Results 111 to 120 of about 32,825 (324)

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

Frequency dependent rectifier memristor bridge used as a programmable synaptic membrane voltage generator

Journal of Electrical Bioimpedance, 2013
Reasoned by its dynamical behavior, the memristor enables a lot of new applications in analog circuit design. Since some realizations have been shown (e.g.
Pabst Oliver, Schmidt Torsten
doaj   +1 more source

Improved dual sided doped memristor: modelling and applications

The Journal of Engineering, 2014
Memristor as a novel and emerging electronic device having vast range of applications suffer from poor frequency response and saturation length. In this paper, the authors present a novel and an innovative device structure for the memristor with two ...
Anup Shrivastava, Muhammad Khalid, Komal Singh, Jawar Singh   +3 more
doaj   +1 more source

Next-generation reservoir computing based on memristor array [PDF]

, 2022
Kuan Ren, Woyu Zhang, Fei Wang, Zeyu Guo, Dashan Shang   +4 more
openalex   +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

Energy-Efficient Neuromorphic Architectures for Nuclear Radiation Detection Applications

Sensors
A comprehensive analysis and simulation of two memristor-based neuromorphic architectures for nuclear radiation detection is presented. Both scalable architectures retrofit a locally competitive algorithm to solve overcomplete sparse approximation ...
Jorge I. Canales-Verdial, Jamison R. Wagner, Landon A. Schmucker, Mark Wetzel, Philippe Proctor, Merlin Carson, Jian Meng, Nathan J. Withers, Charles Thomas Harris, John J. Nogan, Denise B. Webb, Adam A. Hecht, Christof Teuscher, Marek Osiński, Payman Zarkesh-Ha   +14 more
doaj   +1 more source

Scaling Limits of Memristor-Based Routers for Asynchronous Neuromorphic Systems [PDF]

, 2023
Junren Chen, Siyao Yang, Huaqiang Wu, Giacomo Indiveri, Melika Payvand   +4 more
openalex   +1 more source

Molecular Crystal Memristor

Nature Nanotechnology
Abstract 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, Pengfei Guan, Jiefan Shao, Yu Xiao, Yimeng Yu, Jie Su, Conghui Zhang, Yanyong Li, Shenghong Liu, Pengyu Li, Decai Ouyang, Wenke He, Fenghao Liu, Kaichen Zhu, Kailang Liu, Zhenpeng Yao, Jinsong Wu, Yinghe Zhao, Huiqiao Li, Fei Hui, Peng Lin, Mario Lanza, Yuan Li, Tianyou Zhai   +23 more
openaire   +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

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