Conductive Filament Research Articles

The filaments control for tunning digital resistive switching in data storage application and analog behavior as an artificial synapse with CsPbBr3-based memristor

Implementation of tunable digital and analog resistive switching (RS) behaviors for memristors is crucial toward their development in data storage and energy-efficient computations. Herein, the CsPbBr3 film-based RS memristors with different switching film thickness and adaptable electrodes are constructed, which are implemented by the solution processed method. All the constructed memristors demonstrate stable bipolar switching behaviors, and in special, the gradual analog RS behavior with multi-level conductance is observed for the thin memristor, making it as the promising artificial synapse. As a comparison, the thick memristor demonstrates digital abrupt RS behavior, accompanying with a high memory window (>103), which can be applied in data storage field. Furthermore, the evolution of conductive filaments, stemming from synergetic bromine vacancies and aluminum atoms, is proposed to clarify the distinguished dynamic changes in the RS process. This work provides an optimization strategy to tune RS behavior for CsPbBr3-based RS memristors and paves the way for both data storage and artificial synapse applications.

Low Energy Consumption GeTe Phase-Change Radio Frequency Switch With Direct Heating of Conductive Filament

Low Energy Consumption GeTe Phase-Change Radio Frequency Switch With Direct Heating of Conductive Filament

Effect of Film Density on MgSiO3-Based Resistive Random-Access Memory

Different film density MgSiO3 based resistive random-access memorys (RRAMs) are fabricated to investigate the resistive switching behaviors. The X-ray diffraction 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 MgSiO3 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 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 Cu/MgSiO3/Pt RRAM have the potential for nonvolatile memristors and information security applications.

Carbon quantum dots boosted resistive switching and magnetic properties in Co3O4-based memory devices

Carbon quantum dots (CQDs) could create opportunities of modulating resistive switching behaviors due to their unique electrical performance. Here, CQDs are introduced to enhance switching uniformity and magnetic properties in Co3O4 thin film memory devices. Compared with the pure Co3O4-based device, the device with CQDs exhibited better performance, such as a reduced initialization voltage, uniform distribution of Set and Reset voltages, stable endurance behavior, and enhanced magnetization performance. The fitting results of current-voltage curves showed that the low-resistance states and high-resistance states of the devices obey Ohmic conduction and Schottky emission, respectively. The improvement in resistive switching properties is ascribed to the formation and rupture of confined conductive filaments due to that CQDs enhanced the local electric field, which can efficiently guide the filament growth and suppress the randomness of filament growth. Magnetization modulation associated with resistive switching involves in the variation of oxygen vacancies concentration and the conversion between Co2+ and Co3+. The present study exhibits an effective path to enhance resistive switching and magnetic properties, which shows promising application to design multifunctional electro-magnetic integrated devices.

Investigation of Resistive Switching of Insulating Hafnium Nitride for Nonvolatile Memory Applications

In this study, nitrogen-rich Hafnium Nitride (HfN) featuring insulating properties was investigated for achieving resistive switching, crucial for the functionality of resistive random-access memory (ReRAM) devices. Devices were fabricated with a 15-nm HfN resistive switching layer using a Radio Frequency (RF) sputtering system. The fabricated devices successfully exhibited a bipolar switching characteristic with a high On/Off ratio (up to 104). An interesting 2-step behavior was also observed during the formation of the conduction filament which was suspected to be tied to the migration of the nitrogen ions. This is the first attempt at using HfN as the resistive switching material for nonvolatile memory applications.

