Research of Memristor Effect in Crossbar Architecture for Neuromorphic Artificial Intelligence Systems

V. V. Polyakova; Полякова В. В.; A. V. Saenko; Саенко А. В.; I. N. Kots; Коц И. Н.; A. V. Kovalev; Ковалев А. В.

doi:10.31857/S0544126924010069

Research of Memristor Effect in Crossbar Architecture for Neuromorphic Artificial Intelligence Systems

Autores: Polyakova V.V.¹, Saenko A.V.¹, Kots I.N.¹, Kovalev A.V.¹
Afiliações:
1. Southern Federal University
Edição: Volume 53, Nº 1 (2024)
Páginas: 58-63
Seção: ПРИБОРЫ
URL: https://j-morphology.com/0544-1269/article/view/655246
DOI: https://doi.org/10.31857/S0544126924010069
ID: 655246

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Resumo

This article presents the results of experimental studies of structures formed on the basis of the crossbar architecture of memristor structures made of various materials. TiO₂ was used as a working memristor layer. The following materials were used for the contact pads: Al, Ni, Cr, Mo, Ta, Ag. In the course of experimental studies, the optimal combination of materials for the formation of crossbar memristor structures was revealed, which in the future can be used in devices of neuromorphic artificial intelligence systems.

Palavras-chave

memristor, crossbar architecture, neuromorphic systems, magnetron sputtering, atomic force microscopy

Bibliografia

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Polyakova V.V., Saenko A.V. Local Anodic Oxidation for Crossbar-Array Architecture Technical Physics. 2022. V. 92. No. 8. Р. 1159–1165.
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