Results 51 to 60 of about 4,703 (195)
Advanced Materials, EarlyView.Mg─Te chalcogenides address the leakage scaling trade‐off in ultrathin selector‐only memory. Structural partitioning in multiphase Mg─Te, combined with highly ionic Mg─Te bonding and Hf interfacial engineering, supports reliable 5 nm thickness operation at low write voltage with suppressed leakage current, narrow threshold voltage distributions, 10 ns ...
Yoori Seo +5 more
wiley +1 more source
Nature‐Derived Chitosan Biopolymer: A Promising Candidate for Sustainable Electronics
Advanced Materials Technologies, EarlyView.In the creation of environmentally friendly devices, nature‐derived chitosan biopolymer is a promising contender for sustainable electronic research. It can be utilized to create more ecologically friendly scalable gadgets and has a variety of uses in different active layers of electronics.
Joshua McDonald +3 more
wiley +1 more source
RRAM based neuromorphic algorithms
CoRR, 2019 This submission is a report on RRAM based neuromorphic algorithms. This report basically gives an overview of the algorithms implemented on neuromorphic hardware with crossbar array of RRAM synapses. This report mainly talks about the work on deep neural network to spiking neural network conversion and its significance.
openaire +2 more sources
NanomaterialsResistive 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 +2 more
doaj +1 more source
Investigating the Temperature Effects on ZnO, TiO2, WO3 and HfO2 Based Resistive Random Access Memory (RRAM) Devices [PDF]
Журнал нано- та електронної фізики, 2016 In this paper, we report the effect of filament radius and filament resistivity on the ZnO, TiO2, WO3 and HfO2 based Resistive Random Access Memory (RRAM) devices. We resort to the thermal reaction model of RRAM for the present analysis.
T.D. Dongale +12 more
doaj +1 more source
Ferroelectric Devices for In‐Memory and In‐Sensor Computing
Advanced Science, EarlyView.Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang +5 more
wiley +1 more source
RRAM device with different switching layer thicknesses
, 2019 This paper presents switching characteristics of Ni/HfOx/p(+)-Si with different switching layer thicknesses (5/10 nm) in DC mode. Larger forming voltage and on/off ratio is obtained from the 10 nm HfOx RRAM while step-like reset process is seen from 5 nm
Min-Hwi Kim +15 more
core +1 more source
Sol–Gel-Processed Y2O3 Multilevel Resistive Random-Access Memory Cells for Neural Networks
Nanomaterials, 2023 Yttrium oxide (Y2O3) resistive random-access memory (RRAM) devices were fabricated using the sol–gel process on indium tin oxide/glass substrates. These devices exhibited conventional bipolar RRAM characteristics without requiring a high-voltage forming ...
Taehun Lee +9 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 +9 more
wiley +1 more source
, 2019 Resistance random-access memory (RRAM) is a promising candidate for both the next-generation non-volatile memory and the key element of neural networks.
Dittmann, Regina +10 more
core +1 more source