Reset Voltage Research Articles

Reliable BiI3-Based Resistive Random-Access Memory Devices with a High On/Off Ratio

In this paper, we report resistive random-access memory (RRAM) with bismuth iodide (BiI3) as the resistance switching layer, which exhibits an on/off ratio of the order of 108. The behaviors of the resistive switching performance of the BiI3 devices were systematically investigated. The chemical states and electronic structures of the resistance switching layer (BiI3) were studied via X-ray photoemission spectroscopy with depth profile. The spectroscopies demonstrate that the filament formation belongs to the metal bridge type, which is dominated by the presence of bismuth atoms resulting from the formation of silver iodide (AgI). X-ray diffraction, the cross section of transmission electron microscopy, scanning electron microscopy, and atomic force microscopy were employed to study the formation process of the metal filament in the BiI3-based RRAM. The results reveal that the upward diffusion of Ag cations will react with iodide anions, and bismuth cations will turn into the metallic state, which results in forming a conductive filament inside the resistance switching layer. Furthermore, the devices with the structure of Ag/polymethylmethacrylate (PMMA)/BiI3/PMMA/Au demonstrate low first reset voltage (approximately −0.66 V), a high retention larger than 5 × 104 s, and 6 × 103 switching cycles. This study not only demonstrates the excellent performance of BiI3-based RRAM devices but also provides fundamental insights into the mechanisms of the metallic filament first reset process in the BiI3 layers.

Non-Volatile Memory and Synaptic Characteristics of TiN/CeOx/Pt RRAM Devices.

In this study, we investigate the synaptic characteristics and the non-volatile memory characteristics of TiN/CeOx/Pt RRAM devices for a neuromorphic system. The thickness and chemical properties of the CeOx are confirmed through TEM, EDS, and XPS analysis. A lot of oxygen vacancies (ions) in CeOx film enhance resistive switching. The stable bipolar resistive switching characteristics, endurance cycling (>100 cycles), and non-volatile properties in the retention test (>10,000 s) are assessed through DC sweep. The filamentary switching model and Schottky emission-based conduction model are presented for TiN/CeOx/Pt RRAM devices in the LRS and HRS. The compliance current (1~5 mA) and reset stop voltage (−1.3~−2.2 V) are used in the set and reset processes, respectively, to implement multi-level cell (MLC) in DC sweep mode. Based on neural activity, a neuromorphic system is performed by electrical stimulation. Accordingly, the pulse responses achieve longer endurance cycling (>10,000 cycles), MLC (potentiation and depression), spike-timing dependent plasticity (STDP), and excitatory postsynaptic current (EPSC) to mimic synapse using TiN/CeOx/Pt RRAM devices.

Low-power multilevel resistive switching in β-Ga2O3 based RRAM devices

In this study, multilevel switching at low-power in Ti/TiN/Ga2O3/Ti/Pt resistive random-access memory (RRAM) devices has been systematically studied. The fabricated RRAM device exhibits an excellent non-overlapping window between set and reset voltages of ∼1.1 V with a maximum R off/R on ratio of ∼103. Moreover, to the best of our knowledge, the multi-bit storage capability of these RRAM devices with a reasonably high R off/R on ratio is experimentally demonstrated, for the first time, for lower compliance currents at 10 μA, 20 μA and 50 μA. The multi-bit resistive switching behavior of the Ga2O3 RRAM device at a low compliance current paves the way for low-power and high-density data storage applications.

Effect of annealing temperature on resistive switching behavior of Al/ La0.7Sr0.3MnO3 /LaNiO3 devices

La0.7Sr0.3MnO3 (LSMO)/LaNiO3 (LNO) thin films were deposited successively on Si single crystal by the sol-gel method. The bipolar resistive switching (RS) behavior was studied in Al/LSMO/LNO devices. Obvious current hysteresis was observed, the set (reset) voltage and resistance ratio were modulated by the annealing temperature of LSMO thin films. At the annealing temperature of 750 °C, good endurance and retention performance were obtained in the memory device. According to the fitting results of I–V curves, based on Schottky emission model, the conduction mechanisms of Al/LSMO/LNO devices were discussed. Our results may give a valuable insight on developing perovskite-type rare earth manganese oxide.

