R. W. Ahmad, Rainer Waser, Florian Maudet, Onur Toprak, Catherine Dubourdieu, S. Menzel
{"title":"Variability-aware modelling of electrochemical metallization memory cells","authors":"R. W. Ahmad, Rainer Waser, Florian Maudet, Onur Toprak, Catherine Dubourdieu, S. Menzel","doi":"10.1088/2634-4386/ad57e7","DOIUrl":null,"url":null,"abstract":"\n Resistively switching electrochemical metallization memory (ECM) cells are gaining huge interest, as they are seen as promising candidates and basic building blocks of future computation-in-memory applications. However, especially filamentary-based memristive devices suffer from inherent variability, originating from their stochastic switching behaviour. A variability-aware compact model of Electrochemical Metallization Memory Cells is presented in this work and verified by showing a fit to experimental data. It is an extension of a deterministic model. As this extension consists of several different features allowing for a realistic variability-aware fit, it depicts a unique model comprising physics-based, stochastically and experimentally originating variabilities and reproduces them well. Also, a physics-based model parameter study is executed, which enables a comprehensive view into the device physics and presents guidelines for the compact model fitting procedure.","PeriodicalId":198030,"journal":{"name":"Neuromorphic Computing and Engineering","volume":"54 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuromorphic Computing and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1088/2634-4386/ad57e7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Resistively switching electrochemical metallization memory (ECM) cells are gaining huge interest, as they are seen as promising candidates and basic building blocks of future computation-in-memory applications. However, especially filamentary-based memristive devices suffer from inherent variability, originating from their stochastic switching behaviour. A variability-aware compact model of Electrochemical Metallization Memory Cells is presented in this work and verified by showing a fit to experimental data. It is an extension of a deterministic model. As this extension consists of several different features allowing for a realistic variability-aware fit, it depicts a unique model comprising physics-based, stochastically and experimentally originating variabilities and reproduces them well. Also, a physics-based model parameter study is executed, which enables a comprehensive view into the device physics and presents guidelines for the compact model fitting procedure.