Realization of Selector‐Memory Bi‐Functionality with Self‐Current Regulation Utilizing Poly‐Crystalline Based GST Electrolyte for Memristor Hardware Development

AbstractConductive bridge random‐access memory (CBRAM) are two terminal devices that offer excellent switching performance. In addition, CBRAM shows various switching modes, including volatile threshold switching (TS) and nonvolatile threshold switching (N‐TS). These properties expand its applications to memory, selector, biological synapses, and neurons. However, due to the uncontrollable behavior of stochastic switching between TS and N‐TS in CBRAM devices, a novel approach is needed to improve the switching performance of CBRAM. Moreover, conventional devices that have different stacking between TS and N‐TS increase fabrication cost and worsen the device yield. Here, the selector‐memory bi‐functionality with self‐current regulation effect of Ag‐inserted Ge2Sb2Te5 (GST) thin films is demonstrated. Selector‐memory bi‐functionality, having TS behavior with an adjustable on/off current, with confined conductive filaments (CFs) improves the uniformity and reduces the fabrication cost by implementing TS/N‐TS in a single stack. From the material analysis, it becomes evident that confined Ag‐based CFs within GST films are key factors for realizing selector‐memory bi‐functionality. The selector‐memory bi‐functionality is achieved through the reaction of Ag metal cations with non‐bonded Te atoms in GST film depending on field polarity. These results suggest that the Ag‐inserted GST film contributes to the development of large‐scale nonvolatile memory and neuromorphic application.

Logic Gate Circuits Based on CeOx/WOy Memristor for the Odd/Even Checker and Encryption/Decryption of Image Applications

AbstractDue to its powerful brain‐like parallel computing and efficient data processing capabilities, memristors are considered to be the core components for building the next generation of artificial intelligence systems. In this study, the CeOx/WOy heterojunction is employed as the functional layer, and various metal materials are utilized as the top electrode to fabricate the memristor. The results indicate that the memristive performance of the Ag/CeOx/WOy/ITO device can be improved by using Ag as the top electrode. By studying the conductivity mechanism of the device, a conductivity model is established that regulates oxygen vacancies and Ag conductive filaments. Furthermore, using the as‐prepared memristor, it is constructed four basic digital logic circuits: OR, AND, XOR, and XNOR, as well as a half adder and a full adder that can be used for digital arithmetic operations. Specifically, an odd/even checker is developed based on XOR and XNOR logic circuits to verify the correctness of data transmission. Finally, it is also designed and implemented a cryptographic array based on a memristor, which can be applied to encrypt and decrypt a series of numbers and images. Therefore, this work extends the application of memristor toward digital circuits, information transmission, data processing and image security encryption.

Performance analysis and prediction of tunable metasurface filter based on electrochemical metallization

In this paper, a tunable metasurface filter based on electrochemical metallization is proposed. The finite element method is used to simulate the formation and rupture of the conductive filament (CF). The geometric structure of the metasurfaces filter is reconstructed by CF to achieve the purpose of tuning the transmission characteristics of the metasurface. Due to the formation of CF in the gap of separated rectangular gold patches, the proposed metasurface simultaneously exhibits the resonance characteristics of two separated rectangular gold patches and unseparated rectangular gold patches. Numerical calculations show that when the radius of the CF increases from 5 nm to 25 nm, the metasurface shows good tunable filtering characteristics, and its quality factor gradually increases. Finally, in order to solve the problem of consuming a lot of time to design metasurface, a deep neural network is used to predict the transmission curves corresponding to different metasurface structures. The results show that the mean square error of the training model is less than 1 × 10−3, which shows superior robustness and generalization, and greatly shortens the time required for design. This design paves a new way to develop optoelectronic devices, such as modulators, sensors and optical switches.

Reliable Memristive Switching Empowered by Ag/NiO/W ReRAM Configuration for Multi‐Level Non‐Volatile Memory Applications

AbstractResistive random‐access memories (ReRAM) are promising candidates for next‐generation non‐volatile memory, logic components, and bioinspired neuromorphic computing applications. The analog resistive switching (RS) tuning with a sizable memory window is crucial for realizing multi‐level storage devices. This work demonstrates the multi‐level storage capability of fabricated Ag/NiO/W ReRAM architecture, controlled through voltage modulations. The fabricated ReRAM structures exhibit stable bipolar analog RS, non‐overlapping resistance, and endurance of ≈104 cycles, respectively, with marginal statistical variations/fluctuations. Also, the fabricated ReRAM offers highly controlled and stable retention characteristics tested up to ≈104 s with significantly controlled statistical variations/fluctuations. Adjacent thereto, it offers a substantially lower operating SET and RESET voltage of 1 and −1 V, respectively. Moreover, the non‐overlapping multiple resistive states are observed with the voltage pulse modulation schemes. Furthermore, the current switching mechanism is described using a model proposed for the conductive filament growth and the contribution of the NiO/W interface layer (IL) toward notable RS of fabricated Ag/NiO/W structures.

