Memristive Memory Research Articles

Mechanism analysis of a flexible organic memristive memory with capacitance effect and negative differential resistance state

It has been gradually realized that the sustainable electronic devices are of great prospects for sustainable applications in electronic technology products. From another point of view, a device with multiple physical performances would be a potential candidate for next generation multifunctional electronics. In this report, a flexible memory device based on sweet potato skin (SPS) was demonstrated, which presented a stable memory performance over 500 cycles and a large switching resistance ratio, and the current-voltage (I-V) hysteretic loop accompanied by capacitance effect and negative differential resistance state. In order to carry out detailed mechanism analysis, two materials (ITO or Ti) with different work functions as the bottom electrode and Ag as the top electrode were used to prepare two memristive devices. It can be confirmed that the conductive behavior obeys Schottky emission and direct tunneling at low voltage region, while it follows the hopping conduction at high voltage region. In a word, the selected SPS, a sustainable waste material, can be employed to prepare bioelectronic devices, which has a potential application value in green electronic products.

Fixed-time synchronization control of memristive MAM neural networks with mixed delays and application in chaotic secure communication

Abstract In this paper, the fixed-time synchronization control problem of memristive multidirectional associative memory neural networks (MMAMNNs) is considered. Based on the nonlinear and chaos characteristics of memristor, a chaotic model is constructed. And then, utilizing the Lyapunov stability theory, two appropriate controllers are constructed and different activation functions are used. This control method ensures that drive system and response system can achieve synchronization within a fixed time. So, compared with previous studies, it has more practical value. In addition, we present a fixed-time synchronization chaotic encryption method, the chaos characteristic of the model is used to encrypt plaintext, and the decryption of ciphertext is realized based on the synchronization control theories. Finally, several numerical simulations are given to demonstrate the validity of the theories and the chaotic secure communication scheme.

Electronic Devices and Circuits Based on Wafer‐Scale Polycrystalline Monolayer MoS2 by Chemical Vapor Deposition

Abstract2D layered materials such as graphene and transition‐metal dichalcogenides (TMDCs) have emerged as promising candidates for next‐generation nanoelectronic applications due to their atomically thin thicknesses and unique electronic properties. Among TMDCs, molybdenum disulfide (MoS2) has been extensively investigated as a channel material for field‐effect transistor (FET) and circuit realization. However, to date most reported works have been limited to exfoliated MoS2 nanosheets primarily due to the difficulty in synthesizing large‐area and high‐quality MoS2 thin film. A demonstration of wafer‐scale monolayer MoS2 synthesis is reported by chemical vapor deposition (CVD), enabling transistors, memristive memories, and integrated circuits to be realized simultaneously. Specifically, building on top‐gated FETs with a high‐κ gate dielectric (HfO2), Boolean logic circuits including inverters and NAND gates are successfully demonstrated using direct‐coupled FET logic technology, with typical inverters exhibiting a high voltage gain of 16, a large total noise margin of 0.72 VDD at VDD = 3 V, and perfect logic‐level matching. Additionally, resistive switching is demonstrated in a MoS2‐based memristor, indicating that they have great potential for the development of resistive random‐access memory. By virtue of scalable CVD growth capability, the way toward practical and large‐scale electronic applications of MoS2 is indicated.

Directed Assembly of Nanoparticle Threshold‐Selector Arrays

AbstractThe directed assembly of ordered arrays of cubic silver nanoparticles featuring distinct electrical threshold‐switching characteristics is reported. Threshold selectors are key elements for nonvolatile resistive random‐access‐memory architectures, as they suppress sneak path currents in crosspoint arrays. Nanocubes are site‐selectively immobilized on a TiO2‐coated silicon surface via a complementary molecular surface functionalization of nanoparticles and substrate based on a Cu(I)‐catalyzed alkyne‐azide cycloaddition without any physical template. Electrical characterization of individual silver nanocubes by conductive‐probe atomic force microscopy reveals pronounced and reproducible threshold‐switching behavior, featuring ultralow OFF currents below 1 pA, steep turn‐on slopes of <50 mV dec−1 and ON‐OFF ratios in excess of 103. Numerical simulation of Ag‐ion migration dynamics in the TiO2 electrolyte using a kinetic Monte Carlo model supports a switching mechanism based on conductive filament formation from Ag nanoclusters, and their reversible rupture in the low‐voltage regime. Assembled Ag nanocube threshold selectors are proposed for applications in memristive memory architectures, in particular for future highly integrated 3D circuitry.

