Resistive Random Access Memory Devices Research Articles

Stable and repeatable ZrO2 RRAM achieved by NiO barrier layer for negative set phenomenon elimination

Resistive random-access memory (RRAM) is a promising non-volatile memory technology due to its fast operation, low power consumption, and high reliability. However, the negative set phenomenon remains a challenge for RRAM, which can lead to the deterioration of device switching parameters. In this study, we successfully addressed this issue by inserting a NiO blocking layer between the ZrO2 and Ag top electrodes in ZrO2-based RRAM. In addition, the resistive switching characteristics of the device are significantly enhanced by the incorporation of a p-type oxide NiO layer. Compared to single-layer ZrO2 devices, the double-layer Ag/NiO/ZrO2/ITO RRAM exhibits improved cycling durability (>500 cycles) and good retention time (3 × 104s). Our analysis of the device conduction mechanism and proposed resistive switching model suggest that oxygen vacancies play a connecting role in the reset process, leading to failed reset behavior. Through the incorporation of a p-type semiconductor NiO layer into ZrO2-based RRAMs, the interference of oxygen vacancies on the reset process can be effectively impeded. This approach not only provides an effective resolution to the unforeseen negative set phenomenon in RRAM devices, but it also holds paramount significance for the advancement of high-performance RRAMs.

Realization of Multiple Synapse Plasticity by Coexistence of Volatile and Nonvolatile Characteristics of Interface Type Memristor.

Studies on neuromorphic computing systems are becoming increasingly important in the big-data-processing era as these systems are capable of energy-efficient parallel data processing and can overcome the present limitations owing to the von Neumann bottleneck. The Pt/WOx/ITO resistive random-access memory device can be used to implement versatile synapse functions because it possesses both volatile and nonvolatile characteristics. The gradual increase and decrease in the current of the Pt/WOx/ITO device with its uniform resistance state for endurance and retention enables additional synaptic applications that can be controlled using electric pulses. If the volatile and nonvolatile device properties are set through rehearsal and forgetting processes, the device can emulate various synaptic behaviors, such as potentiation and depression, paired-pulse facilitation, post-tetanic potentiation, image training, Hebbian learning rules, excitatory postsynaptic current, and Pavlov's test. Furthermore, reservoir computing can be implemented for applications such as pattern generation and recognition. This emphasizes the various applications of future neuromorphic devices, demonstrating the various favorable characteristics of pulse-enhanced Pt/WOx/ITO devices.

Enhancing the Uniformity of a Memristor Using a Bilayer Dielectric Structure

Resistive random access memory (RRAM) holds great promise for in-memory computing, which is considered the most promising strategy for solving the von Neumann bottleneck. However, there are still significant problems in its application due to the non-uniform performance of RRAM devices. In this work, a bilayer dielectric layer memristor was designed based on the difference in the Gibbs free energy of the oxide. We fabricated Au/Ta2O5/HfO2/Ta/Pt (S3) devices with excellent uniformity. Compared with Au/HfO2/Pt (S1) and Au/Ta2O5/Pt (S2) devices, the S3 device has a low reset voltage fluctuation of 2.44%, and the resistive coefficients of variation are 13.12% and 3.84% in HRS and LRS, respectively, over 200 cycles. Otherwise, the bilayer device has better linearity and more conductance states in multi-state regulation. At the same time, we analyze the physical mechanism of the bilayer device and provide a physical model of ion migration. This work provides a new idea for designing and fabricating resistive devices with stable performance.

DenRAM: neuromorphic dendritic architecture with RRAM for efficient temporal processing with delays

An increasing number of studies are highlighting the importance of spatial dendritic branching in pyramidal neurons in the neocortex for supporting non-linear computation through localized synaptic integration. In particular, dendritic branches play a key role in temporal signal processing and feature detection. This is accomplished thanks to coincidence detection (CD) mechanisms enabled by the presence of synaptic delays that align temporally disparate inputs for effective integration. Computational studies on spiking neural networks further highlight the significance of delays for achieving spatio-temporal pattern recognition with pure feed-forward neural networks, without the need of resorting to recurrent architectures. In this work, we present “DenRAM”, the first realization of a feed-forward spiking neural network with dendritic compartments, implemented using analog electronic circuits integrated into a 130 nm technology node and coupled with Resistive Random Access Memory (RRAM) technology. DenRAM’s dendritic circuits use RRAM devices to implement both delays and synaptic weights in the network. By configuring the RRAM devices to reproduce bio-realistic timescales, and by exploiting their heterogeneity we experimentally demonstrate DenRAM’s ability to replicate synaptic delay profiles, and to efficiently implement CD for spatio-temporal pattern recognition. To validate the architecture, we conduct comprehensive system-level simulations on two representative temporal benchmarks, demonstrating DenRAM’s resilience to analog hardware noise, and its superior accuracy compared to recurrent architectures with an equivalent number of parameters. DenRAM not only brings rich temporal processing capabilities to neuromorphic architectures, but also reduces the memory footprint of edge devices, warrants high accuracy on temporal benchmarks, and represents a significant step-forward in low-power real-time signal processing technologies.