Multi-walled carbon nanotubes/carbon black/rPLA for high-performance conductive additive manufacturing filament and the simultaneous detection of acetaminophen and phenylephrine

The combination of multi-walled carbon nanotubes (MWCNT) and carbon black (CB) is presented to produce a high-performance electrically conductive recycled additive manufacturing filament. The filament and subsequent additively manufactured electrodes were characterised by TGA, XPS, Raman, and SEM and showed excellent low-temperature flexibility. The MWCNT/CB filament exhibited an improved electrochemical performance compared to an identical in-house produced bespoke filament using only CB. A heterogeneous electrochemical rate constant, kobs0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${k}_{obs}^0$$\\end{document} of 1.71 (± 0.19) × 10−3 cm s−1 was obtained, showing an almost six times improvement over the commonly used commercial conductive CB/PLA. The filament was successfully tested for the simultaneous determination of acetaminophen and phenylephrine, producing linear ranges of 5–60 and 5–200 μM, sensitivities of 0.05 μA μM−1 and 0.14 μA μM−1, and limits of detection of 0.04 μM and 0.38 μM, respectively. A print-at-home device is presented where a removable lid comprised of rPLA can be placed onto a drinking vessel and the working, counter, and reference components made from our bespoke MWCNT/CB filament. The print-at-home device was successfully used to determine both compounds within real pharmaceutical products, with recoveries between 87 and 120% over a range of three real samples. This work paves the way for fabricating new highly conductive filaments using a combination of carbon materials with different morphologies and physicochemical properties and their application to produce additively manufactured electrodes with greatly improved electrochemical performance.Graphical abstract

Highly Reliable Performance of Flexible Synaptic Devices Based on PVP-GO QD Nanocomposites Due to the Formation of Directional Filaments.

The metallic conductive filament (CF) model, which serves as an important conduction mechanism for realizing synaptic functions in electronic devices, has gained recognition and is the subject of extensive research. However, the formation of CFs within the active layer is plagued by issues such as uncontrolled and random growth, which severely impacts the stability of the devices. Therefore, controlling the growth of CFs and improving the performance of the devices have become the focus of that research. Herein, a synaptic device based on polyvinylpyrrolidone (PVP)/graphene oxide quantum dot (GO QD) nanocomposites is proposed. Doping GO QDs in the PVP provides a large number of active centers for the reduction of silver ions, which allows, to a certain extent, the growth of CFs to be controlled. Because of this, the proposed device can simulate a variety of synaptic functions, including the transition from long-term potentiation to long-term depression, paired-pulse facilitation, post-tetanic potentiation, transition from short-term memory to long-term memory, and the behavior of the "learning experience". Furthermore, after being bent repeatedly, the devices were still able to simulate multiple synaptic functions accurately. Finally, the devices achieved a high recognition accuracy rate of 89.39% in the learning and inference tests, producing clear digit classification results.

Boron-Doped Engineering for Carbon Quantum Dots-Based Memristors with Controllable Memristance Stability.

Carbon quantum dots-based memristors (CQDMs) have emerged as a rising star in data storage and computing. The key constraint to their commercialization is memristance variability, which mainly arises from the disordered conductive paths. Doping methodology can optimize electron and ion transport to help construct a stable conductive mode. Herein, based on boron (B)-doped engineering strategy, three kinds of comparable quantum dots are synthesized, including carbon quantum dots (CQDs), a series of boron-doped CQDs (BCQDs) with different B contents, and boron quantum dots. The corresponding device performances highlight the superiority of BCQDs-based memristors, exhibiting a ternary flash-type memory behavior with longer retention time and more controllable memristance stability. The comprehensive analysis results, including device performance, functional layer morphology, and material simulated calculation, illustrate that the doped B elements can directionally guide the migration of aluminum ions by enhancing the capture of free electrons, resulting in ordered conductive filaments and stable ternary memory behavior. Finally, the conceptual applications of logic display and logic gate are discussed, indicating a bright prospect for BCQDs-based memristors. This work proves that modest B doping can optimize memristance property, establishing a theoretical foundation and template scheme for developing effective and stable CQDMs.

