Results 81 to 90 of about 13,297 (272)

Stochastic compact model for memory and threshold switching memristors

APL Machine Learning
Memristors 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

Physical Implementation of Optical Material‐Based Neural Networks Processing Enabled by Long‐Persistent Luminescence

Advanced Science, EarlyView.
This study reports on the physical implementation of optical material‐based neural processing using long‐persistent luminescence as memory‐retention and nonlinear optical material. The system performs optical‐domain preprocessing with opto‐electronic interfaces for stimulus delivery and readout, enabling real‐time demonstrations including Pong gameplay
Sangwon Wi, Yunsang Lee
wiley   +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, Ronghuan Xie, Qiang Cao, Shishen Yan, Xiaolin Wang, Limei Zheng   +5 more
wiley   +1 more source

Advancements in 2D layered material memristors: unleashing their potential beyond memory

npj 2D Materials and Applications
The scalability of two-dimensional (2D) materials down to a single monolayer offers exciting prospects for high-speed, energy-efficient, scalable memristors.
Kiran A. Nirmal, Dhananjay D. Kumbhar, Arul Varman Kesavan, Tukaram D. Dongale, Tae Geun Kim   +4 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

PZT optical memristors

Nature Communications
Optical 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, Hongyan Yu, Tao Shu, Yueyang Zhang, Chengfeng Wen, Hengzhen Cao, Jin Xie, Hanwen Li, Zixu Xu, Gong Zhang, Zejie Yu, Huan Li, Liu Liu, Yaocheng Shi, Feng Qiu, Daoxin Dai   +15 more
openaire   +2 more sources

Efficient implementation of the Hodgkin-Huxley potassium channel via a single volatile memristor

Frontiers in Neuroscience
IntroductionIn 2012, potassium and sodium ion channels in Hodgkin-Huxley-based brain models were shown to exhibit memristive behavior. This positioned memristors as strong candidates for implementing biologically accurate artificial neurons.
Lennart P. L. Landsmeer, Lennart P. L. Landsmeer, Erbing Hua, Heba Abunahla, Muhammad Ali Siddiqi, Muhammad Ali Siddiqi, Muhammad Ali Siddiqi, Ryoichi Ishihara, Chris I. De Zeeuw, Chris I. De Zeeuw, Said Hamdioui, Christos Strydis, Christos Strydis   +12 more
doaj   +1 more source

Beyond Markov Chains, Towards Adaptive Memristor Network-based Music Generation

, 2013
We undertook a study of the use of a memristor network for music generation, making use of the memristor's memory to go beyond the Markov hypothesis. Seed transition matrices are created and populated using memristor equations, and which are shown to ...
Adamatzky, Andrew, Costello, Ben de Lacy, Gale, Ella, Matthews, Oliver   +3 more
core  

WS2 Optoelectronic Memristive Reservoir Enabling Ultra‐Low‐Power, Multi‐Task, and Environmentally Stable Neuromorphic Computing

Advanced Science, EarlyView.
WS2‐based in‐memory sensing reservoir computing integrates sensing, memory, and computation in one compact device. It achieves ∼94% N‐MNIST, ∼93% eye motion perception, and ∼89% speech recognition with ultra‐low energy (∼25.5 fJ/spike). The system shows stability at 95% humidity, endurance over 1.5M cycles, and supports synaptic plasticity, enabling ...
Dayanand Kumar, Hanrui Li, Divyanshu Divyanshu, Dhananjay D. Kumbhar, Manoj Kumar Rajbhar, Amit Singh, Abdul Momin Syed, Selma Amara, Gianluca Setti, Nazek El‐Atab   +9 more
wiley   +1 more source

Giant Conductivity Modulation and Chemical Neuromodulation via Proton‐Electron Coupling in a Hydrogen‐Bonded Coordination Polymer

Advanced Science, EarlyView.
A “de‐doping” strategy positions mixed protonic–electronic conductors (MPECs) as adaptive neuromorphic platforms with dynamically tunable transport. Co‐BAND achieves giant conductivity modulation (>106) and chemically tunable synaptic plasticity. Analogous to biological neuromodulation, solvent vapors dynamically reprogram the device's learning rules ...
Kwangmin Park, Jumin Park, Huiyeong Ju, Nasim Arafat, Byoung Gwan Lee, Joohee Oh, Eejin Jang, Hyunseob Lim, Seok Min Yoon, Dae‐Woon Lim, Intek Song   +10 more
wiley   +1 more source