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Due to many limitations of Von Neumann architecture such as speed, memory bandwidth, efficiency of global interconnects and increase in the application of artificial neural network, researchers have been pushed to look into alternative…

Emerging Technologies · Computer Science 2019-05-15 Harshit Roy , Mrigank Sharad

The key feature of a memristor is that the resistance is a function of its previous resistance, thereby the behaviour of the device is influenced by changing the way in which potential is applied across it. Ultimately, information can be…

Emerging Technologies · Computer Science 2020-05-22 Alexander E. Beasley , Mohammed-Salah Abdelouahab , René Lozi , Anna L. Powell , Andrew Adamatzky

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…

The classic three-terminal electronic transistors and the emerging two-terminal ion-based memristors are complementary to each other in various nonconventional information processing systems in a heterogeneous integration approach, such as…

Applied Physics · Physics 2023-01-06 Yifei Yang , Lujie Xu , Mingkun Xu , Huan Liu , Dameng Liu , Wenrui Duan , Jing Pei , Huanglong Li

Networks with memristive devices are a potential basis for the next generation of computing devices. They are also an important model system for basic science, from modeling nanoscale conductivity to providing insight into the…

Disordered Systems and Neural Networks · Physics 2025-07-01 Frank Barrows , Forrest C. Sheldon , Francesco Caravelli

The general Lagrange-Euler formalism for the three memory circuit elements, namely, memristive, memcapacitive, and meminductive systems, is introduced. In addition, {\it mutual meminductance}, i.e. mutual inductance with a state depending…

Mesoscale and Nanoscale Physics · Physics 2015-06-03 G. Z. Cohen , Y. V. Pershin , M. Di Ventra

Memristors are prominent passive circuit elements with promising futures for energy-efficient in-memory processing and revolutionary neuromorphic computation. State-of-the-art memristors based on two-dimensional (2D) materials exhibit…

Computational Physics · Physics 2023-03-14 Samuel Aldana , Jakub Jadwiszczak , Hongzhou Zhang

Frequency generators are widely used in electronics. Here, we report the design and experimental realization of a memristive frequency generator employing a unique combination of only digital logic gates, a single-supply voltage and a…

Mesoscale and Nanoscale Physics · Physics 2016-05-30 Yuriy V. Pershin , Sergey N. Shevchenko , Franco Nori

Using basic algebra and simple calculus, the analytical solution to the memristor model of Strukov et al published in Nature is derived. Lissajous figures of current responding to a sinusoidal voltage are presented.

Classical Physics · Physics 2026-04-06 Frank Y. Wang

In this extended abstract, we have introduced a highly memory-efficient state vector simulation of quantum circuits premised on data compression, harnessing the capabilities of both CPUs and GPUs. We have elucidated the inherent challenges…

Quantum Physics · Physics 2023-10-02 Boyuan Zhang , Bo Fang , Qiang Guan , Ang Li , Dingwen Tao

Memristors are emerging as key electronic components that retain resistance states without power. Their non-volatile nature and ability to mimic synaptic behavior make them ideal for next-generation memory technologies and neuromorphic…

Mesoscale and Nanoscale Physics · Physics 2025-10-28 Tongxin Chen , Yinyu Nie , Yafei Hao , Shengchun Shen , Jiajun Pan , Xiaoguang Li , Yuan Lu

Switching uniformity, as a major challenge, hinders the practical implementation of \ac{RRAM} in memory application. Operating \ac{RRAM} in current mode, is proposed as an efficient method to improve programming schemes accuracy within the…

Emerging Technologies · Computer Science 2026-03-02 Bojian Zhang , Paolo Gibertini , Meysam Akbari , Erika Covi

A powerful time series analysis modeling technique is presented to describe cycle-to-cycle variability in memristors. These devices show variability linked to the inherent stochasticity of device operation and it needs to be accurately…

Mesoscale and Nanoscale Physics · Physics 2024-02-08 Francisco J. Alonso , David Maldonado , Ana M. Aguilera , Juan B. Roldán

Memristor-based neural networks provide an exceptional energy-efficient platform for artificial intelligence (AI), presenting the possibility of self-powered operation when paired with energy harvesters. However, most memristor-based…

Nanoscale resistive switching devices (memristive devices or memristors) have been studied for a number of applications ranging from non-volatile memory, logic to neuromorphic systems. However a major challenge is to address the potentially…

Other Condensed Matter · Physics 2013-07-04 Siddharth Gaba , Patrick Sheridan , Jiantao Zhou , Shinhyun Choi , Wei Lu

While the size of functional elements in memristors becomes of the orders of nano-meters or even smaller, the quantum effects in their dynamics can significantly influence their transport properties, consistent with recent experimental…

Mesoscale and Nanoscale Physics · Physics 2023-03-22 C Huggins , S Savel'ev , A Balanov , A Zagoskin

We propose a simple model of a nanoswitch as a memory resistor. The resistance of the nanoswitch is determined by electron tunneling through a nanoparticle diffusing around one or more potential minima located between the electrodes in the…

Mesoscale and Nanoscale Physics · Physics 2013-04-17 Sergey E. Savel'ev , Fabio Marchesoni , Alexander M. Bratkovsky

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

This paper presents a survey of the currently available hardware designs for implementation of the human cortex inspired algorithm, Hierarchical Temporal Memory (HTM). In this review, we focus on the state of the art advances of memristive…

Hardware Architecture · Computer Science 2018-05-09 Olga Krestinskaya , Irina Dolzhikova , Alex Pappachen James

The memristor can be used as non volatile memory (NVM) and for emulating neuron behavior. It has the ability to switch between low resistance $R_{on}$ and high resistance values $R_{off}$, and exhibit the synaptic dynamic behaviour such as…

Emerging Technologies · Computer Science 2018-09-28 Aidana Irmanova , Grant A. Ellis , Alex Pappachen James