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With the ever-increasing digitization of society, the development of materials with low-power memory storage -similar to synapses- is becoming more relevant. The field of iontronic artificial synapses has gained traction, in particular with…

Soft Condensed Matter · Physics 2026-03-19 Esli Diepenbroek , Leon A. Smook , Sissi de Beer

Recent advances in nanoscale science and technology provide possibilities to directly self-assemble and integrate functional circuit elements within the wiring scheme of devices with potentially unique architectures. Electroionic resistive…

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

The morphology and dimension of the conductive filament formed in a memristive device are strongly influenced by the thickness of its switching medium layer. Aggressive scaling of this active layer thickness is critical towards reducing the…

Understanding the resistive switching behavior, or the resistance change, of oxide-based memristor devices, is critical to predicting their responses with known electrical inputs. Also, with the known electrical response of a memristor, one…

This article presents a spiking neuroevolutionary system which implements memristors as plastic connections, i.e. whose weights can vary during a trial. The evolutionary design process exploits parameter self-adaptation and variable…

Emerging Technologies · Computer Science 2012-12-17 Gerard Howard , Ella Gale , Larry Bull , Ben de Lacy Costello , Andy Adamatzky

We present a computationally inexpensive yet accurate phenomenological model of memristive behavior in titanium dioxide devices by fitting experimental data. By design, the model predicts most accurately I-V relation at small non-disturbing…

Materials Science · Physics 2015-06-22 Farnood Merrikh-Bayat , Brian Hoskins , Dmitri B. Strukov

The computational efficiency of the human brain is believed to stem from the parallel information processing capability of neurons with integrated storage in synaptic interconnections programmed by local spike triggered learning rules such…

Emerging Technologies · Computer Science 2020-03-17 S. R. Nandakumar , Bipin Rajendran

The human brain, with its energy-efficient and massively parallel architecture seamlessly integrates memory and computation. Its topology and functionality serve as the inspiration for the field of neuromorphic computing. Realizing…

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

Resistive switching (RS) devices, based on soft materials such as organic, biomolecules as well as natural plant extracts etc., has emerged as a promising alternative to the conventional memory technologies. They offer simple device…

Materials Science · Physics 2025-12-12 Rahul Deb , Debajyoti Bhattacharjee , Syed Arshad Hussain

The development of novel devices for neuromorphic computing and non-traditional logic operations largely relies on the fabrication of well controlled memristive systems with functionalities beyond standard bipolar behavior and digital…

Applied Physics · Physics 2020-01-29 C. Ferreyra , M. J. Sánchez , M. Aguirre , C. Acha , S. Bengió , J. Lecourt , U. Lüders , D. Rubi

Memristors have demonstrated immense potential as building blocks in future adaptive neuromorphic architectures. Recently, there has been focus on emulating specific synaptic functions of the mammalian nervous system by either tailoring the…

Disordered Systems and Neural Networks · Physics 2018-04-19 Taimur Ahmed , Sumeet Walia , Edwin Mayes , Rajesh Ramanathan , Vipul Bansal , Madhu Bhaskaran , Sharath Sriram , Omid Kavehei

Neuromorphic circuits mimic partial functionalities of brain in a bio-inspired information processing sense in order to achieve similar efficiencies as biological systems. While there are common mathematical models for neurons, which can be…

Emerging Technologies · Computer Science 2017-09-26 Enver Solan , Karlheinz Ochs

Memristive neural networks (MNNs), which use memristors as neurons or synapses, have become a hot research topic recently. However, most memristors are not compatible with mainstream integrated circuit technology and their stabilities in…

Emerging Technologies · Computer Science 2019-01-03 Zhiri Tang , Ruohua Zhu , Peng Lin , Jin He , Hao Wang , Qijun Huang , Sheng Chang , Qiming Ma

Dynamic reconfiguration of charge carriers in confined ion-channels under electrical stimulation produces memory effects, where the internal resistance depends on history of the electric field. Vermiculite nanofluidic devices harness this…

While two-terminal HfOX (x<2) memristor devices have been studied for ion transport and current evolution, there have been limited reports on the effect of the long-range thermal environment on their performance. In this work,…

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

All-optical active plasmonic devices are of fundamental importance for designing efficient nanophotonic circuits. We theoretically propose and numerically investigate an active plasmonic device made up of a nonlinear epsilon-near-zero…

Optics · Physics 2013-05-29 Alessandro Ciattoni , Carlo Rizza , Elia Palange

Memristors have been widely studied as artificial synapses in neuromorphic circuits, due to their functional similarity with biological synapses, low operating power, and high integration density. In this work, a memristive synapse,…

Emerging Technologies · Computer Science 2023-08-29 Y. Liu , D. Wang , Z. Dong , H. Xie , W. Zhao