Controllable resistive switching of STO:Ag/SiO2-based memristor synapse for neuromorphic computing

Author(s):  
Nasir Ilyas ◽  
Jingyong Wang ◽  
Chunmei Li ◽  
Hao Fu ◽  
Dongyang Li ◽  
...  
2021 ◽  
Vol 9 ◽  
pp. 100125
Author(s):  
B. Sun ◽  
S. Ranjan ◽  
G. Zhou ◽  
T. Guo ◽  
Y. Xia ◽  
...  

Author(s):  
Meng Qi ◽  
Tianquan Fu ◽  
Huadong Yang ◽  
ye tao ◽  
Chunran Li ◽  
...  

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.


MRS Advances ◽  
2018 ◽  
Vol 3 (33) ◽  
pp. 1943-1948 ◽  
Author(s):  
C. Strobel ◽  
T. Sandner ◽  
S. Strehle

AbstractMemristors represent an intriguing two-terminal device strategy potentially able to replace conventional memory devices as well as to support neuromorphic computing architectures. Here, we present the resistive switching behaviour of the sustainable and low-cost biopolymer chitosan, which can be extracted from natural chitin present for instance in crab exoskeletons. The biopolymer films were doped with Ag ions in varying concentrations and sandwiched between a bottom electrode such as fluorinated-tin-oxide and a silver top electrode. Silver-doped devices showed an overall promising resistive switching behaviour for doping concentrations between 0.5 to 1 wt% AgNO3. As bottom electrode fluorinated-tin-oxide, nickel, silver and titanium were studied and multiple write and erase cycles were recorded. However, the overall reproducibility and stability are still insufficient to support broader applicability.


Nanoscale ◽  
2020 ◽  
Vol 12 (43) ◽  
pp. 22070-22074 ◽  
Author(s):  
Kuan-Chang Chang ◽  
Tianjiao Dai ◽  
Lei Li ◽  
Xinnan Lin ◽  
Shengdong Zhang ◽  
...  

This work investigated the influence of surrounding material on RRAM and offered a strategy to achieve multilevel storage functionality with superior scalability and stability, suggesting its potential to be applied in neuromorphic computing area.


2019 ◽  
Vol 13 (10) ◽  
pp. 1900204 ◽  
Author(s):  
Wenbin Zhang ◽  
Bin Gao ◽  
Jianshi Tang ◽  
Xinyi Li ◽  
Wei Wu ◽  
...  

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Sifan Li ◽  
Bochang Li ◽  
Xuewei Feng ◽  
Li Chen ◽  
Yesheng Li ◽  
...  

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.


Author(s):  
А.Н. Мацукатова ◽  
А.В. Емельянов ◽  
А.А. Миннеханов ◽  
Д.А. Сахарутов ◽  
А.Ю. Вдовиченко ◽  
...  

The properties of parylene based memristors with embedded silver nanoparticles were studied: current–voltage characteristics and resistive switching effect, endurance and retention time. It was found that introduction of nanoparticles leads to a significant improvement of the main memristive characteristics. Obtained results could be used to create large memristor arrays with homogeneous characteristics that emulate synapses in neuromorphic computing systems.


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