scholarly journals ReSe2-Based RRAM and Circuit-Level Model for Neuromorphic Computing

2021 ◽  
Vol 3 ◽  
Author(s):  
Yifu Huang ◽  
Yuqian Gu ◽  
Xiaohan Wu ◽  
Ruijing Ge ◽  
Yao-Feng Chang ◽  
...  
Keyword(s):  
Data Storage ◽  
Resistive Switching ◽  
Random Access ◽  
Long Term Potentiation ◽  
Computing System ◽  
Switching Behavior ◽  
Active Layer Thickness ◽  
Neuromorphic Computing ◽  
Multiple Step

Resistive random-access memory (RRAM) devices have drawn increasing interest for the simplicity of its structure, low power consumption and applicability to neuromorphic computing. By combining analog computing and data storage at the device level, neuromorphic computing system has the potential to meet the demand of computing power in applications such as artificial intelligence (AI), machine learning (ML) and Internet of Things (IoT). Monolayer rhenium diselenide (ReSe2), as a two-dimensional (2D) material, has been reported to exhibit non-volatile resistive switching (NVRS) behavior in RRAM devices with sub-nanometer active layer thickness. In this paper, we demonstrate stable multiple-step RESET in ReSe2 RRAM devices by applying different levels of DC electrical bias. Pulse measurement has been conducted to study the neuromorphic characteristics. Under different height of stimuli, the ReSe2 RRAM devices have been found to switch to different resistance states, which shows the potentiation of synaptic applications. Long-term potentiation (LTP) and depression (LTD) have been demonstrated with the gradual resistance switching behaviors observed in long-term plasticity programming. A Verilog-A model is proposed based on the multiple-step resistive switching behavior. By implementing the LTP/LTD parameters, an artificial neural network (ANN) is constructed for the demonstration of handwriting classification using Modified National Institute of Standards and Technology (MNIST) dataset.

Reliable analog resistive switching behaviors achieved using memristive devices in AlOx/HfOx bilayer structure for neuromorphic systems

2021 ◽  
Author(s):  
Meng Qi ◽  
Tianquan Fu ◽  
Huadong Yang ◽  
ye tao ◽  
Chunran Li ◽  
...  
Keyword(s):  
Resistive Switching ◽  
Learning Experience ◽  
Random Access ◽  
Resistive Random Access Memory ◽  
Spike Timing ◽  
Information Storage ◽  
Bilayer Structure ◽  
Neuromorphic Computing ◽  
Von Neumann ◽  
Simulation Based

Abstract Human brain synaptic memory simulation based on resistive random access memory (RRAM) has an enormous potential to replace traditional Von Neumann digital computer thanks to several advantages, including its simple structure, high-density integration, and the capability to information storage and neuromorphic computing. Herein, the reliable resistive switching (RS) behaviors of RRAM are demonstrated by engineering AlOx/HfOx bilayer structure. This allows for uniform multibit information storage. Further, the analog switching behaviors are capable of imitate several synaptic learning functions, including learning experience behaviors, short-term plasticity-long-term plasticity transition, and spike-timing-dependent-plasticity (STDP). In addition, the memristor based on STDP learning rules are implemented in image pattern recognition. These results may offer a promising potential of HfOx-based memristors for future information storage and neuromorphic computing applications.

A new opportunity for the emerging tellurium semiconductor: resistive switching device implementation

2021 ◽  
Author(s):  
Yifei Yang ◽  
Mingkun Xu ◽  
Lujie Xu ◽  
Xinxin Wang ◽  
Huan Liu ◽  
...  
Keyword(s):  
Data Storage ◽  
Resistive Switching ◽  
High Performance ◽  
Visual Recognition ◽  
Stimulus Frequency ◽  
Dielectric Materials ◽  
Cross Point ◽  
Electrochemically Active ◽  
Event Based