Temperature Regulated Artificial Neuron Based on Memristor

Recently, artificial neurons have attracted much attention due to their excellent energy efficiency and scalability. However, there are still few reports on the regulation of the performance of artificial neuron based on single device. In the letter, we present an artificial neuron device based on Ag/TaOx/Si that not only has excellent turn-on and turn-off performance, but also exhibits sustained stability under multiple cycle tests. Moreover, the Integrate -and-Fire (IF) neuron model is successfully simulated at room temperature. More importantly, we find that an increase of temperature could reduce the threshold voltage and reset voltage of neurons, improve the probability of neuronal firing, and promote the transformation of neurons from nonvolatile to volatile. This work provides an effective method for regulating artificial neurons and has important implications for studying information transfer in biology and adapting complex computations in a memory computing framework.

Anti-bacterial and transparent allantoin biomaterial-based biocomposite for non-volatile memory and brain-inspired computing applications

The allantoin biomaterial-based biocomposite was utilized to fabricate resistive switching (RS) devices for non-volatile memory and brain-inspired computing applications. The polymeric phase, surface morphology, and purity of biomaterial were characterized using different analytical tools. The allantoin biofilm shows anti-bacterial and transparent properties, therefore, it can be useful for wearable electronics. Novel allantoin biomaterial-based composite device exhibits forming-free bipolar resistive switching behavior with low SET (+0.50 V) and RESET (−1.34 V) voltages, good endurance (3 × 103 cycles), and memory retention properties (103 s). Additionally, the device mimics various bio-synaptic properties such as excitatory postsynaptic current, paired-pulse facilitation, and paired-pulse depression.

Multifunctional double active layers formed with electrochemically controlled nanoparticle dispersion for resistive switching memory arrays

Expanding resistive random-access memory (RRAM) from a single device to an array requires a selector to suppress the sneak path and an external device to control the compliance current. Thus, a unique crossbar array that can be independently driven through the novel design of a multilayer RRAM structure with intelligently controlled Cu2O consisting of nanoparticles embedded in the amorphous matrix (ANPs) is proposed. The ANPs–Cu2O active layers are prepared by electrodeposition, and the negative shift of the deposition potential induces a higher density and smaller size of the nanoparticles. The ANPs–Cu2O films show different set voltages and extremely uniform reset voltages, and thus a functional double active layer (DAL) structure consisting of two ANPs–Cu2O layers with different set voltages is proposed. The electrochemically fabricated VCu-controlled DALs effectively protected the reverse current from the self-rectifying characteristics of a large forward/reverse current ratio, thus realizing selector-less RRAMs. In addition, the soft-breakdown showing filament formation in the upper layer reveals the saturation current step acting as a self-compliance current without the assistance of transistors. Finally, a 4 × 4 crossbar DAL RRAM array with transistor-less self-rectification is demonstrated, which shows excellent memory performance and endurance without interfering with adjacent cells.

Correlation of natural honey-based RRAM processing and switching properties by experimental study and machine learning

Natural honey is a promising material for hardware components of nonvolatile memory and artificial synaptic devices in emerging renewable and biodegradable neuromorphic systems. The resistive switching properties of these devices are closely correlated with device process conditions. In this paper, honey based resistive random access memory (RRAM) devices were fabricated with different metal electrodes and drying temperature and duration. SET and RESET voltages were measured and used as dataset to train machine learning algorithms. Four machine learning models were applied to process data and demonstrated an average accuracy of 89.9 % to 91.6 % to predict the SET voltages in the range of [0 V, 6 V]. This study established a useful practice for fabrication of RRAM devices based on honey and can be extended to other natural organic materials.

On origin of resistive and capacitive contributions to impedance of memory states in Cu/TiO2/Pt RRAM devices by impedance spectroscopy

The resistive switching phenomenon is attributed to local formation and rupture of conductive filaments (CF), however some aspects of the switching mechanism still need wider consensus. The origin of resistance contribution to low resistance state (LRS) and high resistance state (HRS) is although well known, the origin of capacitive contribution to the memory state of resistive random access memory device (RRAM) is ambiguous. Here we report impedance spectroscopic studies carried on Cu/TiO2/Pt devices to address the origin of resistive and capacitive contribution, where the effect of DC bias voltage, reset stop voltage and set compliance current on the impedance of RRAM memory states were investigated in detail. The studies revealed that the capacitive contribution was dominated by the surrounding TiO2 bulk and contrary to existing knowledge, gap formed owing to ruptured CF has negligible role. These studies also reaffirmed the origin of the resistive contribution to the HRS and LRS state, which was dictated by the ruptured gap and connected CF, respectively. Results of this study may be significant towards improving the switching time and operating frequency performance of futuristic memory, RF switch and neuromorphic computing applications of RRAM devices.

