Results 91 to 100 of about 13,297 (272)

Memristive Physical Reservoir Computing

Advanced Science, EarlyView.
Memristors’ nonlinear dynamics and input‐dependent memory effects make them ideal candidates for high‐performance physical reservoir computing (RC). Based on their conductance modulation, memristors can be classified as electronic or optoelectronic types.
Dian Jiao, Ziyuan Wang, Jingrui Wang, Li Zhang, Xianhua Wei, Lingxiang Hu, Zongxiao Li, Athanasios V. Vasilakos, Zhizhen Ye, Fei Zhuge   +9 more
wiley   +1 more source

Overview of amorphous carbon memristor device, modeling, and applications for neuromorphic computing

Nanotechnology Reviews
Carbon-based materials strongly pertain to citizens’ daily life due to their versatile derivatives such as diamond, graphite, fullerenes, carbon nanotube, single-layer graphene, and amorphous carbon (a-C).
Wu Jie, Yang Xuqi, Chen Jing, Li Shiyu, Zhou Tianchen, Cai Zhikuang, Lian Xiaojuan, Wang Lei   +7 more
doaj   +1 more source

Transfer-Free Analog and Digital Flexible Memristors Based on Boron Nitride Films

Nanomaterials
The traditional von Neumann architecture of computers, constrained by the inherent separation of processing and memory units, faces challenges, for instance, memory wall issue.
Sibo Wang, Xiuhuan Liu, Han Yu, Xiaohang Liu, Jihong Zhao, Lixin Hou, Yanjun Gao, Zhanguo Chen   +7 more
doaj   +1 more source

Epitaxial Bi2O2Se/Bi2O5Se Thin Films: Revealing Electric‐Field‐Driven Oxidation and Resistive Switching Dynamics for Advanced Memory Devices

Advanced Science, EarlyView.
Bi2O2Se/Bi2O5Se bilayer heterostructure exhibits reversible structural evolution during device operation, directly revealed by atomic‐scale investigation. Oxygen vacancy redistribution governs filament formation and rupture, enabling stable multilevel resistive switching and synaptic‐like behaviors.
Yen‐Jung Chen, Yong‐Jyun Wang, Zi‐Qin Hong, Chien‐Hua Wang, Yi‐Ning Wang, Jia De Cheng, Chun‐Wei Huang, Ying‐Hao Chu, Wen‐Wei Wu   +8 more
wiley   +1 more source

Weighted Echo State Graph Neural Networks Based on Robust and Epitaxial Film Memristors

Advanced Science
Hardware system customized toward the demands of graph neural network learning would promote efficiency and strong temporal processing for graph‐structured data.
Zhenqiang Guo, Guojun Duan, Yinxing Zhang, Yong Sun, Weifeng Zhang, Xiaohan Li, Haowan Shi, Pengfei Li, Zhen Zhao, Jikang Xu, Biao Yang, Yousef Faraj, Xiaobing Yan   +12 more
doaj   +1 more source

Optical Charge Trap Memory Based on Graphene/ZnO Heterostructures for Long‐Term Retention and Adaptive Learning

Advanced Electronic Materials, EarlyView.
A biocompatible graphene/ZnO optical charge trap memory (CTM) is reported with over 54 h retention, enabled by interfacial photodoping. Using transient absorption spectroscopy and electrical analysis, charge transfer quenching is elucidated and reveal that a large energy barrier at the interface is responsible for long‐term memory retention.
Seungmin Shin, Junhyung Kim, Hyungdoh Lee, Yixuan Dou, Jacob T. Heiden, Seung Eun Lee, Jinwoo Song, Lina Quan, Giulia Tagliabue, Min Seok Jang, Himchan Cho   +10 more
wiley   +1 more source

Organic Thin‐Film Transistors for Neuromorphic Computing

Advanced Electronic Materials, EarlyView.
Organic thin‐film transistors (OTFTs) are reviewed for neuromorphic computing applications, highlighting their power‐efficient, and biological time‐scale operation. This article surveys OFET and OECT devices, compares them with memristors and CMOS, analyzes how fabrication parameters shape spike‐based metrics, proposes standardized characterization ...
Luke McCarthy, Mohan V. Jacob, Mostafa Rahimi Azghadi   +2 more
wiley   +1 more source

RRAM Variability Harvesting for CIM‐Integrated TRNG

Advanced Electronic Materials, EarlyView.
This work demonstrates a compute‐in‐memory‐compatible true random number generator that harvests intrinsic cycle‐to‐cycle variability from a 1T1R RRAM array. Parallel entropy extraction enables high‐throughput bit generation without dedicated circuits. This approach achieves NIST‐compliant randomness and low per‐bit energy, offering a scalable hardware
Ankit Bende, Gokulnath Rajendran, Regina Dittmann, Anupam Chattopadhyay, Vikas Rana   +4 more
wiley   +1 more source

Quantum Memristor [PDF]

, 2020
Research in quantum computing hardware has shown that quantum bits can be implemented with superconducting circuits, these qubits could be used in other applications such as quantum devices for electronic systems. In this paper a nonlinear parameterised two qubits quantum device is presented, the current - voltage characteristic of this element is ...
openaire   +2 more sources

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

Advanced Electronic Materials, EarlyView.
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley   +1 more source