Abstract The electrochemical (EC) resistive switching (RS) cross-point arrays, composed of nonvolatile RS (NV-RS) memories and volatile RS (V-RS) selectors, hold promise for high-density data storage, in-memory computing and neuromorphic computing. However, the conventional EC-RS devices based on metallic filaments suffer from the notorious current-volatility dilemma that the low and high current requirements for NV-RS memories and V-RS selectors, respectively, cannot be satisfied simultaneously, due to the dominant EC nature of the RS. In this work, we demonstrate electrochemically active, low thermal-conductivity and low melting-temperature semiconducting tellurium filament-based RS devices that solve this dilemma, enabling NV-RS memories to operate under lower currents than do V-RS selectors. This novel phenomenon arises as the consequence of the adversarial EC and Joule heating (JH) effects. The devices also show unusual stimulus frequency dependent long-term plasticity (LTP)-to-short-term plasticity (STP) transition. Devices with this property can be generically utilized as spatial-temporal filters in spiking neural networks (SNNs) for high-performance event-based visual recognition tasks, as illustrated in our noise filtering simulations. By regulating the EC-JH relationship using dielectric materials with decreasing thermal conductivities, full functional-range tunable Te filament-based devices, from always-NV RS, to NV-to-V transitionable RS, and to always-V RS, are also demonstrated. The tellurium filament-based RS devices are promising enablers for functional cross-point arrays.

scholarly journals Electron-beam-irradiated rhenium disulfide memristors with low variability for neuromorphic computing

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Sifan Li ◽  
Bochang Li ◽  
Xuewei Feng ◽  
Li Chen ◽  
Yesheng Li ◽  
...  
Keyword(s):  
Electron Beam ◽  
Resistive Switching ◽  
Neuromorphic Computing ◽  
Reset Voltage ◽  
Voltage Variation ◽  
Artificial Synapse ◽  
Metal Insulator Metal ◽  
Temporal And Spatial ◽  
Transition Voltage

AbstractState-of-the-art memristors are mostly formed by vertical metal–insulator–metal (MIM) structure, which rely on the formation of conductive filaments for resistive switching (RS). However, owing to the stochastic formation of filament, the set/reset voltage of vertical MIM memristors is difficult to control, which results in poor temporal and spatial switching uniformity. Here, a two-terminal lateral memristor based on electron-beam-irradiated rhenium disulfide (ReS2) is realized, which unveils a resistive switching mechanism based on Schottky barrier height (SBH) modulation. The devices exhibit a forming-free, stable gradual RS characteristic, and simultaneously achieve a small transition voltage variation during positive and negative sweeps (6.3%/5.3%). The RS is attributed to the motion of sulfur vacancies induced by voltage bias in the device, which modulates the ReS2/metal SBH. The gradual SBH modulation stabilizes the temporal variation in contrast to the abrupt RS in MIM-based memristors. Moreover, the emulation of long-term synaptic plasticity of biological synapses is demonstrated using the device, manifesting its potential as artificial synapse for energy-efficient neuromorphic computing applications.

Complementary resistive switching behavior induced by varying forming current compliance in resistance random access memory

2015 ◽  
Vol 106 (21) ◽  
pp. 213505 ◽  
Author(s):  
Yi-Ting Tseng ◽  
Tsung-Ming Tsai ◽  
Ting-Chang Chang ◽  
Chih-Cheng Shih ◽  
Kuan-Chang Chang ◽  
...  
Keyword(s):  
Resistive Switching ◽  
Random Access ◽  
Random Access Memory ◽  
Switching Behavior ◽  
Access Memory ◽  
Resistive Switching Behavior ◽  
Resistance Random Access Memory ◽  
Current Compliance

scholarly journals Effects of Sm2O3 and V2O5 Film Stacking on Switching Behaviors of Resistive Random Access Memories

Crystals ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. 318
Author(s):  
Lin ◽  
Wu ◽  
Chen
Keyword(s):  
Resistive Switching ◽  
Random Access ◽  
Single Layer ◽  
High Resistance State ◽  
Switching Behavior ◽  
Bipolar Resistive Switching ◽  
Compliance Behavior ◽  
Order Of Magnitude ◽  
Resistance State ◽  
Switching Characteristics

: In this work, the resistive switching characteristics of resistive random access memories (RRAMs) containing Sm2O3 and V2O5 films were investigated. All the RRAM structures made in this work showed stable resistive switching behavior. The High-Resistance State and Low-Resistance State of Resistive memory (RHRS/RLRS) ratio of the RRAM device containing a V2O5/Sm2O3 bilayer is one order of magnitude higher than that of the devices containing a single layer of V2O5 or Sm2O3. We also found that the stacking sequence of the Sm2O3 and V2O5 films in the bilayer structure can affect the switching features of the RRAM, causing them to exhibit both bipolar resistive switching (BRS) behavior and self-compliance behavior. The current conduction mechanisms of RRAM devices with different film structures were also discussed.

