Resistive Switching Devices Research Articles

Analog Resistive Switching Devices for Training Deep Neural Networks with the Novel Tiki-Taka Algorithm.

A critical bottleneck for the training of large neural networks (NNs) is communication with off-chip memory. A promising mitigation effort consists of integrating crossbar arrays of analogue memories in the Back-End-Of-Line, to store the NN parameters and efficiently perform the required synaptic operations. The "Tiki-Taka" algorithm was developed to facilitate NN training in the presence of device nonidealities. However, so far, a resistive switching device exhibiting all the fundamental Tiki-Taka requirements, which are many programmable states, a centered symmetry point, and low programming noise, was not yet demonstrated. Here, a complementary metal-oxide semiconductor (CMOS)-compatible resistive random access memory (RRAM), showing more than 30 programmable states with low noise and a symmetry point with only 5% skew from the center, is presented for the first time. These results enable generalization of Tiki-Taka training from small fully connected networks to larger long-/short-term-memory types of NN.

Exploring non-stoichiometric SiOx thin film for non-volatile memory application

This article explores the electrical performance of capacitive memory and resistive switching (RS) devices based on thin films of a single active layer of Silicon oxide (SiOx). The fabricated device Au/SiOx/p-Si displayed frequency-dependent characteristics ranging from 200 kHz to 1 MHz w.r.t capacitance. The charge trapping nature was also investigated, which revealed a charge storage density (N) of order 1010 cm−2 and a low trapping density of interface (Dit) ∼2.65 × 1011 eV−1 cm−2. Furthermore, the device exhibits bipolar RS behavior while maintaining a stable endurance for 1000 DC sweeping cycles and a good retention period of > 103 s. The major pathway of the conduction mechanism in these devices is attributed to the accumulation of oxygen vacancies near the Au/SiOx interface. The conduction in this device is predominantly governed by trap-mediated space-charge-limited current (SCLC) and ohmic conductions.

Fabrication of Sb2S3/Sb2Se3 heterostructure for potential resistive switching applications

The exponential growth of large data and the widespread adoption of the Internet of Things (IoT) have created significant challenges for traditional Von Neumann computers. These challenges include complex hardware, high energy consumption, and slow memory access time. Researchers are investigating novel materials and device architectures to address these issues by reducing energy consumption, improving performance, and enabling compact designs. A new study has successfully engineered a heterostructure that integrates Sb2Se3 and Sb2S3, resulting in improved electrical properties. This has generated significant interest in its potential applications in resistive switching. In this study, we have demonstrated the fabrication of a device based on Sb2S3/Sb2Se3 heterostructure that exhibits resistive switching behavior. The device has different resistance states that can be switched between high and low resistance levels when exposed to an external bias (−1 V to 0 V to 1 V). It also has good non-volatile memory characteristics, including low power consumption, high resistance ratio (∼102), and reliable endurance (∼103). The device enables faster data processing, reduces energy consumption, and streamlines hardware designs, contributing to computing advancements amidst modern challenges. This approach can revolutionize resistive switching devices, leading to more efficient computing solutions for big data processing and IoT technologies.

Inexpensive Fabrication of Sn-Ag- Cu/Cu:ZnO/Al/PET Memristive Devices through Unconventional Synthesis Techniques

In the last few decades there has been rapidly growing research interest in resistive switching devices which led to tremendous technological advancements. In this work, copper (Cu) doped zinc oxide (ZnO) thin film was deposited on Aluminum coated PET conductive sheets having a sheet resistance of 20 Ω. Soldering balls of 2 mm diameter consisting of 96.5% Sn, 3% Ag and 0.5% Cu alloy were dropped into this thin film to form the Sn-Ag- Cu/Cu:ZnO/Al/PET memristive devices. No additional annealing temperature was required as the heat transfer from 350 C hot soldering ball onto the Cu:ZnO thin film was sufficient to anneal the thin film. The electronic characteristics of the device were obtained by employing a function generator and an oscilloscope instead of an expensive source meter. The elimination of redundant hot furnace (for annealing) and source meter (for I-V characterization) resulted in the improvement of total equipment expenses by ~96%.

On the time series analysis of resistive switching devices

On the time series analysis of resistive switching devices

Resistive switching in benzylammonium-based Ruddlesden-Popper layered hybrid perovskites for non-volatile memory and neuromorphic computing.

