Results 41 to 50 of about 3,602 (165)
Mechanical Properties Analysis of Flexible Memristors for Neuromorphic Computing
Nano-Micro LettersHighlights This review systematically summarizes materials system, development history, device structure, stress simulation and applications of flexible memristors.
Zhenqian Zhu +3 more
doaj +1 more source
Temporal Dynamics Makes Memristive Physical Unclonable Functions More Secure and Ultra‐Lightweight
Advanced Electronic MaterialsMemristive physical unclonable function (PUF) is a recent entry to the list of security primitives, employing the intrinsic randomness of memristors. Although this represents a huge opportunity for memristors, all present memristive PUFs suffer from the ...
Yunpeng Guo, Cheng Ma, Huanglong Li
doaj +1 more source
Silk Protein Based Volatile Threshold Switching Memristors for Neuromorphic Computing
Advanced Electronic Materials, 2022 Memristors based neuromorphic devices can efficiently process complex information and fundamentally overcome the bottleneck of traditional computing based on von Neumann architecture.
Momo Zhao +13 more
doaj +1 more source
Advanced Electronic MaterialsDoped‐metal oxide‐based memristors, with the potential for improved switching performance and capability for multi‐bit information storage, are attractive candidates in the implementation of artificial neural network (ANN) hardware systems.
Quanzhou Zhu +13 more
doaj +1 more source
Modeling Networks of Probabilistic Memristors in SPICE [PDF]
Radioengineering, 2021 Efficient simulation of stochastic memristors and their networks requires novel modeling approaches. Utilizing a master equation to find occupation probabilities of network states is a recent major departure from typical memristor modeling [Chaos ...
V. J. Dowling +2 more
doaj
Nature CommunicationsOptical memristors represent a monumental leap in the fusion of photonics and electronics, heralding a new era of applications from neuromorphic computing to artificial intelligence. However, current technologies are hindered by complex fabrication, limited endurance, high optical loss or low modulation depth.
Chenlei Li +15 more
openaire +3 more sources
Stochastic compact model for memory and threshold switching memristors
APL Machine LearningMemristors are electron devices whose resistance changes according to the history of electrical signals applied to their two terminals. These resistance changes can remain for very long times or relax after a short time.
Jordi Suñé, Enrique Miranda
doaj +1 more source
Nature NanotechnologyAbstract The emergence of memristors offers a revolutionary solution for achieving in-memory computing at the hardware level. However, existing memristors suffer from the inherent channel materials damage during cyclical resistive switching, rendering excessive energy consumption and poor endurance.
Lanhao Qin +23 more
openaire +2 more sources
Formation of Light‐Emitting Defects in Ag‐Based Memristors
Advanced Electronic MaterialsOptical memristors are innovative devices that enable the integration of electro‐optical functionalities—such as light modulation, multilevel optical memory, and nonvolatile reprogramming—into neuromorphic networks.
Diana Singh +4 more
doaj +1 more source
Advancements in 2D layered material memristors: unleashing their potential beyond memory
npj 2D Materials and ApplicationsThe scalability of two-dimensional (2D) materials down to a single monolayer offers exciting prospects for high-speed, energy-efficient, scalable memristors.
Kiran A. Nirmal +4 more
doaj +1 more source