Flexible resistive memory device with egg-albumen/HfO x hybrid bilayer: fabrication and modeling of its switching variations

Egg-albumen, a natural polymer, in bilayer combination with ultrathin HfO x is explored as an active switching layer component in flexible resistive random access memory devices. The fabricated devices have shown excellent switching characteristics with a current on/off ratio of greater than 104, stable retention of both low resistance and high resistance states, reliable multiple cycle switching, and very low switching power (with set power as 0.5 µW and reset power as 3.1 mW). To investigate the electro-mechanical stability, devices were bent with different bending radii and it was found that negligible degradation in device performance was observed until a 5 mm bending radius. Furthermore, a simple mathematical model is used to simulate the devices’ characteristics and the values of fitting parameters were extracted with a root mean square error of less than 4.5%. Moreover, a switching variation was introduced by utilizing variations of the physical parameters, and a near practical physics based mathematical device model was demonstrated which can enable the strengthening of simulation capabilities for exploration of unique flexible resistive memory devices and related circuits.

Atomic layer annealing for spatial tailoring in sub-4 nm AlN RRAM devices with low-voltage operation

This article investigates the spatial tailoring of nitrogen vacancies by atomic layer annealing (ALA) on resistive random access memory (RRAM) devices with an AlN resistive switching layer. The ALA technique involves the in-situ layer-by-layer He/Ar plasma treatment in the cycle of atomic layer deposition for AlN. The AlN RRAM devices prepared with the ALA treatment near the TiN electrode have significantly superior uniformity of the operation voltages and the switching resistances, along with a lower cycle-to-cycle variation in endurance. This enhancement could be attributed to the relatively stable location of rupture and formation of conductive filaments, as a result of the film densification and the suppression of nitrogen vacancies in the AlN region treated with the ALA process. The AlN RRAM devices also demonstrate excellent retention of more than 106 seconds at 125°C. In addition, the ultra-thin 3.3 nm AlN switching layer contributes to low operation voltages of AlN RRAM. The outcomes manifest that the ALA technique could effectively improve the properties of nanoscale materials through precise spatial tailoring, with an accuracy up to atomic scale.

Dielectric Properties and Carrier Transport Mechanism in Annealed HfOx‐Based Resistive Random Access Memory Devices

The diversity of the carrier transport mechanism in the resistive switching process remains a significant obstacle for the design and application of resistive random access memory (RRAM) devices. In this study, the influence of annealing on the dielectric properties of the Ti/HfOx/Pt RRAM device and its associated carrier transport mechanism is investigated. The results reveal that the current conduction in both annealed and unannealed devices is primarily attributed to grain boundary (GB) relaxation, with only the GB acting as a depletion layer that induces dielectric relaxation. Furthermore, annealing decreases the interfacial polarization and changes the relaxation time at the GB. In addition, the charge carriers exhibit nearest‐neighbor hopping conduction at a higher temperature in Ti/HfOx/Pt RRAM devices, whereas variable‐range‐hopping conduction occurs at lower temperatures. Long‐range charge carrier transport also plays a significant role in the conduction process. To offer a deeper understanding of the conduction processes in the Ti/HfOx/Pt RRAM device, a carrier transport model is proposed, which provides valuable insights into the intricate mechanisms governing conduction in these devices.

