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An impressive success of spintronic applications has been typically realized in metal-based structures which utilize magnetoresistive effects for substantial improvements in the performance of computer hard drives and magnetic random access…

Other Condensed Matter · Physics 2009-11-13 Igor Zutic , Jaroslav Fabian , Steven C. Erwin

We report a bistable organic memory made of a single organic layer embedded between two electrodes, we compare to the organic/metal nanoparticle/organic tri-layers device [L.P. Ma, J. Liu, and Y. Yang, Appl. Phys. Lett. 80, 2997 (2002)]. We…

Materials Science · Physics 2015-06-24 Dominique Vuillaume , Kamal Lmimouni , Denis Tondelier , Christophe Fery , Gunther Haas

Building on a recently introduced model for non-volatile resistive switching, we propose a mechanism for unipolar resistance switching in metal-insulator-metal sandwich structures. The commutation from the high to low resistance state and…

Other Condensed Matter · Physics 2009-11-13 M. J. Sanchez , M. J. Rozenberg , I. H. Inoue

Combining scanning electron microscopy (SEM) and electron-beam-induced current (EBIC) imaging with transport measurements, it is shown that the current flowing across a two-terminal oxide-based capacitor-like structure is preferentially…

Materials Science · Physics 2009-11-07 C. Rossel , G. I. Meijer , D. Bremaud , D. Widmer

Edge devices operating in dynamic environments critically need the ability to continually learn without catastrophic forgetting. The strict resource constraints in these devices pose a major challenge to achieve this, as continual learning…

Systems and Control · Electrical Eng. & Systems 2024-11-12 Fatima Tuz Zohora , Vedant Karia , Nicholas Soures , Dhireesha Kudithipudi

Metastability is ubiquitous in diverse complex systems. In open quantum systems, metastability offers protection against dissipation and decoherence, yet its application in quantum batteries remains unexplored. We propose a solid-state open…

Quantum Physics · Physics 2025-09-03 Yuanjin Wang , Hao Wu , Qing Zhao

The faithful storage and coherent manipulation of quantum states with matter-systems enable the construction of large-scale quantum networks based on quantum repeater. To achieve useful communication rates, highly multimode quantum memories…

Brain-inspired computing architectures attempt to emulate the computations performed in the neurons and the synapses in human brain. Memristors with continuously tunable resistances are ideal building blocks for artificial synapses. Through…

Large-capacity Content Addressable Memory (CAM) is a key element in a wide variety of applications. The inevitable complexities of scaling MOS transistors introduce a major challenge in the realization of such systems. Convergence of…

Mesoscale and Nanoscale Physics · Physics 2015-03-17 Kamran Eshraghian , Kyoung Rok Cho , Omid Kavehei , Soon-Ku Kang , Derek Abbott , Sung-Mo Steve Kang

We suggest electronic circuits with memristors (resistors with memory) that operate as memcapacitors (capacitors with memory) and meminductors (inductors with memory). Using a memristor emulator, the suggested circuits have been built and…

Instrumentation and Detectors · Physics 2014-11-20 Yuriy V. Pershin , Massimiliano Di Ventra

Quantum memory devices with high storage efficiency and bandwidth are essential elements for future quantum networks. Solid-state quantum memories can provide broadband storage, but they primarily suffer from low storage efficiency. We use…

Quantum Physics · Physics 2024-04-08 Yisheng Lei , Haechan An , Zongfeng Li , Mahdi Hosseini

The possibility of in-memory computing with volatile memristive devices, namely, memristors requiring a power source to sustain their memory, is demonstrated. We have adopted a hysteretic graphene-based field emission structure as a…

Mesoscale and Nanoscale Physics · Physics 2017-01-17 Y. V. Pershin , S. N. Shevchenko

Portable miniaturized energy storage micro-supercapacitor has engrossed significant attention due to its power source and energy storage capacity, replacing batteries in ultra-small electronic devices. Fabrication with porous and 2D…

Applied Physics · Physics 2019-07-18 Meenakshi Talukdar , Sushant Kumar Behera , Pritam Deb

We report on resistive switching of memristive electrochemical metallization devices using 3D kinetic Monte Carlo simulations describing the transport of ions through a solid state electrolyte of an Ag/TiO$_{\text{x}}$/Pt thin layer system.…

Materials Science · Physics 2017-06-06 Sven Dirkmann , Thomas Mussenbrock

Some bi or multi-stable Mechanical meta-structures have been implemented as mechanical memory devices which however are with limits such as complex structural forms, low information storage capability and/or fragile structural stability to…

Materials Science · Physics 2023-04-20 Libiao Xin , Yanbin Li , Baolong Wang , Zhiqiang Li

As the models and the datasets to train deep learning (DL) models scale, system architects are faced with new challenges, one of which is the memory capacity bottleneck, where the limited physical memory inside the accelerator device…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-02-19 Youngeun Kwon , Minsoo Rhu

Hybrid ionic-electronic conductors have the potential to generate memory effects and neuronal behavior. The functionality of these mixed materials depends on ion motion through thin polarizable channels. Here, we explore different…

Monolithic three-dimensional integration of memory and logic circuits could dramatically improve performance and energy efficiency of computing systems. Some conventional and emerging memories are suitable for vertical integration,…

Emerging Technologies · Computer Science 2015-09-11 Gina C. Adam , Brian D. Hoskins , Mirko Prezioso , Dmitri B. Strukov

Construction and training principles have been proposed and tested for an artificial neural network based on metal-oxide thin-film nanostructures possessing bipolar resistive switching (memristive) effect. Experimental electronic circuit of…

Replacing electrons with photons is a compelling route towards light-speed, highly parallel, and low-power artificial intelligence computing. Recently, all-optical diffractive neural deep neural networks have been demonstrated. However, the…

Signal Processing · Electrical Eng. & Systems 2021-07-19 Xuhao Luo , Yueqiang Hu , Xin Li , Xiangnian Ou , Jiajie Lai , Na Liu , Huigao Duan