Optically accessible memristive devices

Abstract One of the most promising contenders for ultralow-energy electronic devices are memristive memories, which allow for sustainably scalable “neuromorphic” computing, potentially capable of reducing power dissipation in IT by >50%. Understanding the nanoscale kinetics of the switching mechanisms is needed to enable high-endurance devices – only this can unlock their integration into fast, low-energy, logic-in-memory architectures. Lately, non-perturbative techniques were introduced to study morphological changes within memristive devices. In particular, plasmonic nanocavities recently became a smart and powerful investigation tool and opened the path for completely new electro-optical applications based on memristive devices. In this review, we will discuss the main research streams currently linking the fields of nanoscale device engineering and plasmon-enhanced light-matter interactions focusing on innovative fast ways to study real-time movement of individual atoms that underpins this new generation of ultralow-energy memory nano-devices.

Analysis of Parasitic Effects in Filamentary-Switching Memristive Memories Using an Approximated Verilog-A Memristor Model

The technology for oxide resistive memories offers nowadays a number of different implementations and solutions. As a consequence, many models have been presented so far, generally technology-specific, representing a problem for the memory design standardization. Moreover, the computational effort can be reduced using memristive models with lower complexity but that grant at the same time good speed and numerical stability. In this paper, the authors try to find a compromise between accuracy and computational costs, proposing a simulation procedure based on a linear approximation of the memristive device model. The description, formally derived from the traditional linear model, has been implemented in Verilog-A and, thanks to the analysis of practical design cases on a reference architecture, has been demonstrated to be useful in highlighting critical parasitic effects related to the interaction of the memristive cells with the memory circuit periphery. Thanks to the approximated method, a computer simulation time saving up to 40% is achieved when simulating a full cross-bar memory device. The model parameters have been extracted from experimental curves obtained from HfO2 devices implemented in a 250-nm BiCMOS IHP technology.

Analysis of Memory Matrices with HfO2 Memristors in a PSpice Environment

The investigation of new memory circuits is very important for the development of future generations’ non-volatile and Random Access Memories (RAM) memories and modern schemes for in-memory calculations. The purpose of the present research is to propose a detailed analysis of passive and hybrid memristor-based memory crossbars with separating metal oxide semiconductor (MOS) transistors. The considered memristors are based on HfO2. The transistors are applied to eliminate the parasitic paths in the schemes. For simulations, a previously proposed strongly nonlinear modified window function by the author together with a physical nonlinear memristor model is used. The considered model is adjusted according to the experimental i–v relationship of HfO2 memristors. The i–v relationship obtained by the simulation is successfully fitted to the respective relationship derived by physical measurements. A good coincidence between these characteristics is established. Several basic window functions are also applied for comparison to the corresponding results. The proposed model is analyzed in Personal Simulation Program with Integrated Circuit Emphasis (PSpice) and it is also used for simulation of a 5 × 5 fragment of a memristor memory crossbar with isolating transistors and for the analysis of a 6 × 6 passive memory matrix. The investigated matrices are simulated for writing, reading, and erasing information. It is established that the model proposed could be used for simulations of complex memristor circuits.

Investigation of memristor effect on basis of thin-film oxide dielectrics modified by carbon

The regularities of the change of electrophysical properties of memristor structures based on porous films of titanium dioxide are considered at their modification by carbon. It is shown that the introduction of impurity results in the significant change of the electrophysical properties of memristor structures based on porous films of titanium dioxide. The purpose of this paper is to reveal the regularities between the electrophysical properties of elements of non-volatile memristor memory and the phenomena of switching and memory at atmospheric pressure.

Understanding the influence of device, circuit and environmental variations on real processing in memristive memory using Memristor Aided Logic

Memristors have gained increasing interest recently as emerging memory technologies. Their unique ability to perform logic operations within the memory makes them even more attractive. MAGIC NOR is one such logic gate that can be integrated within memristive memory cells, thus opening possibilities for real in-memory computing. This paper explores the integration of MAGIC NOR gates within large-scale memory crossbar arrays. We evaluate both analytically and numerically different non-ideality parameters that influence the logic gate performance. First, we investigate the effect of parasitic resistance and capacitance within the memory array. Then, process and device variations are considered and modeled, as well as environmental conditions such as temperature and power supply variations. These non-idealities are formulated in the form of process corners that enable designers to estimate the effect of variations on their design in worst case scenarios, similar to the manner in which such effects are estimated in CMOS-based VLSI design.