Artificial synapses based on resistive switching have emerged as a promising avenue for brain-inspired computing. Hybrid metal halide perovskites have provided the opportunity to simplify resistive switching device architectures due to their mixed electronic-ionic conduction, yet the instabilities under operating conditions compromise their reliability. We demonstrate reliable resistive switching and synaptic behaviour in layered benzylammonium (BzA) based halide perovskites of (BzA)2PbX4 composition (X = Br, I), showing a transformation of the resistive switching from digital to analog with the change of the halide anion. While (BzA)2PbI4 devices demonstrate gradual set and reset processes with reduced power consumption, the (BzA)2PbBr4 system features a more abrupt switching behaviour. Moreover, the iodide-based system displays excellent retention and endurance, whereas bromide-based devices achieve a superior on/off ratio. The underlying mechanism is attributed to the migration of halide ions and the formation of halide vacancy conductive filaments. As a result, the corresponding devices emulate synaptic characteristics, demonstrating the potential for neuromorphic computing. Such resistive switching and synaptic behaviour highlight (BzA)2PbX4 perovskites as promising candidates for non-volatile memory and neuromorphic computing.

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.

Two-dimensional α -In2Se3 memory devices from resistive switching to synaptic plasticity

We employ two-dimensional (2D) α-In2Se3 nanosheets and polymethyl methacrylate (PMMA) materials to develop three types of devices with different resistive switching (RS) layer structures and deeply study the electrical properties and physical mechanisms of these devices. It is confirmed that the pure 2D α-In2Se3 nanosheet-based RS device is a mode of ferroelectric regulation of the potential barrier, exhibiting memristor characteristics that can mimic the synaptic plasticity. Meanwhile, PMMA can improve the RS properties of the α-In2Se3 nanosheet-based device, including the appropriate switching ratio, narrow ratio distribution, and good endurance and retention capability, but the device's physical mechanism changes to charge trapping assisted hopping mechanism from the ferroelectric regulation of the potential barrier.

HfO2-Based Switching Devices with Nitridation of the Bottom Electrode

HfO2 -based Resistive Switching devices are a promising candidate for in-memory computing due to their lowpower consumption, good endurance, reliability, and compatibility with CMOS technology [1]. Controlling theoxygen vacancy (Vo) distribution near the top and bottom electrodes by selecting proper metal-dielectric-metalstack materials has impact on the performance of the device [2-3]. Significant improvement in switching poweris achieved when Vo distribution is higher near the top electrode (TE) and lower near the bottom electrode [4].Introducing nitridation treatment to the TiN bottom electrode shows a significant reduction in switching powerand superior conductance quantization with nanosecond pulse width of programing pulsed operation [5].In this work we studied different TiN bottom electrode (BE) films in the TiN/HZO/TiN MIM toinvestigate its impact of BE TiN on the switching characteristics. Fig. 1 shows schematic for the two differentswitching devices with identical top electrodes (10 nm PVD TiN) and same switching dielectric (10 nm HZO) butwith different N2 levels of 30 nm TiN at the BE. Device-B has higher level of N2 compared to device-A. Formingprocess was performed by applying DC voltage sweep with 1nA compliance current. The device-A has the lowestforming power (0.86nW) as shown in Fig. 2(a). An increase in the forming power consumption was observed fordevice-B (2.45nW) as shown in Fig. 2(b). We carried out the carrier transport characterization at the highresistance state (HRS) prior to forming process. Fig. 2(c)&(d) shows the conduction process in both devices. Indevice-A, the current conduction mechanism followed the hopping conduction in the dielectric as shown in Fig.2(c). The hopping conduction is a bulk-limited conduction mechanism depends on the electrical properties of thedielectric itself such as the trap energy level [6]. The conduction mechanism in device-B (high N2) (Fig. 2(d)) andwas dominated by the Schottky conduction in the HZO layer, which is an electrode-limited conduction thatdepends on the electrical properties at the electrode-dielectric interface [6]. When the active nitrogen atoms areintroduced to the BE, it diffuses to the dielectric due to increased concentration, then connect to the hafnium iondangling bonds as their lone-pair electrons, since the bonding energy of the Hf–N bond is very low (535eV)compared with that of the Hf–O bond (801eV) [7]. This allows a migration of Vo towards TE and reducing the Voconcentration near the BE for device-A leading to carrier hopping. On the other hand, Vo concentration near theBE is completely purged because of high nitrogen concentration (device-B) leading to Schottky conduction. Thisexplains the reduction of forming power in device-A. Fig. 3 shows the resistance distribution after applying 30DC sweeps with reading voltage of 0.1V after each sweep. The device-B (high N2) shows the largest windowbetween HRS and LRS compared to the other devices. That further confirms the forming process in these devices.In summary, low level of N2 reduces the forming power while higher level of N2 enhances the resistance windowbetween LRS and HRS because of Vo concentration variation near BE.

