journal article·2020-01

Multilayer Metal‐Oxide Memristive Device with Stabilized Resistive Switching

Alexey Mikhaylov, Alexey Belov, Dmitry Korolev, Ivan Antonov, Valentina Kotomina, Alina Kotina, Evgeny Gryaznov, Alexander Sharapov, Maria Koryazhkina, Ruslan Kryukov, Sergey Zubkov, Artem Sushkov, Dmitry Pavlov, Stanislav Tikhov, Oleg Morozov, David Tetelbaum

Advanced Materials Technologies· Volume 5· Issue 1
Publisher page

Abstract

Abstract Variability of resistive switching is a key problem for application of memristive devices in emerging information‐computing systems. Achieving a stable switching between the nonlinear resistive states is an important task on the way to implementation of large memristive cross‐bar arrays and solving the related sneak‐path‐current problem. A promising approach is the fabrication of memristive structures with appropriate interfaces by combining the materials of electrodes with certain oxygen affinity and different dielectric layers. In the present work, such approach allows the demonstration of stabilized resistive switching in a multilayer device structure based on ZrO2(Y) and Ta2O5 films. It is established for the large‐area devices that the switching is stabilized after several hundreds of cycles. A possible scenario of the stabilization is proposed taking into account experimental data on the presence of grain boundaries in ZrO2(Y) as the preferred sites for nucleation of filaments, self‐organization of Ta nanocrystals as the electric field concentrators in Ta2O5 film, as well as oxygen exchange between oxide layers and interface with bottom TiN electrode. The robust resistive switching between nonlinear states is implemented in microscale cross‐point devices without numerous cycling before stabilization promising for the fabrication of programmable memristive weights in passively integrated cross‐bar arrays.
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Research context

OpenAlex topics: Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Lobachevsky University 23/3 Gagarin Prospect Nizhny Novgorod 603950 Russia

Funding

Russian Science Foundation

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