Robust resistive switching in MoS2-based memristor with Ti top electrode

Nonvolatile memories based on two-dimensional nanomaterials are of significant interest to researchers attempting to achieve robust resistive switching (RS) with simple device integration and low energy consumption. In this study, the RS behavior of a MoS2-based memristor was investigated using Ti and Ag as top electrodes (TEs). Compared with the memristor using the Ag TE, that employing the Ti TE not only exhibited substantially enhanced and reproducible endurance performance for up to 104 cycles, but also showed excellent operational uniformity with a coefficient of variation limited to 3.5% and 4.0% for SET and RESET voltages, respectively. Moreover, the Ti TE memristor demonstrated RS behavior after 1 month of storage under ambient conditions. The formation of a TixSy layer at the Ti/MoS2 interface and the presence of an abundant 1T phase MoS2 (or S vacancy, VS) in the initial state of the MoS2 film contribute to its distinctive properties. This work indicates that suitable TE selection can enable the fabrication of high-performance nonvolatile MoS2-based memristors.

Atomic Layer Deposited SiOX-Based Resistive Switching Memory for Multi-Level Cell Storage

Herein, stable resistive switching characteristics are demonstrated in an atomic-layer-deposited SiOX-based resistive memory device. The thickness and chemical properties of the Pt/SiOX/TaN stack are verified by transmission electron microscopy (TEM) and X-ray photoemission spectroscopy (XPS). It is demonstrated that much better resistive switching is obtained using a negative set and positive reset compared to the opposite polarity. In addition, multi-level switching is demonstrated by changing the compliance current (CC) and the reset stop voltage, and potentiation and depression are emulated by applying pulses to achieve a synaptic device. Finally, a pulse endurance of 10,000 cycles and a retention time of 5000 s are confirmed by modulating the pulse input and reading voltage, respectively.

Oxygen Vacancies Controlled Highly Stable Bilayer Analog Synapse Used for Neuromorphic Computing Systems

This study investigated an oxygen-vacancy-controlled bilayer TiN/TaOy/TaOx/Pt memristive synaptic device for neuromorphic computing. Multilevel characteristics of the synaptic device were observed with RESET voltage varying between −1.4 and −1.9 V. The device shows highly stable reparative 200 potentiation and depression cycles. The high nonlinearity results of αp = 0.83 for potentiation and αd = −2.03 for depression were observed with the device’s potentiation and depression functions. The device also exhibits a highly stable DC endurance of at least 1000 cycles, an AC pulse endurance of 1 M, and a steady retention of 104 s at 100 °C without any degradation. Furthermore, a Hopfield neural network (HNN) is trained to recognize a 28 × 28 pixels image as an input, representing 784 synapses. In 23 epochs, the HNN successfully identified the input image with training accuracy over 92%. This bilayer memristive device can be highly suitable for neuromorphic devices in the development of neuromorphic-computing field.

A Novel Image Encryption Algorithm Based on Improved Arnold Transform and Chaotic Pulse-Coupled Neural Network.

Information security has become a focal topic in the information and digital age. How to realize secure transmission and the secure storage of image data is a major research focus of information security. Aiming at this hot topic, in order to improve the security of image data transmission, this paper proposes an image encryption algorithm based on improved Arnold transform and a chaotic pulse-coupled neural network. Firstly, the oscillatory reset voltage is introduced into the uncoupled impulse neural network, which makes the uncoupled impulse neural network exhibit chaotic characteristics. The chaotic sequence is generated by multiple iterations of the chaotic pulse-coupled neural network, and then the image is pre-encrypted by XOR operation with the generated chaotic sequence. Secondly, using the improved Arnold transform, the pre-encrypted image is scrambled to further improve the scrambling degree and encryption effect of the pre-encrypted image so as to obtain the final ciphertext image. Finally, the security analysis and experimental simulation of the encrypted image are carried out. The results of quantitative evaluation show that the proposed algorithm has a better encryption effect than the partial encryption algorithm. The algorithm is highly sensitive to keys and plaintexts, has a large key space, and can effectively resist differential attacks and attacks such as noise and clipping.

