Conductive Filament Growth Research Articles

Effect of electrical stress on time dependent dielectric breakdown (TDDB) tolerate capability of HfO2–ZrO2 ferroelectric films with different thicknesses

HfO2-based ferroelectric materials as the most promising candidate for the ferroelectric memories, have been widely studied for more than a decade due to their excellent ferroelectric properties and CMOS compatibility. In order to realize its industrialization as soon as possible, researchers have been devoted to improving the reliability performance, such as wake up, imprint, limited endurance, et al. Among them, the breakdown characteristic is one of main failure mechanisms of HfO2-based ferroelectric devices, which limits the write/read reliability of the devices. Based on this, we systematically studied the effect of thickness on the time-dependent dielectric breakdown (TDDB) tolerate capability of HfO2–ZrO2 (HZO) FE films under both forward and reverse electrical stress conditions. The thickness of HZO FE film ranged from 6 to 20 nm. Our findings reveal that decreasing the thickness of the HZO FE film leads to an improvement in TDDB tolerance capability which is attributed to the fact that higher density of oxygen vacancies in thinner HZO FE films can effectively inhibit the generation of new oxygen vacancies and the growth of conductive filaments, thus effectively improving the TDDB characteristics. These results provide a potential solution for mitigating breakdown characteristics of HfO2-based ferroelectric devices in memory applications.

Free-standing two-dimensional ferro-ionic memristor

Two-dimensional (2D) ferroelectric materials have emerged as significant platforms for multi-functional three-dimensional (3D) integrated electronic devices. Among 2D ferroelectric materials, ferro-ionic CuInP2S6 has the potential to achieve the versatile advances in neuromorphic computing systems due to its phase tunability and ferro-ionic characteristics. As CuInP2S6 exhibits a ferroelectric phase with insulating properties at room temperature, the external temperature and electrical field should be required to activate the ferro-ionic conduction. Nevertheless, such external conditions inevitably facilitate stochastic ionic conduction, which completely limits the practical applications of 2D ferro-ionic materials. Herein, free-standing 2D ferroelectric heterostructure is mechanically manipulated for nano-confined conductive filaments growth in free-standing 2D ferro-ionic memristor. The ultra-high mechanical bending is selectively facilitated at the free-standing area to spatially activate the ferro-ionic conduction, which allows the deterministic local positioning of Cu+ ion transport. According to the local flexoelectric engineering, 5.76×102-fold increased maximum current is observed within vertical shear strain 720 nN, which is theoretically supported by the 3D flexoelectric simulation. In conclusion, we envision that our universal free-standing platform can provide the extendable geometric solution for ultra-efficient self-powered system and reliable neuromorphic device.

Approaching the Ideal Linearity in Epitaxial Crystalline-Type Memristor by Controlling Filament Growth.

Brain-inspired neuromorphic computing has attracted widespread attention owing to its ability to perform parallel and energy-efficient computation. However, the synaptic weight of amorphous/polycrystalline oxide based memristor usually exhibits large nonlinear behavior with high asymmetry, which aggravates the complexity of peripheral circuit system. Controllable growth of conductive filaments is highly demanded for achieving the highly linear conductance modulation. However, the stochastic behavior of the filament growth in commonly used amorphous/polycrystalline oxide memristor makes it very challenging. Here, the epitaxially grown Hf0.5Zr0.5O2-based memristor with the linearity and symmetry approaching ideal case is reported. A layer of Cu nanoparticles is inserted into epitaxially grown Hf0.5Zr0.5O2 film to form the grain boundaries due to the breaking of the epitaxial growth. By combining with the local electric field enhancement, the growth of filament is confined in the grain boundaries due to the fact that the diffusion of oxygen vacancy in crystalline lattice is more difficult than that in the grain boundaries. Furthermore, the decimal operation and high-accuracy neural network are demonstrated by utilizing the highly linear and multi-level conductance modulation capacity. This method opens an avenue to control the filament growth for the application of resistance random access memory (RRAM) and neuromorphic computing.

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.

