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The memristor is the fundamental non-linear circuit element, with uses in computing and computer memory. ReRAM (Resistive Random Access Memory) is a resistive switching memory proposed as a non-volatile memory. In this review we shall…

Materials Science · Physics 2016-11-15 Ella Gale

Memristors are passive elements that allow us to store information using a single element per bit. However, this is not the only utility of the memristor. Considering the physical chemical structure of the element used, the memristor can…

Emerging Technologies · Computer Science 2017-05-10 David Alejandro Trejo Pizzo

In recent times, neural networks have been gaining increasing importance in fields such as pattern recognition and computer vision. However, their usage entails significant energy and hardware costs, limiting the domains in which this…

Memristors are nonlinear two-terminal circuit elements whose resistance at a given time depends on past electrical stimuli. Recently, networks of memristors have received attention in neuromorphic computing since they can be used as a tool…

Optimization and Control · Mathematics 2024-09-24 Marieke Heidema , Henk van Waarde , Bart Besselink

The duration, strength and structure of memory effects are crucial properties of physical evolution. Due to the invasive nature of quantum measurement, such properties must be defined with respect to the probing instruments employed. Here,…

Quantum Physics · Physics 2021-06-18 Yu Guo , Philip Taranto , Bi-Heng Liu , Xiao-Min Hu , Yun-Feng Huang , Chuan-Feng Li , Guang-Can Guo

We suggest an approach to use memristors (resistors with memory) in programmable analog circuits. Our idea consists in a circuit design in which low voltages are applied to memristors during their operation as analog circuit elements and…

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

The advent of deep learning has resulted in a number of applications which have transformed the landscape of the research area in which it has been applied. However, with an increase in popularity, the complexity of classical deep neural…

Emerging Technologies · Computer Science 2022-08-24 Venkatesh Rammamoorthy , Geng Zhao , Bharathi Reddy , Ming-Yang Lin

We simulate static memory materials on a two-dimensional lattice. The bulk properties of such materials depend on boundary conditions. Considerable information can be stored in various local patterns. We observe local probabilities…

Statistical Mechanics · Physics 2018-02-26 D. Sexty , C. Wetterich

The advent of memristors and resistive switching has transformed solid state physics, enabling advanced applications such as neuromorphic computing. Inspired by these developments, we introduce the concept of Mem-emitters, devices that…

When magnets are fashioned into nanoscale elements, they exhibit a wide variety of phenomena replete with rich physics and the lure of tantalizing applications. In this topical review, we discuss some of these phenomena, especially those…

Mesoscale and Nanoscale Physics · Physics 2021-12-08 Bivas Rana , Amrit Kumar Mondal , Supriyo Bandyopadhyay , Anjan Barman

Reconfigurable memristors featuring neural and synaptic functions hold great potential for neuromorphic circuits by simplifying system architecture, cutting power consumption, and boosting computational efficiency. Their additive…

Memory effects in time-series of experimental observables are ubiquitous, have important cosequences for the interpretation of kinetic data, and may even affect the function of biomolecular nanomachines such as enzymes. Here we propose a…

Statistical Mechanics · Physics 2021-06-02 Alessio Lapolla , Aljaž Godec

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

The development of new computing technologies has given a new stimulus in the study of multiferroics. The use of multiferroics allows the realization of competitive energy efficient scalable logic and storage devices. The low-power…

Materials Science · Physics 2023-10-10 Z. V. Gareeva , N. V. Shulga , A. K. Zvezdin

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

We extend to materials with fading memory and materials with internal variables a result previously established by one of us for materials with instantaneous memory: the additive decomposability of the total energy into an internal and a…

Mathematical Physics · Physics 2009-07-30 Antonino Favata , Paolo Podio-Guidugli , Giuseppe Tomassetti

Micro and nanoscale materials have remarkable mechanical properties, such as enhanced strength and toughness, but usually display sample-to-sample fluctuations and non-trivial size effects, a nuisance for engineering applications and an…

Materials Science · Physics 2022-06-17 Alessandro Taloni , Michele Vodret , Giulio Costantini , Stefano Zapperi

When we encounter a new person or place, we may easily encode it into our memories, or we may quickly forget it. Recent work finds that this likelihood of encoding a given entity - memorability - is highly consistent across viewers and…

Neurons and Cognition · Quantitative Biology 2020-04-21 Wilma A. Bainbridge

In present day technology, storing and processing of information occur on physically distinct regions of space. Not only does this result in space limitations; it also translates into unwanted delays in retrieving and processing of relevant…

Emerging Technologies · Computer Science 2013-04-09 M. Di Ventra , Y. V. Pershin

The periodic response of magnetoresistance to an externally tunable parameter, such as magnetic field or chemical composition, in the bulk or an artificially designed material has been exploited for technological applications as well as to…

Materials Science · Physics 2012-09-04 S. Dickert , D. K. Singh , R. Thantirige , M. T. Tuominen