Results 101 to 110 of about 11,242 (219)
Advanced Intelligent Systems, EarlyView.Large‐scale Hopfield neural networks (HNNs) for associative computing are implemented using vertical NAND (VNAND) flash memory. The proposed VNAND HNN with the asynchronous update scenario achieve robust image restoration performance despite fabrication variations, while significantly reducing chip area (≈117× smaller than resistive random‐access ...
Jin Ho Chang +4 more
wiley +1 more source
Electromagnetic Analysis of Vertical Resistive Memory with a Sub-nm Thick Electrode
Nanomaterials, 2020 Resistive random access memories (RRAMs) are a type of resistive memory with two metal electrodes and a semi-insulating switching material in-between. As the persistent technology node downscaling continues in transistor technologies, RRAM designers also
Batyrbek Alimkhanuly +3 more
doaj +1 more source
Hafnium carbide formation in oxygen deficient hafnium oxide thin films
, 2016 On highly oxygen deficient thin films of hafnium oxide (hafnia, HfO$_{2-x}$) contaminated with adsorbates of carbon oxides, the formation of hafnium carbide (HfC$_x$) at the surface during vacuum annealing at temperatures as low as 600 {\deg}C is ...
Alff, L. +8 more
core +1 more source
Advanced Intelligent Systems, EarlyView.This study explores amorphous phosphate semiconductor glass for resistive random access memory (RRAM) applications. The nanodevices exhibit distinct resistive switching via trap‐assisted tunneling, space‐charge‐limited current, and Ohmic transport.
Hong‐Lin Lu +2 more
wiley +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 +3 more
core +1 more source
Review of Memristors for In‐Memory Computing and Spiking Neural Networks
Advanced Intelligent Systems, EarlyView.Memristors uniquely enable energy‐efficient, brain‐inspired computing by acting as both memory and synaptic elements. This review highlights their physical mechanisms, integration in crossbar arrays, and role in spiking neural networks. Key challenges, including variability, relaxation, and stochastic switching, are discussed, alongside emerging ...
Mostafa Shooshtari +2 more
wiley +1 more source
Advanced Intelligent Systems, EarlyView.A 48 × 48 ferroelectric tunnel junction (FTJ) crossbar array is fabricated and optimized through postmetallization annealing, enabling stable polarization switching and reliable multilevel conductance programming. Half‐bias operation, accurate vector–matrix multiplication with less than 1% error, and CIFAR‐10 image classification with near‐software ...
Sangwook Youn, Hwiho Hwang, Hyungjin Kim
wiley +1 more source
Low-Rank Compensation in Hybrid 3D-RRAM/SRAM Computing-in-Memory System for Edge Computing
EngArtificial intelligence (AI) has made significant strides, with computing-in-memory (CIM) emerging as a key enabler for energy-efficient AI acceleration.
Weiye Tang +7 more
doaj +1 more source
Advanced Intelligent Systems, EarlyView.A fully integrated analog processing‐in‐memory system is demonstrated, combining charge‐trap flash synapse arrays with a successive integration‐and‐rescaling neuron circuit. The architecture performs bit‐sliced analog accumulation with high linearity and low power, achieving efficient and scalable analog in‐memory computing and bridging device‐level ...
Sojoong Kim +4 more
wiley +1 more source
, 2014 The rapid development of computing technology is reflected in the fact that industry has consistently doubled the number of transistors per unit area on a semiconductor wafer every two years.
Kenyon, AJ, Mehonic, A
core