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Memristive-based in-memory computing: from device to large-scale CMOS integration

  • With the rapid emergence of in-memory computing systems based on memristive technology, the integration of such memory devices in large-scale architectures is one of the main aspects to tackle. In this work we present a study of HfO2-based memristive devices for their integration in large-scale CMOS systems, namely 200 mm wafers. The DC characteristics of single metal–insulator–metal devices are analyzed taking under consideration device-to-device variabilities and switching properties. Furthermore, the distribution of the leakage current levels in the pristine state of the samples are analyzed and correlated to the amount of formingless memristors found among the measured devices. Finally, the obtained results are fitted into a physic-based compact model that enables their integration into larger-scale simulation environments.

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Author: Emilio Perez-Bosch Quesada, Eduardo Perez, Mamathamba Kalishettyhalli Mahadevaiah, Christian WengerORCiD
DOI:https://doi.org/10.1088/2634-4386/ac2cd4
ISSN:2634-4386
Title of the source (English):Neuromorphic Computing and Engineering
Document Type:Scientific journal article peer-reviewed
Language:English
Year of publication:2021
Tag:HfO2; RRAM; memristive device
Volume/Year:1
Issue number:2
Number of pages:8
Article number:024006
Faculty/Chair:Fakultät 1 MINT - Mathematik, Informatik, Physik, Elektro- und Informationstechnik / FG Halbleitermaterialien
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