Optoelectronic Properties of Cold Plasma-Deposited, Oxidized Sn-C Thin Films.

We report on investigating the structural and electronic properties of semiconducting and insulating layers produced in a process resembling percolation in a unique cold plasma fabrication method (plasma-enhanced chemical vapor deposition-PECVD). Amorphous carbon-tin films (Sn-C) produced from tetramethyl tin (TMT) with an acoustic-frequency glow discharge in a three-electrode reactor were investigated. The layers, after air exposure, oxidized to SnO2/Sn-C. Depending on the coupling capacitance applied to the plasma reactor, the films could be obtained in the form of an amorphous semiconductor or an amorphous insulator. We assume that the semiconductor consists of an internal network of channels auto-organized during deposition. The insulator does not demonstrate any internal structure features. An investigation on conductive filaments creating low-dimensional (LD) nanojunctions in the semiconductor and the location of energetic levels in the insulator was performed. The main parameters of the electronic band structure of the insulating film, such as the transport gap EG (5.2 eV), optical gap Eopt (3.1 eV), electron affinity Χ (2.1 eV), and ionization potential J (7.3 eV), were determined. We have demonstrated a simple approach for developing a catalyst candidate consisting of amorphous semiconductor-insulator nanojunctions for (photo)catalytic hydrogen evolution or CO2 reduction.

Effect of Ni-doped on switching mechanisms and characteristics of ZnO-based memristor: Experimental and first-principles investigations

In this paper, we explore the impact of Ni doping on the resistive switching (RS) performance of ZnO-based resistive random access memory (RRAM). The Ti/ZnO: Ni/ITO resistive memory exhibits a reduced and less discrete forming voltage (Vforming) and set voltage (Vset), along with a more stable high resistance state (HRS). The doping does not change the conductivity mechanism of the device. The observed outcomes can be attributed to the influence of Ni doping on the generation and breakage of the oxygen vacancy conductive filaments (CF) in the vicinity. Using First-Principles calculations, we calculated the formation energy of oxygen vacancies (Vos), the band structure, the density of states (DOS), charge density, and electronic properties of the doped ZnO cell. The oxygen vacancy formation energy (Efv) is significantly lower in the Ni-doped ZnO cell, which is associated with lower Vforming and Vset. And it allows for less randomness in the generation of CF, which improves the stability of the HRS. The band structure shows that Ni doping can add an additional band at the Fermi energy level of ZnO, corresponding to the defect states in the density of states. The improved storage capacity of Ni-doped ZnO devices has been experimentally demonstrated.

Realistic Chest X‐Ray Image Synthesis via Generative Network with Stochastic Memristor Array for Machine Learning‐Based Medical Diagnosis

AbstractArtificial Intelligence (AI) technology has attracted tremendous interest in the medical community, from image analysis to lesion diagnosis. However, progress in medical AI is hampered by a lack of available medical image datasets and labor‐intensive labeling processes. Here, it is demonstrated that a large number of annotated, realistic chest X‐ray images can be generated using a state‐of‐the‐art generative adversarial network (GAN) that exploits noise produced by stochastic in‐memory computing of memristor crossbar arrays. Memristors based on polymer film with high thermal resistance can increase the stochasticity of the tunneling distance for randomly ruptured conductive filaments via excessive Joule heating, thus generating true random numbers required for creating naturally diverse images in GAN. Using StyleGAN2‐adaptive discriminator augmentation (ADA), high‐quality chest X‐ray images with and without pneumothorax are successfully augmented while maintaining a good Frechet inception distance score. The results provide a cost‐effective solution for preparing privacy‐sensitive medical images and labeling to develop innovative medical AI algorithms.