Design of Ultra-High Density Archival Storage Memory with Nanoprobe and Patterned Oxygenated Amorphous Carbon with Metal Nanoclusters

Recent prosperity of artificial intelligence is undoubtedly making global data increase at a phenomenal rate. This obviously poses more stringent requirements on current storage devices. Unfortunately, considerable effort is only devoted to the development of on-chip storage device, while off-chip storage technology, particularly for archival storage device, remains slowly progressed. To further innovate the archival storage device, and thus revive its market, we here proposed a novel concept of an archival storage device based on scanning nanoprobe and oxygenated amorphous carbon having metal nanoclusters. A comprehensive numerical model was developed to mimic the write and readout performances of such archival storage device. It was found that the introduction of metal nanoclusters induced much stronger electric field inside the amorphous carbon layer than the case without metal nanoclusters. This beneficially facilitated the growth of conductive filament along metal nanoclusters, and the feasibility of using the proposed device to achieve an areal density of terabit per-square-inch area density, a write energy of picojoule energy per bit, and a switching speed of tens of nanoseconds, was demonstrated.

Elucidating dynamic conductive state changes in amorphous lithium lanthanum titanate for resistive switching devices

Exploration of novel resistive switching materials attracts attention to achieve neuromorphic computing that can surpass the limit of the current Von-Neumann computing for the time of Internet of Things (IoT). Battery materials priorly used to serve as an electrode or electrolyte have demonstrated metal-insulator transitions upon an electrical biasing due to resulting compositional change, which is desirable property for future resistive switching devices. For example, it has been suggested that solid-state electrolyte amorphous lithium lanthanum titanate (a-LLTO) changes in electronic conductivity depending on oxygen content. In this work, switching behavior of a-LLTO was investigated at both bulk- and nano-scale by employing a range of voltage sweep techniques, ultimately establishing a stable and optimal operating condition within the voltage window of − 3.5 V to 3.5 V. This voltage range effectively balances the desirable trait of a substantial resistance change by three orders of magnitude with the imperative avoidance of LLTO decomposition. Experiment and computation with different LLTO composition shows that LLTO has two distinct conductivity states due to Ti reduction. The distribution of these two states is discussed using simplified binary model, implying the conductive filament growth during low resistance state. Consequently, our study deepens understanding of LLTO electronic properties and encourages the interdisciplinary application of battery materials for resistive switching devices.

NDR effect and negative-set/reset phenomenon in core-shell structure-based memristor under the effect of humidity

The potential applications of memristors in the post-Moore era of rapidly developing next-generation artificial intelligence and high-frequency communication technologies are immense. The effects on the resistive switching (RS) characteristics based on Ag Salt@TiO2 memristive device with a nano core-shell structure under different relative humidity (RH) environments have been investigated in this work. Negative-set/reset phenomena occurs in negative voltage region due to excessive growth of conductive filaments (CFs). When the CF returns to normal growth, the current suddenly decreases in the positive high voltage area at lower humidity, which can be explained by the dissolution and growth hindrance of the CFs. Furthermore, the coexistence of negative differential resistance (NDR) and bipolar RS at room temperature can be regulated by adjusting humidity. The current conduction mechanism of the device in both dry and humid environments were fitted using the ohmic conduction mechanism, space charge-limited current (SCLC) conduction mechanism, and Schottky emission mechanism.

Calculation and study for the growth process and electrical characteristics of the conductive filament in nanoscale resistance memory under current-driven mode

After investigating the behavior of ions during the growth of conductive filaments, we suggested a model for the growth process and electrical characteristics of the conductive filament under current-driven mode. In this model, the ionic displacement equation is derived by Arrhenius law, and a differential equation for the conductive filament growth has been established. We have also proved that the dielectric layer with the leakage current under current-driven mode can be equivalent to a parallel plate capacitor, which has a the equivalent dielectric constant. Consequently, the forming/set time of the device is gotten. At the same time, the kinetics process of ion motion is analyzed in detail, so that many microscopic parameters of the ion motion, such as the height of the potential barrier, the jump step, mobility and diffusion coefficient, can be obtained. Due to divalent and monovalent copper ions all participate in conduction, an equivalent copper ion Cuz+ is used for replacing both Cu+ and Cu2+, solving the computational complexity problem caused by multivalent metal ions. Finally, an equivalent circuit is proposed to calculate output voltage versus time characteristic. The calculation results of the model are consistent with experimental data.