Redox gated polymer memristive processing memory unit

Memristors with enormous storage capacity and superior processing efficiency are of critical importance to overcome the Moore’s Law limitation and von Neumann bottleneck problems in the big data and artificial intelligence era. In particular, the integration of multifunctionalities into a single memristor promises an essential strategy of obtaining a high-performance electronic device that satisfies the nowadays increasing demands of data storage and processing. In this contribution, we report a proof-of-concept polymer memristive processing-memory unit that demonstrates programmable information storage and processing capabilities. By introducing redox active moieties of triphenylamine and ferrocene onto the pendants of fluorene skeletons, the conjugated polymer exhibits triple oxidation behavior and interesting memristive switching characteristics. Associated with the unique electrochemical and electrical behavior, the polymer device is capable of executing multilevel memory, decimal arithmetic operations of addition, subtraction, multiplication and division, as well as simple Boolean logic operations.

ANN Circuit Application of Complementary Resistive Switches

Artificial neural networks are successfully used for classification, prediction, estimation, modeling and system control. However, artificial neural networks integrated circuits are expensive and not matured enough. Memristors or memristive systems which show a nonvolatile memory behavior has a high potential for use in artificial neural network circuit applications. Some memristive synapse or memristive neural network applications already exist in literature. The complementary memristor or resistive switch memories have been suggested as an alternative to one-cell memristor memories. Their sensing is more difficult and complex than the others. The complementary memristor memory topologies with a sensing node are also inspected in literature. To the best of our knowledge, a neural network circuit which is based on the complementary resistive switches with a sensing/writing node does not exist in literature yet. In this paper, several neural network circuits which are based on the complementary resistive switches with a sensing/writing node have been designed and examined for the first time in literature. Their analysis are given and simulations are performed to verify their operation. We expect that such a complementary resistive switch implementation may find use in artificial neural networks chips in the future.

Input-to-state stability analysis for memristive BAM neural networks with variable time delays

In this paper, we are concerned with input-to-state stability of a class of memristive bidirectional associative memory (BAM) neural networks with variable time delays. Based on a nonsmooth analysis and set-valued maps, some novel sufficient conditions are obtained for the input-to-state stability of such networks, which extended some known results as particular cases. Finally, a numerical example is presented to illustrate the feasibility and effectiveness of our results.

Organic Memristor Utilizing Copper Phthalocyanine Nanowires with Infrared Response and Cation Regulating Properties

AbstractCurrent organic memristive devices have been suffering from unstable performance, ambiguous mechanism, and poor NIR response, thus restricting their commercial translation. Here, a near‐infrared‐sensitive (NIR) organic memristive device with high stability based on solution‐processed copper phthalocyanine nanowires (N‐CuMe2Pc NWs) is first reported. Compared with uneven thermal evaporated N‐CuMe2Pc film, the N‐CuMe2Pc NWs film possesses a uniform 3D mesh structure, which attribute to the localized cationic migration, robust formation/rupture of conductive filament and subsequent improvement of reproducibility, thermal stability, and retention characteristics. Furthermore, operating voltage and OFF current can be readily regulated by NIR illumination due to strong NIR absorption of the well‐aligned edge‐to‐edge interconnected N‐CuMe2Pc NWs and tunable potential barrier formed between active layer and Ag electrode, which are further verified by absorption spectrum and Kelvin probe force microscope analysis, respectively. This study provides a generalized method for optimizing device performance and attaching phototunable properties of organic memristive memories. In addition, compared with pristine CuPc molecules with low solubility, limitation of thermal evaporation approach that is incompatible with scaling up is expected to overcome by the solution‐processed N‐CuMe2Pc NWs.

Four-Level Forms for Memristive Material Implication Logic

This brief proposes the use of four-level forms in the memristive material implication (M-IMP) logic. M-IMP is a promising approach to perform stateful logic in memristive nonvolatile memories. In such a design technique, a given Boolean function is evaluated as a sequence of instructions, making logic synthesis methods necessary to attain the shortest sequence. In comparison to previous work, experimental results have shown an average reduction of 40% when evaluating the tradeoff between the numbers of instructions and memristive devices.

