Results 41 to 50 of about 485 (168)

Investigation of Re-Program Scheme in Charge Trap-Based 3D NAND Flash Memory

IEEE Journal of the Electron Devices Society, 2021
Early retention or initial threshold voltage shift (IVS) is one of the key reliability challenges in charge trapping memory (CTM) based 3D NAND flash. Re-program scheme was introduced in quad-level-cell (QLC) NAND (Shibata et al., 2007, Lee et al., 2018,
Ting Cheng, Jianquan Jia, Lei Jin, Xinlei Jia, Shiyu Xia, Jianwei Lu, Kaiwei Li, Zhe Luo, Da Li, Hongtao Liu, Qiguang Wang, An Zhang, Daohong Yang, Zongliang Huo   +13 more
doaj   +1 more source

Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review

Advanced Science, EarlyView.
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh, Ki‐bum Lee, Junghyeon Lee, Seunghee Cho, Malkeshkumar Patel, Hangfei Li, Yu Wen, Ye Zhou, Joondong Kim   +8 more
wiley   +1 more source

3D NAND Flash Memory Cell Current and Interference Characteristics Improvement With Multiple Dielectric Spacer

IEEE Access, 2023
To achieve high density, the spacer length of three dimensional (3D) NAND device has been scaled down. When the program/erase cycle repeats, problems such as electrons accumulation in the inter-cell region are occurred. To solve this problem, a method of
Yun-Jae Oh, Inyoung Lee, Yunejae Suh, Daewoong Kang, Il Hwan Cho   +4 more
doaj   +1 more source

Self-Organizing Mapping Neural Network Implementation Based on 3-D NAND Flash for Competitive Learning

IEEE Journal of the Electron Devices Society
Self-organizing Map (SOM) neural network is a prominent algorithm in unsupervised machine learning, which is widely used for data clustering, high-dimensional visualization, and feature extraction.
Anyi Zhu, Lei Jin, Wen Zhou, Tianchun Ye, Zongliang Huo   +4 more
doaj   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

Smart Electrical Screening Methodology for Channel Hole Defects of 3D Vertical NAND (VNAND) Flash Memory

Eng
In order to successfully achieve mass production in NAND flash memory, a novel test procedure has been proposed to electrically detect and screen the channel hole defects, such as Not-Open, Bowing, and Bending, which are unique in high-density 3D NAND ...
Beomjun Kim, Gyeongseob Seo, Myungsuk Kim   +2 more
doaj   +1 more source

Physical and Electrical Analysis of Poly-Si Channel Effect on SONOS Flash Memory

Micromachines, 2021
In this study, polycrystalline silicon (poly-Si) is applied to silicon-oxide-nitride-oxide-silicon (SONOS) flash memory as a channel material and the physical and electrical characteristics are analyzed.
Jun-Kyo Jeong, Jae-Young Sung, Woon-San Ko, Ki-Ryung Nam, Hi-Deok Lee, Ga-Won Lee   +5 more
doaj   +1 more source

Silicon Nitride Resistive Memories

Advanced Electronic Materials, EarlyView.
Amorphous SiNx is an attractive resistance switching material for ReRAM applications due to its physicochemical properties, such as humidity resistance, low oxygen diffusivity, and is used as a metal diffusion blocker. By modifying the ratio between N and Si atoms, the microstructure of the SiNx is affected, rendering it possible to change the ...
Alexandros‐Eleftherios Mavropoulis, Nikolaos Vasileiadis, Iosif‐Angelos Fyrigos, Emmanouil Stavroulakis, Caroline Bonafos, Pascal Normand, Georgios Ch. Sirakoulis, Panagiotis Dimitrakis   +7 more
wiley   +1 more source

Determining the Relationship Between Composition, Structure, and Device Properties of GexSe1‐x‐Based Selector‐Only Memory

Advanced Electronic Materials, EarlyView.
Composition‐dependent structural evolution in GeXSe1‐X selector‐only memory (SOM) is correlated with device switching behavior. Increasing Ge strengthens network rigidity, suppresses atomic motion, and stabilizes threshold switching, while narrowing the memory window. The revealed structure–property relationship provides a guideline for compositionally
Tien Anh Nguyen, Changdeok Han, Dipannita Ghosh, Suyong Chae, Moongyu Choi, Sanghyun Ban, Myoungsub Kim, Sangmin Yoo, Seung Hwan Lee, Sieun Chae   +9 more
wiley   +1 more source

Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation

Advanced Intelligent Systems, EarlyView.
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison, Kevin Nadaud, Josquin Harrison, Guillaume F. Nataf, Laura Bégon‐Lours   +4 more
wiley   +1 more source