A synaptic device built in one diode–one resistor (1D–1R) architecture with intrinsic SiOx-based resistive switching memory

2016 ◽  
Vol 1 (4) ◽  
Author(s):  
Yao-Feng Chang ◽  
Burt Fowler ◽  
Ying-Chen Chen ◽  
Fei Zhou ◽  
Chih-Hung Pan ◽  
...  
Keyword(s):  
Resistive Switching ◽  
Silicon Oxide ◽  
Complementary Metal Oxide Semiconductor ◽  
Long Term Potentiation ◽  
Spike Timing ◽  
Oxide Semiconductor ◽  
Resistive Switching Memory ◽  
Term Potentiation ◽  
Switching Memory

Abstract We realize a device with biological synaptic behaviors by integrating silicon oxide (SiOx) resistive switching memory with Si diodes to further minimize total synaptic power consumption due to sneak-path currents and demonstrate the capability for spike-induced synaptic behaviors, representing critical milestones for the use of SiO2-based materials in future neuromorphic computing applications. Biological synaptic behaviors such as long-term potentiation, long-term depression, and spike-timing dependent plasticity are demonstrated systemically with comprehensive investigation of spike waveform analyses and represent a potential application for SiOx-based resistive switching materials. The resistive switching SET transition is modeled as hydrogen (proton) release from the (SiH)2 defect to generate the hydrogenbridge defect, and the RESET transition is modeled as an electrochemical reaction (proton capture) that re-forms (SiH)2. The experimental results suggest a simple, robust approach to realize programmable neuromorphic chips compatible with largescale complementary metal-oxide semiconductor manufacturing technology.

Zinc Oxide and IGZO Bi-layer Synaptic Device with Highly Linear Long-term Potentiation and Depression Characteristics

2021 ◽  
Author(s):  
Hyun-Woong Choi ◽  
Ki-Woo Song ◽  
Seong-Hyun Kim ◽  
Nguyen Kim Thanh ◽  
Sunil Babu Eadi ◽  
...  
Keyword(s):  
Zinc Oxide ◽  
Electrical Properties ◽  
Oxygen Vacancy ◽  
Photoelectron Spectroscopy ◽  
Long Term Potentiation ◽  
Switching Behavior ◽  
Reset Voltage ◽  
Term Potentiation ◽  
Resistance State

Abstract The electrical properties, resistive switching behavior, and long-term potentiation/depression (LTP/LTD) in a single indium-gallium-zinc-oxide (IGZO) and bi-layer IGZO/ZnO memristors were investigated for synapse application. The use of oxide bi-layer memristor, in particular, improved electrical properties such as stability, reliability of memristors, and increase in the synaptic weight states. Bi-layer IGZO/ZnO memristors had a set voltage of 0.9 V, and reset voltage around -0.7 V, resulting in low-power consumption for neuromorphic systems. The oxygen vacancies in X-ray photoelectron spectroscopy analysis played a role in the modulation of the high-resistance state (HRS) (oxygen-deficient) and the low-resistance state (oxygen-rich) region. The VRESET of bi-layer IGZO/ZnO memristors was lower than that of a single IGZO, which implied that oxygen vacancy filaments could be easily ruptured due to the higher oxygen vacancy peak HRS layer. The nonlinearity of LTP and LTD characteristics in a bi-layer IGZO/ZnO memristor was 6.77% and 11.49%, respectively, compared to those of 20.03% and 51.1% in a single IGZO memristor, respectively. Therefore, the extra ZnO layer in the bi-layer memristor with IGZO was potentially significant and essential to achieve a small set voltage and a reset voltage, and the switching behavior to form the conductive path.

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