistive switching (RS) memory behavior. The NPC effect is impressively observed in the high resistance state branch of the RS memory, enabling the memristor function to be extended to both memory logic display and multistate data storage. The observed NPC effect is attributed to the excitation, migration, and compensation of oxygen vacancy at the GQDs/TiOx interface, at which the electron transportation is efficiently restricted because of the variation in the charge distribution and electrostatic potential under illumination. Experiments, theoretical calculations, and physical models are used to provide engineer the interface with the aim of building the NPC effect in the memristive device. These results unveil a new horizon on extending the functionality of the memristor.

A Visible Light Modulated Resistive Switching Memory Behaviors in the Ta/BiFeO3/Carbon/BaTiO3/Si Device

A bipolar resistance switching memory effect is observed in the Ta/BiFeO3/carbon/BaTiO3/Si structure. The resistance switching (RS) behavior can be modulated by an optical signal. The HRS/LRS resistance ratio and threshold voltage change remarkably under white-light irradiation. The trap-based charges in the Schottky-like depletion layers excited by the white light are responsible for the white-light controlled RS memory behaviors. This research is useful in exploring multi-functional materials and applications in optical-controlled nonvolatile memory devices.

Compliance current controlled volatile and nonvolatile memory in Ag/CoFe2O4/Pt resistive switching device

We report on the resistive memory effects of a Ag/CoFe2O4/Pt device and a deterministic conversion between volatile and nonvolatile resistive switching (RS) memory through the tuning of current compliance (I CC). For the smaller I CC (10−4 A) the device exhibits volatile RS behavior with an atomically sized conducting filament showing the quantum conductance. For an intermediate I CC (10−2 A) nonvolatile bipolar RS behavior is observed, which could originate from the formation and rupture of filament consisting of Ag ions. The high resistance state (HRS) of the device shows a semiconducting conduction mechanism, whereas the low resistance state (LRS) was found to be Ohmic in nature. The temperature dependent resistance studies and magnetization studies indicated that the electrochemical metallization plays a dominant role in the resistive switching process for volatile and nonvolatile modes through the formation of Ag conducting filaments. For higher I CC (10−1 A) the device permanently switches to LRS. The irreversible RS memory behaviors, observed for higher I CC, could be attributed to the formation of a thick and stable conducting channel formed of oxygen vacancies and Ag ions. The compliance current controlled resistive switching modes with a large memory window make the present device a potential candidate to pave the way for future resistive switching devices.

A versatile multifaceted resistive switching memory activated by light and ion irradiation in poly (3-octylthiophene)-zinc oxide hybrids

Abstract The resistive switching memory behavior activated by simulated solar light and swift heavy ion irradiation in poly (3-octylthiophene)-zinc oxide hybrid devices are reported. The current-voltage characteristics show the appearance of a remarkable hysteresis in reverse bias and a considerable in a forward bias upon illumination by simulated solar light results in memory behavior. Ion irradiation exhibits strong enhancement of the memory behavior under both dark and light illuminations. Thus, the memory response is activated and/or enhanced upon illumination by light and irradiation along with the cyclic endurance of the devices. This is attributed due to the formation of well built-in conducting filament pathways through the trapping of injected and photo-generated charges via irradiation-induced electrically active defect and trap states and well explained by a schematic energy band diagram. The defect density induced upon ion irradiation works as a dominant factor and thus the tailoring of the interfacial properties of the hybrid devices leads to the strong strengthening of memory formations. Thus, the hybrid devices can be activated and/or enhanced by light and irradiation for potential fast resistive switching memory applications.

Complementary Resistive Switching and Synaptic-Like Memory Behavior in an Epitaxial SrFeO2.5 Thin Film through Oriented Oxygen-Vacancy Channels.

Oxygen-vacancy-ordered brownmillerite oxides offer a reversible topotactic phase transition by significantly varying the oxygen stoichiometry of the material without losing its lattice framework. This phase transition leads to substantial changes in the physical and chemical properties of brownmillerite oxides, including electrical and ion conductivity, magnetic state, and oxygen diffusivity. In this study, the variations in the resistive switching mode of the epitaxial brownmillerite SrFeO2.5 thin film in the device were studied by systematically controlling the oxygen concentration, which could be varied by changing the compliance current during the first electroforming step. Depending on the compliance current, the SrFeO2.5 devices exhibited either low-power bipolar resistive switching or complementary resistive switching behaviors. A physical model based on the internal redistribution of oxygen ions between the interfaces with the top and the bottom electrodes was developed to explain the complementary resistive switching behavior. This model was experimentally validated using impedance spectroscopy. Finally, the gradual conductance variation in the brownmillerite SrFeO2.5 thin films was exploited to realize synaptic learning.

Multilevel resistive switching memory behaviors arising from ion diffusion and photoelectron transfer in α-Fe2O3 nano-island arrays.

Resistive switching (RS) memory behaviors are observed in an Ag|α-Fe2O3|Ti device after operating under an ultralow bias voltage of ±0.1 V. An SET voltage of ∼20 mV is obtained under illumination. Multilevel RS memory is realized under photoelectric signal control. The separation and fast transfer of hole-electron pairs are responsible for the enhanced RS memory under illumination.