Neuromorphic Computing Using Emerging NV Memory Devices

2018 ◽  
pp. 221-269
Keyword(s):  
Memory Devices ◽  
Neuromorphic Computing

Resistive Switching Memory based on Silver-doped Chitosan Thin Films

MRS Advances ◽  
2018 ◽  
Vol 3 (33) ◽  
pp. 1943-1948 ◽  
Author(s):  
C. Strobel ◽  
T. Sandner ◽  
S. Strehle
Keyword(s):  
Thin Films ◽  
Resistive Switching ◽  
Tin Oxide ◽  
Bottom Electrode ◽  
Low Cost ◽  
Memory Devices ◽  
Neuromorphic Computing ◽  
Resistive Switching Memory ◽  
Switching Behaviour ◽  
Switching Memory

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.

scholarly journals Neuromorphic Computing Using Emerging Synaptic Devices: A Retrospective Summary and an Outlook

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1414
Author(s):  
Jaeyoung Park
Keyword(s):  
Human Brain ◽  
Memory Devices ◽  
Approximate Computing ◽  
Promising Candidate ◽  
Neuromorphic Computing ◽  
Fast Speed ◽  
Emerging Memory ◽  
Inherent Error ◽  
Atomic Switch ◽  
Computing Approach

In this paper, emerging memory devices are investigated for a promising synaptic device of neuromorphic computing. Because the neuromorphic computing hardware requires high memory density, fast speed, and low power as well as a unique characteristic that simulates the function of learning by imitating the process of the human brain, memristor devices are considered as a promising candidate because of their desirable characteristic. Among them, Phase-change RAM (PRAM) Resistive RAM (ReRAM), Magnetic RAM (MRAM), and Atomic Switch Network (ASN) are selected to review. Even if the memristor devices show such characteristics, the inherent error by their physical properties needs to be resolved. This paper suggests adopting an approximate computing approach to deal with the error without degrading the advantages of emerging memory devices.

Organic small molecule-based RRAM for data storage and neuromorphic computing

2020 ◽  
Vol 8 (37) ◽  
pp. 12714-12738 ◽  
Author(s):  
Boyuan Mu ◽  
Hsiao-Hsuan Hsu ◽  
Chi-Ching Kuo ◽  
Su-Ting Han ◽  
Ye Zhou
Keyword(s):  
Small Molecules ◽  
Data Storage ◽  
Small Molecule ◽  
State Of The Art ◽  
Random Access ◽  
Random Access Memory ◽  
Resistive Random Access Memory ◽  
Memory Devices ◽  
Access Memory ◽  
Neuromorphic Computing

Recent state-of-the-art developments related to organic small molecules for resistive random-access memory devices has been emphasized.

Transparent Photovoltaic Memory for neuromorphic device

Nanoscale ◽  
2021 ◽  
Author(s):  
Priyanka Bhatnagar ◽  
Thanh Tai Nguyen ◽  
Sangho Kim ◽  
Ji Heun Seo ◽  
Malkeshkumar Patel ◽  
...  
Keyword(s):  
Electronic Devices ◽  
Memory Devices ◽  
Neuromorphic Computing ◽  
Significant Potential ◽  
The Future ◽  
Heterojunction Device

Bio-inspired electronic devices have significant potential for use in memory devices of the future, including in the context of neuromorphic computing and architecture. This study proposes a transparent heterojunction device...

scholarly journals Emerging Memory Devices for Neuromorphic Computing

2019 ◽  
Vol 4 (4) ◽  
pp. 1800589 ◽  
Author(s):  
Navnidhi K. Upadhyay ◽  
Hao Jiang ◽  
Zhongrui Wang ◽  
Shiva Asapu ◽  
Qiangfei Xia ◽  
...  
Keyword(s):  
Memory Devices ◽  
Neuromorphic Computing ◽  
Emerging Memory

scholarly journals Embracing the Unreliability of Memory Devices for Neuromorphic Computing

2020 ◽  
Author(s):  
Marc Bocquet ◽  
Tifenn Hirtzlin ◽  
Jacques-Olivier Klein ◽  
Etienne Nowak ◽  
Elisa Vianello ◽  
...  
Keyword(s):  
Memory Devices ◽  
Neuromorphic Computing

Epitaxial ferroelectric thin films

1994 ◽  
Vol 52 ◽  
pp. 572-573
Author(s):  
S. G. Ghonge ◽  
E. Goo ◽  
R. Ramesh ◽  
R. Haakenaasen ◽  
D. K. Fork
Keyword(s):  
Single Crystal ◽  
Work Function ◽  
Nonvolatile Memory ◽  
Ferroelectric Properties ◽  
Electrical Contact ◽  
Memory Devices ◽  
Ferroelectric Films ◽  
Si Substrates ◽  
Electro Optic ◽  
Wide Range

Microstructure of epitaxial ferroelectric/conductive oxide heterostructures on LaAIO3(LAO) and Si substrates have been studied by conventional and high resolution transmission electron microscopy. The epitaxial films have a wide range of potential applications in areas such as non-volatile memory devices, electro-optic devices and pyroelectric detectors. For applications such as electro-optic devices the films must be single crystal and for applications such as nonvolatile memory devices and pyroelectric devices single crystal films will enhance the performance of the devices. The ferroelectric films studied are Pb(Zr0.2Ti0.8)O3(PLZT), PbTiO3(PT), BiTiO3(BT) and Pb0.9La0.1(Zr0.2Ti0.8)0.975O3(PLZT).Electrical contact to ferroelectric films is commonly made with metals such as Pt. Metals generally have a large difference in work function compared to the work function of the ferroelectric oxides. This results in a Schottky barrier at the interface and the interfacial space charge is believed to responsible for domain pinning and degradation in the ferroelectric properties resulting in phenomenon such as fatigue.

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