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20112021
most citedTraining and Operation of an Integrated Neuromorphic Network Based on Metal-Oxide Memristors

3k citations · 3.7k across the 11 of their papers we have counts for

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Showing cond-mat.mtrl-sciShow all

5 papers · 1 filter

cond-mat.mtrl-sci2021★ 99 cited

Computing and Memory Technologies based on Magnetic Skyrmions

Hamed Vakili, Wei Zhou, Chung T Ma +13

Solitonic magnetic excitations such as domain walls and, specifically, skyrmionics enable the possibility of compact, high density, ultrafast,all-electronic, low-energy devices, wh…

cond-mat.mtrl-sci2018

In aqua electrochemistry probed by XPEEM: experimental setup, examples, and challenges

Slavomír Nemšák, Evgheni Strelcov, Hongxuan Guo +8

Recent developments in environmental and liquid cells equipped with electron transparent graphene windows have enabled traditional surface science spectromicroscopy tools, such as…

cond-mat.mtrl-sci2017★ 47 cited

Stateful characterization of resistive switching TiO2 with electron beam induced currents

Brian D. Hoskins, Gina C. Adam, Evgheni Strelcov +4

Metal oxide resistive switches are increasingly important as possible artificial synapses in next generation neuromorphic networks. Nevertheless, there is still no codified set of…

cond-mat.mtrl-sci2014★ 61 cited

Phenomenological Modeling of Memristive Devices

Farnood Merrikh-Bayat, Brian Hoskins, Dmitri B. Strukov

We present a computationally inexpensive yet accurate phenomenological model of memristive behavior in titanium dioxide devices by fitting experimental data. By design, the model p…

cond-mat.mtrl-sci2011★ 504 cited

High-Precision Tuning of State for Memristive Devices by Adaptable Variation-Tolerant Algorithm

Fabien Alibart, Ligang Gao, Brian Hoskins +1

Using memristive properties common for the titanium dioxide thin film devices, we designed a simple write algorithm to tune device conductance at a specific bias point to 1% relati…