Neuroelectronics as neuromorphic and neurohybryd systems enabled by memristive technology

Due to its distinctive capability to replicate vital functions of synapses and neurons, memristive devices and arrays enable both the hardware implementation of neural networks and a significant advancement towards integrating artificial electronic and biological systems to address pressing issues in artificial intelligence (AI), robotics, and medicine. This research area is still nascent and can be viewed as part of the broader field of neuroelectronics. The aforementioned is a fusion of analog and digital solutions used for diverse computational tasks inspired by biology. Notably, analog neuromorphic systems that employ memristive components are distinctive features of this arena and they can significantly enhance throughput and energy efficiency in contrast to existing AI accelerators. Designing neuromorphic systems grounded on this fresh component base mandates coordinated and interdisciplinary research and development. The foundation of this scientific and technological field lies in the cross-cutting technology of memristive devices and circuits. This technology enables the development of a novel brain-like information and computing system infrastructure that can be applied in a diverse range of fields. Current perspectives include the seamless integration of memristive devices and arrays with CMOS circuits, and the co-optimization of materials, devices, and architectures to create prototypes for computing and information systems. These systems replicate computational features present in biological neural networks capable of solving cognitive tasks that are typically either intractable by traditional AI or highly time-consuming. Neuroelectronic solutions can integrate with the brain or living neuronal cultures to form neurohybrid systems. In this presentation, we discuss two distinct strategies for connecting memristive systems with biological neural networks both in vitro and in vivo. These include a perceptron using an array of programmable memristive weights represented by metal-oxide resistive-switching devices and a methodology leveraging memristive stochastic plasticity and neural synchrony, which is part of the brain’s spiking architecture. Finally, the concept of a memristive neurohybrid chip is presented to create a compact, multifunctional, bidirectional interface between biological neural networks and memristive electronics, combined with microelectrode and microfluidic systems on a single chip. The technological advancements in component base and the development of memristor-based neuroelectronic systems will diversify hardware for the continuous evolution and mass application of artificial intelligence technologies. This will enable the creation of hybrid intelligence based on the symbiosis of artificial and biological neural networks and allow for the establishment of novel tasks at an unprecedented level.

Electrophysical properties, memristive and resistive switching of charged domain walls in lithium niobate

Charged domain walls (CDWs) in ferroelectric materials raise both fundamental and practical interest due to their electrophysical properties differing from bulk ones. On a microstructure level, CDWs in ferroelectrics are 2D defects separating regions with different spontaneous polarization vector directions. Screening of electric field of the CDW's bound ionic charges by mobile carriers leads to the formation of elongated narrow channels with an elevated conductivity in initially dielectric materials. Controlling the position and inclination angle of CDW relative to the spontaneous polarization direction, one can change its conductivity over a wide range thus providing good opportunities for developing memory devices, including neuromorphic systems. This review describes the state of art in the formation and application of CDWs in single crystal uniaxial ferroelectric lithium niobate (LiNbO3, LN), as resistive and memristive switching devices. The main CDWs formation methods in single crystal and thin-film LN have been described, and modern data have been presented on the electrophysical properties and electrical conductivity control methods of CDWs. Prospects of CDWs application in resistive and memristive switching memory devices have been discussed.

Doped HfOxNanoclusters: Polar and Resistive Switching in the Smallest Functional Units

In the study presented in this article, the impact of proton doping on the structural and electronic properties of hafnium oxide nanoclusters is investigated, with a focus on their potential for use in resistive and polar switching devices. In the results, it is shown that the incorporation of protons can stabilize the cage‐like crystalline structures of clusters, leading to reversible changes in electronic properties by varying oxygen stoichiometry. However, the full coverage of hafnia atoms by hydrogen removes in‐gap states, highlighting the importance of controlled moisture content in redox‐based memristive devices and neuromorphic units. In addition, in this study, the polar properties of these clusters are explored, illustrating possible polar switching in metastable pure , low‐barrier antiferroelectric‐like switching in carbon‐stabilized , and low‐barrier polar switching in . In these findings, the potential of clusters is revealed as active components for next‐generation high‐capacity nonvolatile electronic memory and beyond von Neumann computing in sub‐nanometer scale.