ZnSnOy/ZnSnOx Bilayer Transparent Memristive Synaptic Device for Neuromorphic Computing

In this letter, we have investigated synaptic features of a transparent bilayer memristor for neuromorphic computing applications. Our device has shown stable synaptic characteristics like potentiation and depression for repetitive 5000 epochs having 400 conductance pulses each. The device has also shown highly linear synaptic features with linearity of 1.2 and −1.4 for potentiation and depression, respectively. Retention property of bilayer transparent synapse showed good stability for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$10^{{5}}$ </tex-math></inline-formula> s at 90 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^{\text {o}}\text{C}$ </tex-math></inline-formula> . Multi-Level Cell (MLC) characteristics were achieved by varying reset stop voltages from −0.7V to −1.0V. The proposed bilayer transparent synapse showed good synaptic characteristics and showed high potential to be used in future neuromorphic computing systems.

Excellent performance Ruthenium doped Sb2Te3 alloy for phase change memory

The contradictory between thermal stability and operation speed has traditionally been the restriction to apply phase change memory (PCM) in the harsh condition. For providing a feasible solution, in this paper, Ru-modification is introduced to boost the data retention of Sb2Te3 without sacrificing the operation speed over the conventional Ge2Sb2Te5 compound. The both experimental and simulation results indicate that Ru locates at the grain boundary to inhibit the formation of large grains. Several performance of the device was enhanced, including: ultra-high 10-year data retention above 200 °C, lower Reset voltage about 1.9 V at 100 ns pulse width and a fast operation speed of 6 ns. Refined grains and smaller density change contributed to the reduced voltage and increased endurance. These findings demonstrated that PCM based Ru doped Sb2Te3 will be a potential application in high performance memories.

Switching facilitated by the simultaneous formation of oxygen vacancies and conductive filaments in resistive memory devices based on thermally annealed TiO2/a-IGZO bilayers

Resistive random access memory (ReRAM) devices have been gaining popularity in recent years as prime contenders to achieve high-performance non-volatile memory, as such devices offer simple structure, good stability, and high performance and low power consumption. Here, we present a resistive memory based on the bilayer of 2 nm TiO2 and 20 nm amorphous indium-gallium-zinc oxide (a-IGZO) thin films. The device is fabricated on a glass substrate with indium-tin-oxide bottom and silver top electrodes. Annealing temperature of the active layer is optimized by a comparative study of the memory devices, resulting in the widest memory window at 350 °C. X-ray photoemission spectroscopy was utilized to assess the change in the film stoichiometry caused by the annealing process. A memory mechanism is proposed with the generation and migration of oxygen vacancies and the formation of conductive filaments. Based on the device characteristics under repeated sweeps, SET and RESET voltages are selected at 2.0 and −2.0 V respectively, with READ voltage at 0.2 V, demonstrating low voltage operation. The optimized ReRAM has good retention stability for more than 1000 s and its endurance stability exceeds 500 s. The applicability is demonstrated in a circuit with an a-IGZO-based thin film transistor.

High-performance memristor based on MoS2 for reliable biological synapse emulation

Inspired by the neural network of the human brain, neuromorphic emulation for memorizing and processing data using electronic devices has attracted widespread intention. The conductance of memristor device can be changed by the charge flowing through it, which is analogical to the variation of synaptic plasticity with the applied external stimulation. However, the high switch voltage and inferior stability of memristor limit the further application to the imitation of biological synapse. Here, a memristor based on large-area MoS2 with vertical structure Al/MoS2/Cu is constructed, which is deposited by magnetron sputtering system on aluminum foil. The memristor presents superior stability and robustness, and has a small set and reset voltages with narrow variation distribution. More importantly, by applying relevant pulse sequence, the essential synaptic behaviors are mimicked by using the memristor based on MoS2, including paired-pulse facilitation (PPF) and spiking-time-dependent plasticity (STDP), etc.

