A. Michez, J. Boch, J. Dardié, F. Wrobel, A. Touboul, T. Maraine, F. Saigné, E. Lorfèvre, F. Bezerra
{"title":"TCAD prediction of dose effects on MOSFETs with ECORCE","authors":"A. Michez, J. Boch, J. Dardié, F. Wrobel, A. Touboul, T. Maraine, F. Saigné, E. Lorfèvre, F. Bezerra","doi":"10.1109/RADECS.2017.8696230","DOIUrl":null,"url":null,"abstract":"Response to Total Ionizing Dose of a component varies widely depending on applied bias, temperature and dose rate. Thus testing a component that will be used in radiative environment implies to experimentally check all the combinations of these parameters that will be encountered during the mission. To ease this operation, we propose to build a TCAD model from a reduce set of experiments, and then use this model to predict the behavior of components whatever the bias, the temperature, the total dose and the dose rate is, even if the value has not been tested experimentally.","PeriodicalId":223580,"journal":{"name":"2017 17th European Conference on Radiation and Its Effects on Components and Systems (RADECS)","volume":"153 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 17th European Conference on Radiation and Its Effects on Components and Systems (RADECS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADECS.2017.8696230","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Response to Total Ionizing Dose of a component varies widely depending on applied bias, temperature and dose rate. Thus testing a component that will be used in radiative environment implies to experimentally check all the combinations of these parameters that will be encountered during the mission. To ease this operation, we propose to build a TCAD model from a reduce set of experiments, and then use this model to predict the behavior of components whatever the bias, the temperature, the total dose and the dose rate is, even if the value has not been tested experimentally.