Mechanisms of Formation of Current-Conducting Channels in Bipolar Memristors of Various Designs

The paper shows and describes various mechanisms for the formation of a conductive channel in bipolar memristors of the vacancy and ion types: in the first case, due to the nucleation and growth of conductive filaments, and in the second, due to segregation processes with the formation of spatial associations of ions from the active electrode material. The volt-ampere characteristics for memristors of both types are given and a comparison is made of the design features of these memristors

Highly Reliable Textile-Type Memristor by Designing Aligned Nanochannels.

Information-processing devices are the core components of modern electronics. Integrating them into textiles is the indispensable demand for electronic textiles to form close-loop functional systems. Memristors with cross-bar configuration are regarded as promising building blocks to design woven information-processing devices that seamlessly unify with textiles. However, the memristors always suffer from severe temporal and spatial variations due to the random growth of conductive filaments during filamentary switching processes. Here, inspired by the ion nanochannels across synaptic membranes, we report a highly reliable textile-type memristor made of Pt/CuZnS memristive fiber with aligned nanochannels, showing small set voltage variation (<5.6%) under ultralow set voltage (∼0.089V), high on/off ratio (∼106 ) and low power consumption (0.1 nW). Experimental evidences indicate that nanochannels with abundant active S defects could anchor silver ions and confine their migrations to form orderly and efficient conductive filaments. Such memristive performances enable the resultant textile-type memristor array to have high device-to-device uniformity and process complex physiological data like brainwave signals with high recognition accuracy (95%). Our textile-type memristor arrays are mechanically durable to withstand hundreds of bending and sliding deformations, and seamlessly unified with sensing, power-supplying and displaying textiles/fibers to form all-textile integrated electronic systems for new-generation human-machine interactions. This article is protected by copyright. All rights reserved.

Nano t-Se Peninsulas Embedded in Natively Oxidized 2D TiSe2 Enable Uniform and Fast Memristive Switching.

Memristive devices, regardless of their potential applications in memory and computing scenarios, still suffer from large cycle-to-cycle and device-to-device variations due to the stochastic growth of conductive filaments (CFs). In this work, we fabricated a crossbar memristor using the 2D TiSe2 material and then oxidized it into TiO2 in the atmosphere at a moderate temperature. Such a mild oxidation approach fails to evaporate all Se into the air, and after further annealing using thermal or electrical stimulations, the remnant Se atoms gather near the interfaces and grow into nanosized crystals with relatively high conductivity. The resulting peninsula-shaped nanocrystals distort the electric field, forcing CFs to grow on them, which could largely confine the location and length of CFs. As a result, this two-terminal TiSe2/TiO2/TiSe2 device exhibits excellent resistive switching performance with a fairly low threshold voltage (Vset < 0.8 V, Vreset > 0.55 V) and high cycle-to-cycle consistency, enabling resistive switching at narrow operating variations, e.g., 500 ± 48 and 845 ± 39 mV. Our work offers a new approach to minimize the cycle-to-cycle stochasticity of the memristive device, paving the way for its applications in data storage and brain-inspired computing.

The Effects of Ag Nanoislands on the Volatile Threshold-Switching Behaviors of Au/Ag/HfO2/Ag Nanoislands/Au Devices

Volatile threshold-switching (TS) devices have been used as selectors and to simulate neurons in neural networks. It is necessary to find new ways to improve their performance. The randomness of conductive filament (CF) growth and the endurance of the devices are urgent issues at present. Here, we explored embedded Ag nanoislands (NIs) in HfO2-based TS devices to limit the position of the CF and facilitate its growth at the same time. The Au/Ag(2 nm)/HfO2(4 nm)/Ag NIs/Au volatile TS devices exhibited forming-free characteristics with improved endurance compared with the devices without Ag NIs, which was ascribed to the enhanced localization of the electrical field and increased oxygen vacancies in HfO2 induced by the Ag NIs. A mechanism was proposed to explain the volatile TS behaviors of the devices. The Ag NIs and the thickness of the HfO2 layers played key roles in whether the devices required forming. This work shows that the use of metal NIs is an effective and convenient way to improve the performance of TS devices.