Emerging resistive random-access memory for 'fog' computing and IoT: materials and structural options taxonomy

The emergence of resistive random-access memory (ReRAM) die and fog computing plus internet-of-things (IoT) has given rise to the need for developing memristive memory elements structure and material conductance mechanisms taxonomy for ReRAM. In this paper, we review those aspects, including nanoparticles (metallic, bimetallic, etc.), graphene and other carbonbased materials and structures and related 2D materials. The corresponding taxonomies are presented in this paper, which can help to find new materials, optimal values of technological parameters, optimise the structure and maximise the efficiency ReRAM for emerging applications.

PH-Modulated memristive behavior based on an edible garlic-constructed bio-electronic device

A new type of memristive memory device with an edible garlic-constructed Ag/garlic/fluorine-doped SnO2(FTO) structure for analog neuromorphic sensor applications was designed.

An Optically Gated Transistor Composed of Amorphous M + Ge2Se3 (M = Cu or Sn) for Accessing and Continuously Programming a Memristor

We demonstrate that a device composed of sputtered amorphous chalcogenide Ge2Se3/M + Ge2Se3 (M = Sn or Cu) alternating layers functions as an optically gated transistor (OGT) and can be used as an access transistor for a memristor memory element. This transistor has only two electrically connected terminals (source and drain), with the gate being optically controlled, thus allowing the transistor to operate only in the presence of light (385–1200 nm). The switching speed of the OGTs is <15 μs. The OGT is demonstrated in series with a Ge2Se3 + W memristor, where we show that by altering the light intensity on the OGT gate, the memristor can be programmed to a continuous range of nonvolatile memory states using the saturation current of the OGT as a programming compliance current. By having a continuous range of nonvolatile states, one memory cell can potentially achieve 2n levels. This high density, combined with optical programmability, enables hybrid electronic/photonic memory.

The stability of memristive multidirectional associative memory neural networks with time-varying delays in the leakage terms via sampled-data control.

In this paper, we propose a new model of memristive multidirectional associative memory neural networks, which concludes the time-varying delays in leakage terms via sampled-data control. We use the input delay method to turn the sampling system into a continuous time-delaying system. Then we analyze the exponential stability and asymptotic stability of the equilibrium points for this model. By constructing a suitable Lyapunov function, using the Lyapunov stability theorem and some inequality techniques, some sufficient criteria for ensuring the stability of equilibrium points are obtained. Finally, numerical examples are given to demonstrate the effectiveness of our results.

Coexistence of filamentary and homogeneous resistive switching with memristive and meminductive memory effects in Al/MnO2/SS thin film metal\u2013insulator\u2013metal device

In the present investigation, we have experimentally demonstrated the coexistence of filamentary and homogeneous resistive switching mechanisms in single Al/MnO2/SS thin film metal–insulator–metal device. The voltage-induced resistive switching leads to clockwise and counter-clockwise resistive switching effects. The present investigations confirm that the coexistence of both RS mechanisms is dependent on input voltage, charge-flux and time. Furthermore, the non-zero I–V crossing locations and crossovers hysteresis loops suggested that the developed device has memristive and meminductive properties. The memristive and meminductive memory effects are further confirmed by electrochemical impedance spectroscopy. The results suggested that the mem-device dynamics and electrochemical kinetics during different voltage sweeps and sweep rates are responsible for the coexistence of filamentary and homogeneous resistive switching mechanisms as well as memristive and meminductive memory effect in single Al/MnO2/SS metal–insulator–metal device. The coexistence of both RS effects is useful for the development of high-performance resistive memory and electronic synapse devices. Furthermore, the coexistence of memristive and meminductive memory effects is important for the development of adaptive and self-resonating devices and circuits.

Not in Name Alone: A Memristive Memory Processing Unit for Real In-Memory Processing

Data movement between processing and memory is the root cause of the limited performance and energy efficiency in modern von Neumann systems. To overcome the data-movement bottleneck, we present the memristive Memory Processing Unit (mMPU)-a real processing-in-memory system in which the computation is done directly in the memory cells, thus eliminating the necessity for data transfer. Furthermore, with its enormous inner parallelism, this system is ideal for data-intensive applications that are based on single instruction, multiple data (SIMD)-providing high throughput and energy-efficiency.