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Synchronization of large spin Hall nano-oscillators (SHNO) arrays is an appealing approach toward ultra-fast non-conventional computing based on nanoscale coupled oscillator networks. However, for large arrays, interfacing to the network,…

Memristors offer significant advantages as in-memory computing devices due to their non-volatility, low power consumption, and history-dependent conductivity. These attributes are particularly valuable in the realm of neuromorphic circuits…

Neural and Evolutionary Computing · Computer Science 2024-07-19 Julio Souto , Guillermo Botella , Daniel García , Raúl Murillo , Alberto del Barrio

Two-dimensional (2D) materials are popular candidates for emerging nanoscale devices, including memristors. Resistive switching (RS) in such 2D material memristors has been attributed to the formation and dissolution of conductive filaments…

In the mammalian nervous system, various synaptic plasticity rules act, either individually or synergistically, and over wide-ranging timescales to dictate the processes that enable learning and memory formation. To mimic biological…

Disordered Systems and Neural Networks · Physics 2021-06-11 Syed Ghazi Sarwat , Benedikt Kersting , Timoleon Moraitis , Vara Prasad Jonnalagadda , Abu Sebastian

Amorphous insulators have localized wave functions that decay with the distance $r$ following exp($-r/\zeta$). Since nanoscale conduction is not excluded at $r<\zeta$, one may use amorphous insulators and take advantage of their size effect…

Mesoscale and Nanoscale Physics · Physics 2019-02-21 Yang Lu , I-Wei Chen

Memristors are promising devices for scalable and low power, in-memory computing to improve the energy efficiency of a rising computational demand. The crossbar array architecture with memristors is used for vector matrix multiplication…

Emerging Technologies · Computer Science 2025-05-20 Neethu Kuriakose , Arun Ashok , Christian Grewing , André Zambanini , Stefan van Waasen

Interface-type resistive switching (RS) devices with lower operation current and more reliable switching repeatability exhibits great potential in the applications for data storage devices and ultra-low-energy computing. However, the…

To obtain precisely controllable, robust as well as reproduceable memristor for efficient neuromorphic computing still very challenging. Molecular tailoring aims at obtaining the much more flexibly tuning plasticity has recently generated…

Mesoscale and Nanoscale Physics · Physics 2017-04-06 Zhiyong Wang , Laiyuan Wang , Masaru Nagai , Linghai Xie , Haifeng Ling , Qi Li , Ying Zhu , Tengfei Li , Mingdong Yi , Naien Shi , Wei Huang

Physical systems exhibiting neuromechanical functions promise to enable structures with directly encoded autonomy and intelligence. We report on a class of neuromorphic metamaterials embodying bioinspired mechanosensing, memory, and…

The superior density of passive analog-grade memristive crossbars may enable storing large synaptic weight matrices directly on specialized neuromorphic chips, thus avoiding costly off-chip communication. To ensure efficient use of such…

Emerging Technologies · Computer Science 2019-07-01 Hyungjin Kim , Hussein Nili , Mahmood Mahmoodi , Dmitri Strukov

Atomically thin layered two-dimensional materials, including transition-metal dichacolgenide (TMDC) and black phosphorus (BP), (1) have been receiving much attention, because of their promising physical properties and potential applications…

Materials Science · Physics 2016-02-17 Qi Feng , Faguang Yan , Wengang Luo , Kaiyou Wang?

Memristors are promising next-generation memory candidates that are nonvolatile, possess low power requirements and are capable of nanoscale fabrication. In this article we physically realise and describe the use of organic memristors in…

Emerging Technologies · Computer Science 2012-12-17 Victor Erokhin , Gerard David Howard , Andrew Adamatzky

Neuromorphic computing --- brainlike computing in hardware --- typically requires myriad CMOS spiking neurons interconnected by a dense mesh of nanoscale plastic synapses. Memristors are frequently citepd as strong synapse candidates due to…

Neural and Evolutionary Computing · Computer Science 2015-09-02 David Howard , Larry Bull , Ben De Lacy Costello

The development of neuromorphic systems based on memristive elements - resistors with memory - requires a fundamental understanding of their collective dynamics when organized in networks. Here, we study an experimentally inspired model of…

Statistical Mechanics · Physics 2017-01-18 Forrest C. Sheldon , Massimiliano Di Ventra

We suggest a possible realization of a solid-state memory capacitive (memcapacitive) system. Our approach relies on the slow polarization rate of a medium between plates of a regular capacitor. To achieve this goal, we consider a…

Mesoscale and Nanoscale Physics · Physics 2019-05-07 J. Martinez , M. Di Ventra , Yu. V. Pershin

Memristor-based neuromorphic computing could overcome the limitations of traditional von Neumann computing architectures -- in which data are shuffled between separate memory and processing units -- and improve the performance of deep…

We demonstrate low energy, forming and compliance-free operation of a resistive memory obtained by the partial oxidation of a two-dimensional layered van-der-Waals semiconductor: hafnium disulfide (HfS$_2$). Semiconductor - oxide…

Atomically thin semiconducting MoS2 is of great interest for high-performance flexible electronic and optoelectronic devices. Initial measurements using back-gated field-effect transistor (FET) structures on SiO2 yielded mobility of 1-50…

Mesoscale and Nanoscale Physics · Physics 2015-06-12 Michael S. Fuhrer , James Hone

Two-dimensional (2D) transition metal dichalcogenides (TMDs), such as molybdenum disulfide (MoS$_2$), are emerging as promising materials for next-generation electronic devices. They have proved to be serious candidates for integration with…

The memristive device is one of the basic elements of novel, brain-inspired, fast, and energy-efficient information processing systems in which there is no separation between memorization and information analysis functions. Since the first…

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