Compensation architecture design utilizing residual resource to mitigate impacts of nonidealities in RRAM-based computing-in-memory chips

Resistive random access memory (RRAM) is a promising technology for energy-efficient in-memory computing. However, due to technology limits, RRAM device faces a series of reliability issues. Deep neural network (DNN) computing based on RRAM suffers from accuracy degradation. On the one hand, offline DNN training solutions are difficult to fully consider and simulate all nonidealities. Worse still, new error or nonideality may come up with the usage of RRAM, which further deteriorates the effectiveness of offline training. On the other hand, online training poses great challenges on programming overhead and device lifetime. The iterative write-verify technique to program multi-bit RRAM cells prolongs write latency more than 10× longer than read latency. To overcome these issues, we propose a compensation architecture and training designs to mitigate the realistic accuracy loss in RRAM chips with negligible hardware resource for RRAM-based DNN computing. Firstly, we add trainable compensation channels in crossbars utilizing the residual resource after original weight mapping. Secondly, an offline training procedure with computing output from hardware is triggered to settle down appropriate weight value in compensation channels. Experimental results demonstrate that the proposed design can guarantee ≤ 0.8% loss of accuracy in DNN even when nonidealities reduce the original accuracy down to ≤73%.

Atomic‐Scale Phase Transformation in Perovskite LaCoOx Resistive Switching Memristive Devices

Resistive random‐access memory (RRAM) is considered the next‐generation nonvolatile memory owing to its simplicity, low power consumption, and high storage density. Resistive switching (RS) occurs in a wide range of materials among the transition metal oxides. Herein, an epitaxial ternary metal oxide layer, LaCoOx (LCO), grown on Nb‐doped SrTiO3 substrates, is utilized as an RRAM device. When voltage is applied, it exhibits excellent RS behavior. More than 900 cycles are obtained, and the retention time reaches up to 104 s. To investigate the RS behavior, high‐resolution transmission electron microscopy and atomic‐scale scanning transmission electron microscopy are used to observe the structural evolution and oxygen ion migration in LCO. The structure exhibits a perovskite–brownmillerite topotactic phase transformation from LaCoO2.5 or LaCoO2.67 to the LaCoO3 conductive regions. The reversible transition between the low‐resistance states and high‐resistance states enables the RS mechanism. Additionally, the valence states are confirmed using high‐resolution X‐ray photoelectron spectroscopy. This study not only illustrates the oxygen‐ion migration mechanism of LCO but also demonstrates its suitability for RRAM applications.

Effect of Electrochemically Active Top Electrode Materials on Nanoionic Conductive Bridge Y2O3 Random-Access Memory.

Herein, sol-gel-processed Y2O3 resistive random-access memory (RRAM) devices were fabricated. The top electrodes (TEs), such as Ag or Cu, affect the electrical characteristics of the Y2O3 RRAM devices. The oxidation process, mobile ion migration speed, and reduction process all impact the conductive filament formation of the indium-tin-oxide (ITO)/Y2O3/Ag and ITO/Y2O3/Cu RRAM devices. Between Ag and Cu, Cu can easily be oxidized due to its standard redox potential values. However, the conductive filament is easily formed using Ag TEs. After triggering the oxidation process, the formed Ag mobile metal ions can migrate faster inside Y2O3 active channel materials when compared to the formed Cu mobile metal ions. The fast migration inside the Y2O3 active channel materials successfully reduces the SET voltage and improves the number of programming-erasing cycles, i.e., endurance, which is one of the nonvolatile memory parameters. These results elucidate the importance of the electrochemical properties of TEs, providing a deeper understanding of how these factors influence the resistive switching characteristics of metal oxide-based atomic switches and conductive-metal-bridge-filament-based cells.

Resistive Switching Devices for Neuromorphic Computing: From Foundations to Chip Level Innovations.

Neuromorphic computing has emerged as an alternative computing paradigm to address the increasing computing needs for data-intensive applications. In this context, resistive random access memory (RRAM) devices have garnered immense interest among the neuromorphic research community due to their capability to emulate intricate neuronal behaviors. RRAM devices excel in terms of their compact size, fast switching capabilities, high ON/OFF ratio, and low energy consumption, among other advantages. This review focuses on the multifaceted aspects of RRAM devices and their application to brain-inspired computing. The review begins with a brief overview of the essential biological concepts that inspire the development of bio-mimetic computing architectures. It then discusses the various types of resistive switching behaviors observed in RRAM devices and the detailed physical mechanisms underlying their operation. Next, a comprehensive discussion on the diverse material choices adapted in recent literature has been carried out, with special emphasis on the benchmark results from recent research literature. Further, the review provides a holistic analysis of the emerging trends in neuromorphic applications, highlighting the state-of-the-art results utilizing RRAM devices. Commercial chip-level applications are given special emphasis in identifying some of the salient research results. Finally, the current challenges and future outlook of RRAM-based devices for neuromorphic research have been summarized. Thus, this review provides valuable understanding along with critical insights and up-to-date information on the latest findings from the field of resistive switching devices towards brain-inspired computing.

