<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>27968</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>8</pageNumber>
    <edition/>
    <issue>2</issue>
    <volume>1</volume>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2021-11-18</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Memristive-based in-memory computing: from device to large-scale CMOS integration</title>
    <abstract language="eng">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.&#13;
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&#13;
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&#13;
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&#13;
enables their integration into larger-scale simulation environments.</abstract>
    <parentTitle language="eng">Neuromorphic Computing and Engineering</parentTitle>
    <identifier type="issn">2634-4386</identifier>
    <identifier type="doi">10.1088/2634-4386/ac2cd4</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="Artikelnummer">024006</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Emilio</firstName>
      <lastName>Perez-Bosch Quesada</lastName>
    </author>
    <submitter>
      <firstName>Christian</firstName>
      <lastName>Wenger</lastName>
    </submitter>
    <author>
      <firstName>Eduardo</firstName>
      <lastName>Pérez</lastName>
    </author>
    <author>
      <firstName>Mamathamba Kalishettyhalli</firstName>
      <lastName>Mahadevaiah</lastName>
    </author>
    <author>
      <firstName>Christian</firstName>
      <lastName>Wenger</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>RRAM</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>memristive device</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>HfO2</value>
    </subject>
    <collection role="institutes" number="1521">FG Halbleitermaterialien</collection>
  </doc>
</export-example>
