Comparison With Nitride Interface Defects and Nanocrystals for Charge Trapping Layer Nanowire Gate-All-Around Nonvolatile Memory Performance

2018 ◽  
Vol 65 (2) ◽  
pp. 493-498
Author(s):  
Yu-Ru Lin ◽  
Yi-Wei Chiang ◽  
Yu-Hsien Lin ◽  
Wei-Cheng Wang ◽  
Yung-Chun Wu
Keyword(s):  
Nonvolatile Memory ◽  
Memory Performance ◽  
Charge Trapping ◽  
Interface Defects

Charge Storage Characteristics of Si-Rich Silicon Nitride and the Effect of Tunneling Thickness on Nonvolatile Memory Performance

2011 ◽  
Vol 181-182 ◽  
pp. 307-311
Author(s):  
Hong Hanh Nguyen ◽  
Ngoc Son Dang ◽  
Van Duy Nguyen ◽  
Kyungsoo Jang ◽  
Kyunghyun Baek ◽  
...  
Keyword(s):  
Silicon Nitride ◽  
Nonvolatile Memory ◽  
Memory Performance ◽  
Charge Trapping ◽  
Oxide Thickness ◽  
Memory Window ◽  
Charge Storage ◽  
Operating Voltage ◽  
Silicon Clusters ◽  
Retention Characteristics

Nonvolatile memory (NVM) devices with nitride-nitride-oxynitride (NNO) stack structure using Si-rich silicon nitride (SiNx) as charge trapping layer on glass substrate were fabricated. Amorphous silicon clusters existing in the Si-rich SiNxlayer enhance the charge storage capacity of the devices. Low temperature poly-silicon (LTPS) technology, plasma-assisted oxidation/nitridation method to form a uniform ultra-thin tunneling layer, and an optimal Si-rich SiNxcharge trapping layer were used to fabricate NNO NVM devices with different tunneling thickness 2.3, 2.6 and 2.9 nm. The increase memory window, lower voltage operation but little scarifying in retention characteristics of nitride trap NVM devices had been accomplished by reducing the tunnel oxide thickness. The fabricated NVM devices with 2.9 nm tunneling thickness shows excellent electrical properties, such as a low threshold voltage, a high ON/OFF current ratio, a low operating voltage of less than ±9 V and a large memory window of 2.7 V, which remained greater than 72% over a period of 10 years.

scholarly journals MoS2-based Charge-trapping synaptic device with electrical and optical modulated conductance

Nanophotonics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 2475-2486 ◽  
Author(s):  
Min Zhang ◽  
Zehui Fan ◽  
Xixi Jiang ◽  
Hao Zhu ◽  
Lin Chen ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Visual Processing ◽  
Nonvolatile Memory ◽  
High Performance ◽  
Memory Performance ◽  
Incident Light ◽  
Charge Trapping ◽  
Long Term Potentiation ◽  
Neuromorphic System

AbstractThe synapse is one of the fundamental elements in human brain performing functions such as learning, memorizing, and visual processing. The implementation of synaptic devices to realize neuromorphic computing and sensing tasks is a key step to artificial intelligence, which, however, has been bottlenecked by the complex circuitry and device integration. We report a high-performance charge-trapping memory synaptic device based on two-dimensional (2D) MoS2 and high-k Ta2O5–TiO2 (TTO) composite to build efficient and reliable neuromorphic system, which can be modulated by both electrical and optical stimuli. Significant and essential synaptic behaviors including short-term plasticity, long-term potentiation, and long-term depression have been emulated. Such excellent synaptic behaviors originated from the good nonvolatile memory performance due to the high density of defect states in the engineered TTO composite. The 2D synaptic device also exhibits effective switching by incident light tuning, which further enables pattern recognition with accuracy rate reaching 100%. Such experimental demonstration paves a robust way toward a multitask neuromorphic system and opens up potential applications in future artificial intelligence and sensing technology.

Novel SONOS-Type Nonvolatile Memory Device With Optimal Al Doping in HfAlO Charge-Trapping Layer

2008 ◽  
Vol 29 (3) ◽  
pp. 265-268 ◽  
Author(s):  
Ping-Hung Tsai ◽  
Kuei-Shu Chang-Liao ◽  
Chu-Yung Liu ◽  
Tien-Ko Wang ◽  
P. J. Tzeng ◽  
...  
Keyword(s):  
Nonvolatile Memory ◽  
Charge Trapping ◽  
Memory Device ◽  
Al Doping ◽  
Nonvolatile Memory Device

Al2O3–Cu2O composite charge-trapping nonvolatile memory

2016 ◽  
Vol 28 (1) ◽  
pp. 928-933 ◽  
Author(s):  
Jinqiu Liu ◽  
Jianxin Lu ◽  
Bo Xu ◽  
Yidong Xia ◽  
Jiang Yin ◽  
...  
Keyword(s):  
Nonvolatile Memory ◽  
Charge Trapping ◽  
Composite Charge
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