R. W. Ahmad, Rainer Waser, Florian Maudet, Onur Toprak, Catherine Dubourdieu, S. Menzel
{"title":"电化学金属化记忆电池的变异感知建模","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":"{\"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}","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}
Variability-aware modelling of electrochemical metallization memory cells
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.