Kinetics study of ions in conductive filament growth process of electrochemical metallization resistive memory

&lt;sec&gt;In this work, a system of modified Mott-Gurney differential equations is based on Arrhenius’ law and the overpotential theory of ionic motion in bipolar electrochemical metallization (ECM) resistive devices. The average displacement of ions is solved by the modified Mott-Gurney equation. Then, the relation between the average displacement and the growth length of the conductive filament is obtained by a geometric model based on cells. The equation of applied voltage versus Forming/Set time and the equation of length of conductive filament growth versus time are deduced by using this relation.&lt;/sec&gt;&lt;sec&gt;In this work, an algorithm for extracting kinetic parameters of ions in a bipolar ECM device is also proposed. By using this algorithm, the characteristics of the applied voltage versus Forming/Set time for Ag/&lt;i&gt;γ&lt;/i&gt;-AgI/Pt, Ag/TiO&lt;sub&gt;2&lt;/sub&gt;/Pt, Ag/GeS&lt;sub&gt;2&lt;/sub&gt;/W, and Cu/SiO&lt;sub&gt;2&lt;/sub&gt;/Au devices are calculated and the calculation results are consistent with experimental data. It is found that in the Forming/Set process, the jump step of silver ion is the lattice constant along the &lt;i&gt;c&lt;/i&gt; direction of a unit cell of the crystal for TiO&lt;sub&gt;2&lt;/sub&gt; and the lattice constant of the cubic, &lt;i&gt;a&lt;/i&gt;, for &lt;i&gt;γ&lt;/i&gt;-AgI. These results are explained in the following. In a unit cell of the two crystals there are some tetrahedral and octahedral interstitial sites. The cationic motion path consists of alternating octahedral and tetrahedral sites or some octahedral sites. The cation jumps from tetrahedron to octahedron to tetrahedron, etc. in the &lt;i&gt;γ&lt;/i&gt;-AgI with coplanar polyhedron and from octahedron to octahedron in the TiO&lt;sub&gt;2&lt;/sub&gt; with edge shared octahedron. In GeS&lt;sub&gt;2&lt;/sub&gt; crystal, it is found that the jump step of silver ions is the lattice constant in the &lt;i&gt;c&lt;/i&gt; direction of a unit cell. Owing to the periodicity of the lattice, the pathways of the ion motion in the three materials can be expressed by a periodic potential barrier each. For the jump situation of the copper ion in amorphous SiO&lt;sub&gt;2&lt;/sub&gt;, the jump step of copper ions is calculated to be 1.57 times the length of the O—O bond, and the jump pathway can also be explained by a periodic potential barrier.&lt;/sec&gt;&lt;sec&gt;By introducing the cosine potential barrier, the ionic activation frequency, potential barrier height, ionic mobility and diffusion coefficient, and characteristics of the conductive filament growth versus time in several devices are calculated. The criteria of selecting dielectric materials for bipolar ECM devices are discussed by using these data. It is found that the standards for selecting dielectric materials of bipolar ECM devices are the ion activation energy ≤0.5 eV, preferably between 0.1–0.2eV, and the DC conductivity as close to 10&lt;sup&gt; –4&lt;/sup&gt; Ω&lt;sup&gt;–1&lt;/sup&gt;·cm&lt;sup&gt;–1&lt;/sup&gt; as possible.&lt;/sec&gt;

Memristors based on NdNiO3 nanocrystals film as sensory neurons for neuromorphic computing.

