Robin Degraeve, A. Fantini, P. Roussel, L. Goux, A. Costantino, C. Y. Chen, S. Clima, B. Govoreanu, D. Linten, Aaron Thean, Malgorzata Jurczak
{"title":"细丝RRAM的定量耐久性失效模型","authors":"Robin Degraeve, A. Fantini, P. Roussel, L. Goux, A. Costantino, C. Y. Chen, S. Clima, B. Govoreanu, D. Linten, Aaron Thean, Malgorzata Jurczak","doi":"10.1109/VLSIT.2015.7223673","DOIUrl":null,"url":null,"abstract":"Endurance in filamentary RRAM is modeled in the framework of the hourglass model. Two failure modes are distinguished: (i) stochastic set failure is caused by defect generation near the bottom electrode, and (ii) resistive window changes are controlled by T-activated changes of the number of filament vacancies. Bottom electrode/oxide interface optimization is the prime knob for endurance improvement. This model enables quantitative and predictive endurance simulations.","PeriodicalId":181654,"journal":{"name":"2015 Symposium on VLSI Technology (VLSI Technology)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Quantitative endurance failure model for filamentary RRAM\",\"authors\":\"Robin Degraeve, A. Fantini, P. Roussel, L. Goux, A. Costantino, C. Y. Chen, S. Clima, B. Govoreanu, D. Linten, Aaron Thean, Malgorzata Jurczak\",\"doi\":\"10.1109/VLSIT.2015.7223673\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Endurance in filamentary RRAM is modeled in the framework of the hourglass model. Two failure modes are distinguished: (i) stochastic set failure is caused by defect generation near the bottom electrode, and (ii) resistive window changes are controlled by T-activated changes of the number of filament vacancies. Bottom electrode/oxide interface optimization is the prime knob for endurance improvement. This model enables quantitative and predictive endurance simulations.\",\"PeriodicalId\":181654,\"journal\":{\"name\":\"2015 Symposium on VLSI Technology (VLSI Technology)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Symposium on VLSI Technology (VLSI Technology)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VLSIT.2015.7223673\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Symposium on VLSI Technology (VLSI Technology)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VLSIT.2015.7223673","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Quantitative endurance failure model for filamentary RRAM
Endurance in filamentary RRAM is modeled in the framework of the hourglass model. Two failure modes are distinguished: (i) stochastic set failure is caused by defect generation near the bottom electrode, and (ii) resistive window changes are controlled by T-activated changes of the number of filament vacancies. Bottom electrode/oxide interface optimization is the prime knob for endurance improvement. This model enables quantitative and predictive endurance simulations.