Ce-doping at Mn site to enhance resistive switching performance of spinel MnCo2O4 resistive random access memory devices

The spinel Ce-doping MnCo2O4 (MCO) thin films were fabricated on Pt/Ti/SiO2/Si substrates for resistive switching (RS) layer using sol-gel spin-coating deposition method. The Pt/Mn0.925Ce0.075Co2O4/Pt (Pt/7.5MCC/Pt) device exhibits stabler and superior bipolar RS performance, the concentrated distribution of Reset/Set voltage as low as – 0.62/1.175 V, good cycle endurance and excellent time retention capability. The improvement in the RS performance of the Pt/7.5MCC/Pt devices can be attributable to the effective limitation of the random formation and rupture of conductive filaments by appropriate Ce doping. The carrier transport mechanism of the device at high resistance state can be dominated by the Schottky emission, whereas the carrier transport mechanism at low resistance state consistent with the Ohmic conduction. This work provides a potential performance improvement approach to design the resistive memory devices for data storage applications.

Enhanced resistive switching performance and structural evolution of NiO/Nb2O5−x bilayer memristive device

The development of bilayer models is crucial for enhancing the performance and enabling multifunctionality of next-generation resistive random-access memory (RRAM). However, detailed switching information is still insufficient for multilayer RRAM, necessitating direct observation of the microstructural evolution to clarify its switching mechanism. In this study, the electrical properties of Pt/Nb2O5−x/Pt monolayer devices were improved by introducing a polycrystalline NiO layer, and the resulting Pt/NiO/Nb2O5−x/Pt bilayer devices exhibited a doubling of the endurance and a reduction of the set voltage. The bilayer device also exhibited a long retention time (>104 s) and high on/off ratio of 104. Transmission electron microscopy, X-ray photoelectron spectroscopy, and electron energy-loss spectroscopy revealed that the conductive filament (CF) contained oxygen vacancies. In addition, a funnel-shaped CF was observed in the Pt/NiO/Nb2O5−x/Pt system, with the neck at the NiO/Nb2O5−x interface. This study provides a distinctive viewpoint and an innovative strategy for improving RRAM devices and exploring new applications in electronics.

Structural phase transition and resistive switching properties of Cu x O films during post-thermal annealing

We studied the phase change and resistive switching characteristics of copper oxide (Cu x O) films through post-thermal annealing. This investigation aimed to assess the material’s potential for a variety of electrical devices, exploring its versatility in electronic applications. The Cu x O films deposited by RF magnetron sputtering were annealed at 300, 500, and 700 °C in ambient air for 4 min by rapid thermal annealing (RTA) method, and then it was confirmed that the structural phase change from Cu2O to CuO occurred with increasing annealing temperature. Resistive random-access memory (ReRAM) devices with Au/Cu x O/p+-Si structures were fabricated, and the ReRAM properties appeared in CuO-based devices, while Cu2O ReRAM devices did not exhibit resistive switching behavior. The CuO ReRAM device annealed at 500 °C showed the best properties, with a on/off ratio of 8 × 102, good switching endurance of ∼100 cycles, data retention for 104 s, and stable uniformity in the cumulative probability distribution. This characteristic change could be explained by the difference in the grain size and density of defects between the Cu2O and CuO films. These results demonstrate that superior and stable resistive switching properties of RF-sputtered Cu x O films can be obtained by low-temperature RTA.

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.

Self-Assembly of Delta-Formamidinium Lead Iodide Nanoparticles to Nanorods: Study of Memristor Properties and Resistive Switching Mechanism.

In the quest for advanced memristor technologies, this study introduces the synthesis of delta-formamidinium lead iodide (δ-FAPbI3 ) nanoparticles (NPs) and their self-assembly into nanorods (NRs). The formation of these NRs is facilitated by iodide vacancies, promoting the fusion of individual NPs at higher concentrations. Notably, these NRs exhibit robust stability under ambient conditions, a distinctive advantage attributed to the presence of capping ligands and a crystal lattice structured around face-sharing octahedra. When employed as the active layer in resistive random-access memory devices, these NRs demonstrate exceptional bipolar switching properties. A remarkable on/off ratio (105 ) is achieved, surpassing the performances of previously reported low-dimensional perovskite derivatives and α-FAPbI3 NP-based devices. This enhanced performance is attributed to the low off-state current owing to the reduced number of halide vacancies, intrinsic low dimensionality, and the parallel alignment of NRs on the FTO substrate. This study not only provides significant insights into the development of superior materials for memristor applications but also opens new avenues for exploring low-dimensional perovskite derivatives in advanced electronic devices.