By mimicking the behavior of the human brain, artificial neural systems offer the possibility to further improve computing efficiency and solve the von Neumann bottleneck. In particular, neural systems with perceptual capability expand the application field and lay a good foundation for the construction of perceptual storage and computational systems. However, research on neurons with perceptual functions is still relatively scarce, with most works focusing on optoelectronic synapses. The neuron is important for neuromorphic computing systems because neurons output excitatory or inhibitory stimuli to regulate the weight of synapses. Therefore, the construction of sensory neurons is crucial to expand the application range of brain-like neural computing. Here, an artificial sensory neuron is proposed, which is constructed using a photosensitive bipolar threshold switching memristor based on NdNiO3 (NNO) nanocrystals. These metallic phase nanocrystals can not only enhance the local electric field, but also act as a reservoir for defects (VoS) to guide the growth of conductive filaments and stabilize the performance of the device. They present stable bipolar threshold switching behavior with a low 120 nW set power, and the operating voltages decreased in light due to photocarrier action. A leaky integrate firing (LIF) neuron has been realized, which achieved key biological neuron functions, such as all-or-nothing spiking, threshold-driven firing, refractory period, and spiking frequency modulation. The LIF neurons receiving optical inputs have the properties of an artificial sensory neuron. It could regulate the spiking output frequency at different light densities, which could be used for a ship approaching a port. This work provides a promising hardware implementation towards constructing high-performance artificial intelligence to assist ships at night in a sensory system.

Visible-light irradiation improved resistive switching characteristics of a 2D Cs2Pb(SCN)2I2-Based memristor device

Two-dimensional (2D) perovskite materials show enormous potential in optoelectronic applications owing to their exceptional thermal stability and unique lattice structures. However, research into anion-substituted 2D perovskites is relatively rare, particularly in the photoelectric information storage field. Here, an anion-based 2D perovskite Cs2Pb(SCN)2I2 film with high orientation and high thermal-stability is achieved by simple low-temperature solution processing and the memristor of Al/Cs2Pb(SCN)2I2/FTO is established. The experimental evidence shows that: 1) In the absence of light irradiation, memristors present typical bipolar resistance switching behaviour with On/Off resistance ratio (>103) and reliable retention (>104 s); 2) By introducing light irradiation, it can achieve a more dependable memristor with decreased RS fluctuation and improved cycling endurance. In addition, by modifying the compliance current (Icc), it can realize multi-level storage function of memories with good high temperature endurance. Finally, the logic gate function is also demonstrated with these cells. The operational principles of memristor devices are comprised of the charge trapping and conductive filament mechanisms. The light irradiation reduces the ion migration barrier and enhances the conductivity of perovskite films, thus limiting the excessive growth of conductive filaments. This work offers the groundwork for creating anionic two-dimensional perovskite photoelectric memristor devices.

Calculation and study of microscopic parameters for conductive filament growth in nanoscale resistive memories

In this paper, the differential equations of the conductive filament growth are suggested on the basis of the jump conduction of ions in the dielectric film. We solved these equations by means of the average value method, obtaining the calculative formula of the forming and set time. Then, we proposed an algorithm of getting the jump rate, the jump distance, and the potential barrier. These parameters are linked with the forming and set time. As a result, the model of calculating microscopic parameters for the conductive filament growth is built. Besides calculating microscopic parameters, this model can also be used to compute the electrical parameters of ions and electrical characteristics of the conductive filament in the forming and set processes, such as the mobility of ions and the current in the process of the conductive filament growth. The calculated data of the model are consistent with the experimental results.

HfOx /AlOy Superlattice-Like Memristive Synapse.