Electrophysical properties, memristive and resistive switching in charged domain walls in lithium niobate

Charged domain walls (CDW) in ferroelectric materials are interesting from fundamental and applied points of view, since they have electrical properties different from bulk ones. At the microstructural level, CDW in ferroelectrics are two-dimensional defects that separate regions of the material with different directions of spontaneous polarization vectors. Compensation of the electric field of the bound ionic charge of the CDW by mobile carriers leads to the formation of extended narrow channels with increased conductivity in the original dielectric material. By controlling the position and angle of inclination of the CDW relative to the direction of spontaneous polarization, it is possible to change its conductivity in a wide range, which opens up broad prospects for creating memory devices, including for neuromorphic systems. The review presents the current state of research in the field of formation and application of CDW formed in single crystals of uniaxial ferroelectric lithium niobate (LiNbO3, LN) as resistive and memristive switching devices. The main methods for forming CDW in single crystals and thin films of LN are considered, and modern data on the electrophysical properties and methods for controlling the electrical conductivity of CDW are presented. The prospects for using CDW in memory devices with resistive and memristive switching are discussed.

Performance Analysis and Read Voltage Optimization of E-Beam Evaporated Amorphous SnO2-Based Cross-Cell Resistive Switching Device

Performance Analysis and Read Voltage Optimization of E-Beam Evaporated Amorphous SnO₂-Based Cross-Cell Resistive Switching Device

Self‐assembled vapor-transport-deposited SnS nanoflake-based memory devices with synaptic learning properties

The most salient features of resistive switching (RS) devices are low energy consumption, fast switching speed, and high-density integration, which render them promising candidates for realizing non-volatile memory and artificial synaptic devices. However, the growth of functional switching layers for RS devices needs innovative deposition techniques. Herein, we utilize a high-throughput vapor-transport-deposition (VTD) technique for synthesizing self-assembled tin-sulfide (SnS) nanoflakes, which are then used as a switching layer to fabricate an RS device. First principle calculations are conducted to understand the optoelectronic properties of SnS by employing density functional theory. The proposed Ag/SnS/Pt memory device exhibits substantial merits, including low-switching voltages (VSET: 0.22 V and VRESET: −0.20 V), suitable ON/OFF ratio (∼259), excellent endurance (106), and extended memory retention (106 s) characteristics. In addition, RS stochasticity is modeled using statistical time-series analysis via Holt’s exponential smoothing. Interestingly, the device can emulate multiple synaptic functionalities, including potentiation, depression, paired-pulse facilitation, paired-pulse depression, excitatory postsynaptic current, inhibitory postsynaptic current, and advanced spike-timing dependent plasticity rules. Moreover, the proposed synaptic device can detect the edge of images by utilizing a convolutional neural network. The unique and efficient VTD-SnS-based device will be a potential candidate for high-density non-volatile memory and neuromorphic computing applications.

Eightwise Switching Mechanism in Memristive SrTiO3Devices and Its Implications on the Device Performance

Filamentary‐type resistive switching devices based on the valence change mechanism (VCM) have been studied extensively during the past decades, due to their great performance as nonvolatile memories and their promising nature for novel computing architectures. For many materials exhibiting the VCM, two different polarities can be observed, namely, counter‐eightwise and eightwise switching. The more technologically relevant materials, such as TaOxand HfOx, usually exhibit the counter‐eightwise resistive switching mode, however, the nature of its abrupt switching limits the potential for their implementation in more analog systems. On the contrary, the eightwise resistive switching mode exhibits a more gradual switching profile, which makes it a more suitable candidate for neuromorphic and in‐memory computing applications. Contrary to its counterpart, the eightwise switching mode has not been fully understood for several years, hampering the improvement of memristive devices based on this mode. This review presents the major advancements that have been made to understand the mechanism behind the eightwise switching mode and its implications on the properties of the memristive devices. The works presented here are based on the model system of SrTiO3, however, the obtained knowledge and the strategies to tailor their properties can be transferred to other technologically relevant systems.