Stable switching behavior of low-temperature ZrO2 RRAM devices realized by combustion synthesis-assisted photopatterning

We have realized efficient photopatterning and high-quality ZrO2 films through combustion synthesis and manufactured resistive random access memory (RRAM) devices with excellent switching stability at low temperatures (250 °C) using these approaches. Combustion synthesis reduces the energy required for oxide conversion, thus accelerating the decomposition of organic ligands in the UV-exposed area, and promoting the formation of metal-oxygen networks, contributing to patterning. Thermal analysis confirmed a reduction in the conversion temperature of combustion precursors, and the prepared combustion ZrO2 films exhibited a high proportion of metal-oxygen bonding that constitutes the oxide lattice, along with an amorphous phase. Furthermore, the synergistic effect of combustion synthesis and UV/O3-assisted photochemical activation resulted in patterned ZrO2 films forming even more complete metal-oxygen networks. RRAM devices fabricated with patterned ZrO2 films using combustion synthesis exhibited excellent switching characteristics, including a narrow resistance distribution, endurance of 103 cycles, and retention for 105 s at 85 °C, despite low-temperature annealing. Combustion synthesis not only enables the formation of high-quality metal oxide films with low external energy but also facilitates improved photopatterning.

Memory device based on a nano-granulars and nano-worms structured MoS2 active layer: The origin of resistive switching characteristics

This study systematically demonstrates resistive switching (RS) functionality of MoS2 nanostructured [nano-granulars (NGs) and nano-worms (NWs)] based non-volatile resistive random access memory (ReRAM) device. Interestingly, the SET and RESET voltage sharply changes from NGs to NWs device. The RS behavior of devices is interpreted by proposing and discussing a model. In the Ag/MoS2(NGs)/ITO device, a high resistance state (HRS) and low resistance state (LRS) could be ascribed due to the formation/disruption of conducting filament via trapping-detrapping of electrons across the NGs active layer. In contrast, the RS behavior of Ag/MoS2(NWs)/ITO device is caused by forming of an Ag metallic filamentary route between the electrodes. The NWs structured device show substantially better endurance and homogeneity than the device with an NGs structure. This nanostructural-dependent device functionality allows extended RS properties and establishes a relationship between the material's nano-level structural and electrical features.

Revealing the quantum nature of the voltage-induced conductance changes in oxygen engineered yttrium oxide-based RRAM devices

In this work, the quasi-analog to discrete transition occurring in the current–voltage characteristic of oxygen engineered yttrium oxide-based resistive random-access memory (RRAM) devices is investigated in detail. In particular, the focus of our research is not on the absolute conductance values of this characteristic but on the magnitude of its conductance changes occurring during the reset process of the device. It is found that the detected changes correspond to conductance values predominantly of the order of the quantum unit of conductance G0 = 2e2/h, where e is the electron charge and h the Planck constant. This feature is observed even at conductance levels far above G0, i.e. where electron transport is seemingly diffusive. It is also observed that such behavior is reproducible across devices comprising yttrium oxide layers with different oxygen concentrations and measured under different voltage sweep rates. While the oxygen deficiency affects the total number of quantized conductance states, the magnitude of the changes in conductance, close to 1 G0, is invariant to the oxygen content of the functional layer.

Structural and electrical characteristics of Zr-doped HfO2 (HZO) thin films deposited by atomic layer deposition for RRAM applications

In this study, Zr-doped HfO2 (HZO) based resistive random-access memory (RRAM) device were fabricated. The Hf:Zr (1:1) ratio in the HZO films were controlled by changing the HfO2 and ZrO2 cycle ratio during the atomic layer deposition (ALD) process. Next, we studied the structural and electrical properties of the Au/HZO/TiN RRAM device structure. The RRAM devices exhibits an excellent resistance ratio of the high resistance state (HRS) to the low resistance state (LRS) of ~103 A, and as well as good endurance (300 cycles) and retention (>103 s), respectively. Further, the device showed different conduction mechanism in LRS and HRS modes. The lower biased linear region is dominated by ohmic conductivity, whereas the higher biased nonlinear region is dominated by a space charge limited current conduction. This device is suitable for application in future high-density nonvolatile memory RRAM devices.