Results 61 to 70 of about 13,298 (199)

Low Power Optoelectronic Neuromorphic Memristor for In‐Sensor Computing and Multilevel Hardware Security Communications

Advanced Science, EarlyView.
ABSTRACT Conventional software‐based encryption faces mounting limitations in power efficiency and security, inspiring the development of emerging neuromorphic computing hardware encryption. This study presents a hardware‐level multi‐dimensional encryption paradigm utilizing optoelectronic neuromorphic devices with low energy consumption of 3.3 fJ ...
Bo Sun, Jinhao Zhang, Jialin Meng, Tianyu Wang   +3 more
wiley   +1 more source

Activation Energy and Bipolar Switching Properties for the Co-Sputtering of ITO_X:SiO₂ Thin Films on Resistive Random Access Memory Devices

Nanomaterials, 2023
Activation energy, bipolar resistance switching behavior, and the electrical conduction transport properties of ITOX:SiO2 thin film resistive random access memory (RRAM) devices were observed and discussed.
Kai-Huang Chen, Chien-Min Cheng, Na-Fu Wang, Ming-Cheng Kao   +3 more
doaj   +1 more source

Advances and Perspectives in Graphene‐Based Quantum Dots Enabled Neuromorphic Devices

Advanced Science, EarlyView.
Graphene‐based QDs are zero‐dimensional carbon nanomaterials with pronounced quantum confinement and tunable electronic structures. Herein, we summarize their synthesis strategies and functionalization methods, and highlight their functional roles and operating mechanisms in devices, as well as recent advances in neuromorphic electronics. We anticipate
Yulin Zhen, Wei Zeng, Zherui Zhao, JiYu Zhao, Ziyan Huang, Zhuo Chen, Kui Zhou, Guanglong Ding, Su‐Ting Han, Ye Zhou   +9 more
wiley   +1 more source

Modeling of Self-Aligned Selector Based on Ultra-Thin Metal Oxide for Resistive Random-Access Memory (RRAM) Crossbar Arrays

Nanomaterials
Resistive random-access memory (RRAM) is a crucial element for next-generation large-scale memory arrays, analogue neuromorphic computing and energy-efficient System-on-Chip applications.
Mikhail Fedotov, Viktor Korotitsky, Sergei Koveshnikov   +2 more
doaj   +1 more source

Prediction of semi-metallic tetragonal Hf2O3 and Zr2O3 from first-principles

, 2012
A tetragonal phase is predicted for Hf2O3 and Zr2O3 using density functional theory. Starting from atomic and unit cell relaxations of substoichiometric monoclinic HfO2 and ZrO2, such tetragonal structures are only reached at zero temperature by ...
Blaise, Philippe, Fonseca, Leonardo R. C., Nishi, Yoshio, Xue, Kan-Hao   +3 more
core   +1 more source

Research on Resistive Switching Mechanism of SnO2/SnS2 Based Heterojunction Memory Devices

Advanced Electronic Materials, EarlyView.
This work fabricates SnO2/SnS2 RRAM using (NH4)4Sn2S6, achieving 224 pJ set energy at 0.4 V with >1000‐cycle stability and 4 × 104 s retention. XPS/SEM/AFM‐validated interfacial engineering enables uniform switching, advancing low‐power neuromorphic memory development.
WenBin Liu, Lifang Hu, RuoXuan Zhao, ZhiYong Hou, JinYu Tian   +4 more
wiley   +1 more source

Unipolar Resistance Switching in Amorphous High-k dielectrics Based on Correlated Barrier Hopping Theory

, 2009
We have proposed a kind of nonvolatile resistive switching memory based on amorphous LaLuO3, which has already been established as a promising candidate of high-k gate dielectric employed in transistors.
Gao, Xu, Guo, Hongxuan, Guo, Kang, Li, Kui, Liu, Zhiguo, Xia, Yidong, Xu, Bo, Yin, Jiang   +7 more
core   +1 more source

Diffusion Characteristics of Ru and Oxygen Vacancies in Ta2O5 for Resistive Random Access Memory Devices: A Density Functional Theory Investigation

Advanced Electronic Materials, EarlyView.
Atomistic analysis of ruthenium (Ru) and oxygen vacancy (OV) diffusion in Ta₂O₅‐based memristors is performed. DFT calculations demonstrate interstitial Ru in Ta₂O₅ has lower diffusion barriers and formation energies than OVs, enhancing mobility and stability.
Md. Sherajul Islam, Sabyasachi Ganguli, J. Joshua Yang, Ajit K Roy   +3 more
wiley   +1 more source

FangTianSim: High-Level Cycle-Accurate Resistive Random-Access Memory-Based Multi-Core Spiking Neural Network Processor Simulator

Frontiers in Neuroscience, 2022
Realization of spiking neural network (SNN) hardware with high energy efficiency and high integration may provide a promising solution to data processing challenges in future internet of things (IoT) and artificial intelligence (AI).
Jinsong Wei, Jinsong Wei, Zhibin Wang, Ye Li, Jikai Lu, Jikai Lu, Hao Jiang, Hao Jiang, Junjie An, Junjie An, Yiqi Li, Lili Gao, Xumeng Zhang, Tuo Shi, Tuo Shi, Qi Liu   +15 more
doaj   +1 more source

ReRAM/CMOS Array Integration and Characterization via Design of Experiments

Advanced Electronic Materials, EarlyView.
This paper proposes the Design of Experiments to characterize arrays of oxide‐based ReRAM devices by exploring the large characterization space efficiently using only a few numbers of experiments. Using in‐house integration of 20 000 ReRAM devices on a CMOS chip, the unconventional optimization approach determines optimized measurement parameters and ...
Imtiaz Hossen, William A. Borders, Advait Madhavan, Shweta Joshi, Patrick M. Braganca, Jabez J. McClelland, Brian D. Hoskins, Gina C. Adam   +7 more
wiley   +1 more source