Study of resistive switching behavior in HfO2 nanocrystals synthesized via a low temperature hydrothermal method

The resistive switching property in HfO2 have attracted increasing interest in recent years. In this work, amorphous HfO2 nanocrystals 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 HfO2 samples 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.

Study of a charge transition-driven resistive switching mechanism in TiO2-based random access memory via density functional theory.

The nature of the conducting filament (CF) with a high concentration of oxygen vacancies (VOs) in oxide thin film-based resistive random access memory (RRAM) remains unclear. The VOs in the CF have been assumed to be positively charged (VO2+) to explain the field-driven switching of RRAM, but VO2+ clusters in high concentration encounter Coulomb repulsion, rendering the CF unstable. Therefore, this study examined the oxidation state of VOs in the CF and their effects on the switching behavior via density functional theory calculations using a Pt/TiO2/Ti model system. It was concluded that the VOs in the CF are in a low oxidation state but are transformed to VO2+ immediately after release from the CF. In addition, the short-range interactions between VOs were confirmed to facilitate the rupture and rejuvenation of the CF by reducing the required activation energy. Finally, an improved switching model was proposed by considering the charge transition of VOs, providing a plausible explanation for the reported coexistence of two opposite bipolar switching polarities: the eight-wise and the counter-eight-wise polarities.

A carbon conductive filament-induced robust resistance switching behavior for brain-inspired computing.

Memristors have revolutionized the path forward for brain-inspired computing. However, the instability of the nucleation process of conductive filaments based on active metal electrodes leads to the discrete distribution of switching parameters, which hinders the realization of high-performance and low-power devices for neuromorphic computing. In response, a carbon conductive filament-induced robust memristor is demonstrated with variation coefficients as low as 3.9%/-1.18%, a threshold power as low as 10-9 W, and 3 × 106 s retention and 107 cycle endurance behaviors can be maintained. The recognition accuracy for Modified National Institute of Standards and Technology (MNIST) handwriting is as high as 96.87%, attributed to the high linearity of the iterative updating of synaptic weights. The demodulation and storage functions of the American Standard Code for Information Interchange (ASCII) are demonstrated by programmable pulse modulation. Notably, the transmission electron microscopy (TEM) images allow the observation of carbon conductive filament paths formed in the low resistance state. First-principles calculations analyze the energetics of defects involved in the diffusion of carbon atoms into MoTe2 films. This work presents a novel guideline for studying memristor-based neuromorphic computing.

Kinetic Monte Carlo simulation analysis of the conductance drift in Multilevel HfO2-based RRAM devices.

The drift characteristics of valence change memory (VCM) devices have been analyzed through both experimental analysis and 3D kinetic Monte Carlo (kMC) simulations. By simulating six distinct low-resistance states (LRS) over a 24-hour period at room temperature, we aim to assess the device temporal stability and retention. Our results demonstrate the feasibility of multi-level operation and reveal insights into the conductive filament (CF) dynamics. The cumulative distribution functions (CDFs) of read-out currents measured at different time intervals provide a comprehensive view of the device performance for the different conductance levels. These findings not only enhance the understanding of VCM device switching behaviour but also allow the development of strategies for improving retention, thereby advancing the development of reliable nonvolatile resistive switching memory technologies.

Direct visualization and 3D reconstruction of conductive filaments in aSiO2 material-based memristive device.

Observation of conductive filaments has greatly aided the development of theoretical models of memristive devices. In this work, we visualized and reconstructed the conductive filaments in a Cu/Cu-doped SiO2/W device employing a focused ion beam (FIB) as a milling technique. The SEM images taken from the device after 150 DC sweep cycles showed that Joule heat played a vital role in determining the morphology of a conductive filament, where the vaporization of the conductive filament resulted in the creation of defects, including particles, voids, and cavities. The competition between the formation and vaporization of conductive filaments generally induces a remarkable current fluctuation. Since Cu-doped SiO2 was utilized as the electrolyte, the vapors exfoliated adjacent single layers. FIB milling proceeded in top-down and front-back modes; thus, a 3D model of conductive filaments and defects was constructed according to a series of FIB-SEM images. This methodology is promising for a future failure analysis of memristive devices.