The adjustable conductance of a two‐terminal memristor in a crossbar array can facilitate vector‐matrix multiplication in one step, making the memristor a promising synapse for efficiently implementing neuromorphic computing. To achieve controllable and gradual switching of multi‐level conductance, important for neuromorphic computing, a theoretical design of a superlattice‐like (SLL) structure switching layer for the multi‐level memristor is proposed and validated, refining the growth of conductive filaments (CFs) and preventing CFs from the abrupt formation and rupture. Ti/(HfOx/AlOy)SLL/TiN memristors are shown with transmission electron microscopy , X‐ray photoelectron spectroscopy , and ab initio calculation findings corroborate the SLL structure of HfOx/AlOy film. The optimized SLL memristor achieves outstanding conductance modulation performance with linearly synaptic weight update (nonlinear factor α = 1.06), and the convolutional neural network based on the SLL memristive synapse improves the handwritten digit recognition accuracy to 94.95%. Meanwhile, this improved synaptic device has a fast operating speed (30 ns), a long data retention time (≥ 104 s at 85 ℃), scalability, and CMOS process compatibility. Finally, its physical nature is explored and the CF evolution process is characterized using nudged elastic band calculations and the conduction mechanism fitting. In this work, as an example the HfOx/AlOy SLL memristor provides a design viewpoint and optimization strategy for neuromorphic computing.

Ultralow Set Voltage and Enhanced Switching Reliability for Resistive Random-Access Memory Enabled by an Electrodeposited Nanocone Array.

Resistive random-access memory (RRAM) has been extensively investigated for 20 years due to its excellent advantages, including scalability, switching speed, compatibility with the complementary metal oxide semiconductor process, and neuromorphic computing application. However, the issue of memristor reliability for cycle to cycle and device to device resulting from the random ion drift and diffusion in solid-state thin films is still a great challenge for commercialization. Therefore, controlling the internal ionic process to improve the memristor performance and reliability is a primary and urgent task. Here, a Ni nanocone array prepared by an electrodeposition method is integrated with an Ag/Al2O3/Pt resistive switching device. The nanocone-array-based memristor yields superior switching performance, including an ultralow set voltage (-0.37 V), a concentrated voltage/resistance distribution (CV 14.8%/32.7%), robust endurance (>105 cycles), and multilevel storage capability. A finite element analysis, transmission electron microscope observation, and current mapping test indicate that the local enhancement of the electric field confines the ionic migration process and yields a predictable formation and dissolution process of the conductive filament. The nanocone-array-based RRAM device provides a new and feasible method to control the conductive filament growth reliably, which paves the way for memristor development.

Atomic Threshold Switch Based on All‐2D Material Heterostructures with Excellent Control Over Filament Growth and Volatility

AbstractThis report demonstrates that atomic‐level controlled formation/rupture of conductive filaments using all 2D heterostructure of hBN‐graphene is a feasible way to achieve excellent switching characteristics for ideal atomic switches. At a threshold voltage, graphene with stable ion migration routes forms a few atom comprising Ag filaments in hBN, which subsequently spontaneously break as the applied voltage lowers, resulting in optimal threshold switching behavior in an hBN atomic switch. The hBN‐graphene atomic threshold switch maintains volatile threshold switching behavior in a wide range of operating currents (10 nA – 100 µA), has an extremely high on/off ratio &gt; 108, ultralow leakage current &lt; 1 pA and exceptionally rapid switching (≈70 ns). Ionic transport of Ag+ through graphene can avoid the migration of excessive Ag atoms into single layer hBN during operations. As a result, the growth of conductive filaments is stable and protected from atomic defects widening in hBN. The novel findings of this study show that the scaling layer thickness can reach the physical limit of vertical thickness scaling to accommodate the single‐atom volume of silver (≈0.257 nm) when using hBN, and a single‐atom‐thick ionic barrier made of graphene can be used to control switching.

Effect of electrode and oxide properties on the filament kinetics during electroforming in metal-oxide-based memories

We developed a physical model to fundamentally understand the conductive filament (CF) formation and growth behavior in the switching layer during electroforming process in the metal-oxide-based resistive random-access memories (RRAM). The effects of the electrode and oxide layer properties on the CF morphology evolution, current-voltage characteristic, local temperature, and electrical potential distribution have been systematically explored. It is found that choosing active electrodes with lower oxygen vacancy formation energy and oxides with small Lorenz number (ratio of thermal and electrical conductivity) enables CF formation at a smaller electroforming voltage and creates a CF with more homogeneous morphology. This work advances our understanding of the kinetic behaviors of the CF formation and growth during the electroforming process and could potentially guide the oxide and electrode materials selection to realize a more stable and functional RRAM.