Dual‐Mode Operation of Epitaxial Hf0.5Zr0.5O2: Ferroelectric and Filamentary‐Type Resistive Switching

Since the discovery of its ferroelectricity, hafnium oxide is widely used for applications in ferroelectric field‐effect transistors and ferroelectric tunnel junctions. is especially favored for its robust ferroelectricity and high remanent polarization at low thicknesses. In addition, is well established as amorphous or crystalline oxide layer in resistive switching devices. Herein, ferroelectric switching is found coexisting with high on/off ratio resistive switching in sub‐10 nm epitaxial . The resistive switching shows typical characteristics of a filamentary‐type valence change memory (VCM), clearly contradicting the polarization charges as the origin of different resistance states. In contrast to previous observations, no electroforming step is required to initiate VCM switching. The bottom electrode enables a RESET to the virgin state, allowing subsequent ferroelectric hysteresis measurements. It is possible to change between both switching schemes repeatedly without impacting the ferroelectric performance. This indicates that ferroelectric switching and oxygen vacancy movement do not interfere with each other, and both switching phenomena can exist independently. This finding opens up ways to unite the different strengths of both switching mechanisms in the same stack. It becomes possible to assign the two operating principles to artificial neural network training and inference according to their respective advantages.

Bipolar and rectifying resistive switching dynamics in E-beam evaporated SnOx based memristor

In this article, we have examined the crystallinity and semiconducting properties (n-type and/or p-type) of e-beam evaporated Tin-oxide (SnOx) with different deposition substrate temperature and study their impact over resistive switching dynamics with Silver (Ag) active and Platinum (Pt) inert metal electrode. The fabricated Resistive switching (RS) devices have performed forming free bipolar and rectifying resistive switching with n-type and p-type semiconducting properties of deposited insulating layer, respectively. The crystal structure and elemental composition of deposited insulating layers (SnOx) have been characterized by using Glancing Angel X-Ray Diffraction (GAXRD) and Energy Dispersive X-Ray (EDX). The electrical responses of fabricated RS devices have been observed by using Keithley-4200 parametric analyser with customize probe station and performance of the bipolar and rectifying RS devices have been analysed with low sweeping voltage (−1.5V/1.5V) along with 20 K pulsative endurance at RT and 105 s retention at 85 °C. We have also described the diffusivity of Silver (Ag) active metal electrode into deposited insulating layers and physics behind BRS and RRS dynamics in fabricated device.

Uniform multilevel switching and synaptic properties in RF-sputtered InGaZnO-based memristor treated with oxygen plasma.

Bipolar gradual resistive switching was investigated in ITO/InGaZnO/ITO resistive switching devices. Controlled intrinsic oxygen vacancy formation inside the switching layer enabled the establishment of a stable multilevel memory state, allowing for RESET voltage control and non-degradable data endurance. The ITO/InGaZnO interface governs the migration of oxygen ions and redox reactions within the switching layer. Voltage-stress-induced electron trapping and oxygen vacancy formation were observed before conductive filament electroforming. This device mimicked biological synapses, demonstrating short- and long-term potentiation and depression through electrical pulse sequences. Modulation of post-synaptic currents and pulse frequency-dependent short-term potentiation were successfully emulated in the InGaZnO-based artificial synapse. The ITO/InGaZnO/ITO memristor exhibited spike-amplitude-dependent plasticity, spike-rate-dependent plasticity, and potentiation-depression synaptic learning with low energy consumption, making it a promising candidate for large-scale integration.

Effects of rubidium substitution of Cs2−xRbxAgBiBr6 double halide perovskites on resistive switching characteristics for memory applications

Cation substitution technique in halide perovskites (HPs) is one of the famous schemes to enhance the characteristics of HPs-based electronic and optoelectronic devices. Here, we fabricated rubidium (Rb) substituted inorganic double halide perovskites (HPs) Cs2−xRbxAgBiBr6 (x = 0, 0.05, 0.1, 0.2, and 0.3) film-based resistive switching (RS) devices and investigated effects of Rb cation substitution on characteristics of RS devices. Grain sizes of the formed Cs2−xRbxAgBiBr6 films gradually increased as increase of Rb contents in the precursor. All of the fabricated RS devices demonstrated non-volatile bipolar RS behavior, device with the Rb content x = 0.1 showed a particularly high on/off ratio (9.29 × 102) of about 30 times greater than pristine Cs2AgBiBr6-based ones (3.09 × 10). In addition, it has been shown that an appropriate amount of Rb substitution at the level of x = 0.1 can effectively prevent the appearance of other crystalline phases at high humidity condition of > 80 %. Through various analytical techniques including SEM, XPS, and SCLC measurement, it was confirmed that an enlargement in grain size resulting in a decrease in defects such as Br vacancies in the fabricated film can lead to an increase in resistance at a high resistance state (HRS) and high on/off resistance ratio. This study provides a facile and feasible way to enhance performances of HPs-based RS devices for practical electronic memory applications.