Dong Keun Lee, Min-Hwi Kim, Suhyun Bang, Tae-Hyeon Kim, Yeon-Joon Choi, Sungjun Kim, Seongjae Cho, Byung-Gook Park
{"title":"Comparison of switching characteristics of HfOx RRAM device with different switching layer thicknesses","authors":"Dong Keun Lee, Min-Hwi Kim, Suhyun Bang, Tae-Hyeon Kim, Yeon-Joon Choi, Sungjun Kim, Seongjae Cho, Byung-Gook Park","doi":"10.23919/SNW.2019.8782952","DOIUrl":null,"url":null,"abstract":"This paper presents switching characteristics of Ni/HfOx/p+-Si with different switching layer thicknesses (5/10 nm) in DC mode. Larger forming voltage and on/off ratio is obtained from the 10 nm HfOx RRAM while step-like reset process is seen from 5 nm HfOx RRAM. From the measurement results, fabricated RRAM device with thicker switching layer is more suitable for nonvolatile memory operation while thinner HfOx layer has potential for application in neuromorphic computing system.","PeriodicalId":170513,"journal":{"name":"2019 Silicon Nanoelectronics Workshop (SNW)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Silicon Nanoelectronics Workshop (SNW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/SNW.2019.8782952","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
This paper presents switching characteristics of Ni/HfOx/p+-Si with different switching layer thicknesses (5/10 nm) in DC mode. Larger forming voltage and on/off ratio is obtained from the 10 nm HfOx RRAM while step-like reset process is seen from 5 nm HfOx RRAM. From the measurement results, fabricated RRAM device with thicker switching layer is more suitable for nonvolatile memory operation while thinner HfOx layer has potential for application in neuromorphic computing system.