Robust Resistive Switching Constancy and Quantum Conductance in High-k Dielectric-Based Memristor for Neuromorphic Engineering

For neuromorphic computing and high-density data storage memory, memristive devices have recently gained a lot of interest. So far, memristive devices have suffered from switching parameter instability, such as distortions in resistance values of low- and high-resistance states (LRSs and HRSs), dispersion in working voltage (set and reset voltages), and a small ratio of high and low resistance, among other issues. In this context, interface engineering is a critical technique for addressing the variation issues that obstruct the use of memristive devices. Herein, we engineered a high band gap, low Gibbs free energy Al2O3 interlayer between the HfO2 switching layer and the tantalum oxy-nitride electrode (TaN) bottom electrode to operate as an oxygen reservoir, increasing the resistance ratio between HRS and LRS and enabling multilayer data storage. The Pt/HfO2/Al2O3/TaN memristive device demonstrates analog bipolar resistive switching behavior with a potential ratio of HRS and LRS of > 105 and the ability to store multi-level data with consistent retention and uniformity. On set and reset voltages, statistical analysis is used; the mean values (µ) of set and reset voltages are determined to be − 2.7 V and + 1.9 V, respectively. There is a repeatable durability over DC 1000 cycles, 105 AC cycles, and a retention time of 104 s at room temperature. Quantum conductance was obtained by increasing the reset voltage with step of 0.005 V with delay time of 0.1 s. Memristive device has also displayed synaptic properties like as potentiation/depression and paired-pulse facilitation (PPF). Results show that engineering of interlayer is an effective approach to improve the uniformity, ratio of high and low resistance, and multiple conductance quantization states and paves the way for research into neuromorphic synapses.

Electronic synaptic plasticity and analog switching characteristics in Pt/TiOx/AlOx/AlTaON/TaN multilayer RRAM for artificial synapses

In this work, electronic synaptic plasticity and analog bipolar switching behavior by using a Pt/TiOx/AlOx/AlTaON/TaN multilayer resistive random-access memory (RRAM) device were examined. By using high-resolution transmission electron microscopy (HRTEM), the oxidation–reduction reaction occurs between the Ti buffer layer and the high-k Al2O3 layer at the top interface, and the high-k Al2O3 layer and the TaN bottom electrode at the bottom interface, resulting in the formation of the Pt/TiOx/AlOx/AlTaON/TaN multilayer RRAM structure. According to X-ray photoelectron spectroscopy (XPS) studies, different proportions of oxygen vacancies in TiOx/AlOx/AlTaON multilayer film play a key role in increasing RS properties uniformity. This multilayer structure-based RRAM device exhibits a stable RS behavior with a very large on/off resistance window (∼104), excellent durability (500 DC endurance cycles), and 104 s retention period with virtuous uniformity during the cycling operation. Furthermore, the device mean value (μ) set-and reset-voltage is −2.82 V, and +1.5 V, resulting in a low-operating voltage that is beneficial for neuromorphic systems. Besides, by adjusting the reset voltage, the device achieved a progressive transition from the low resistance state (LRS) to the high resistance state (HRS). To develop the artificial neural networks, basic biological properties such as potentiation, depression, and paired-pulse facilitation were efficiently mimicked. Ohmic conduction in the LRS and Schottky emission in the HRS are the two types of current transport conduction mechanisms. The analog bipolar switching behavior is governed by the redox reaction, which promotes the formation and rupture of oxygen vacancy-based conical shape conductive filaments. These findings show that multilayer RRAM devices have the potential to be used for future information storage and neuromorphic computing of artificial synapses.

3-D Physical Electro-Thermal Modeling of Nanoscale Y2O3 Memristors for Synaptic Application

Here, we report the physical electro-thermal modeling of nanoscale Y <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> O <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> -based memristor devices. The simulation is carried out by the combined software package of COMSOL Multiphysics and MATLAB. The presented physical modeling is based on the minimization of free energy at an applied voltage. The simulated results exhibit a stable pinched hysteresis loop in resistive switching (RS) response in multiple switching cycles. The RS responses show low values of coefficient of variability ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${C}_{V}$ </tex-math></inline-formula> ), i.e., 17.36% and 17.09% in SET and RESET voltages, respectively, during cycle-to-cycle variation. The impact of voltage ramp rate ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${V}_{RR}$ </tex-math></inline-formula> ) on the device characteristics such as switching response and synaptic plasticity behavior of the device is investigated. The simulated outcomes significantly depict the impact of oxide layer thickness on the switching voltages in the nanoscale device.