{"title":"Modeling of stochastic BTI in small area devices and its impact on SRAM performance","authors":"T. Naphade, S. Mahapatra","doi":"10.1109/SBMICRO.2014.6940078","DOIUrl":"https://doi.org/10.1109/SBMICRO.2014.6940078","url":null,"abstract":"A comprehensive framework is developed to simulate device-level variability due to process variations and Bias Temperature Instability (BTI), and study the impact on circuits such as the SRAM cell. Stochastic simulation approach consisting of the stochastic Reaction Diffusion (RD) model for interface trap generation and stochastic two energy well model for charging of pre-existing bulk traps along with either simple exponential impact assumption or complete 3D TCAD simulation, is used to generate threshold voltage and threshold voltage shift distributions. A compact model approach to generate the threshold voltage distributions from the mean compact model through a procedure that exploits experimental relationship between mean and variance of threshold voltage shift distribution is described. The impact of device-level variability on the 6T-SRAM cell read and write operations is investigated.","PeriodicalId":244987,"journal":{"name":"2014 29th Symposium on Microelectronics Technology and Devices (SBMicro)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131617110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. A. Cotta, Omar P. Vilela Neto, Fernando C. da Silva Coelho
{"title":"Genetic Algorithm applied to the optimized project of semiconductor microcavity lasers","authors":"E. A. Cotta, Omar P. Vilela Neto, Fernando C. da Silva Coelho","doi":"10.1109/SBMICRO.2014.6940103","DOIUrl":"https://doi.org/10.1109/SBMICRO.2014.6940103","url":null,"abstract":"The application of new computational tools to design optimized devices is an important opportunity to minimize resources for its production. Moreover, these tools can ensure the correct operation of the devices, reaching its operating limit. In this paper we present the first quantitative study of parameters optimization for semiconductor microcavities synthesis under uncertainty using a genetic algorithm. These structures have been used in important studies of several areas for technological or purely scientific purposes. However, the definition of the optimal set of parameters for the fabrication of microcavities is a difficult task. Thus, the device can present different properties from those desired. Based on the reflectance spectra of a AlxGa1-xAs semiconductor microcavity, our goal is to find the optimal parameter set (aluminum concentrations x, thickness and the number of the layers). This set of parameters may offer increased robustness in the growth process, while providing a considerable Quality Factor and the desired position of the cavity resonance. The results indicate that the proposed algorithm is able to find satisfactory solutions by minimizing the problems caused by inaccuracy in the growth of these devices.","PeriodicalId":244987,"journal":{"name":"2014 29th Symposium on Microelectronics Technology and Devices (SBMicro)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129040433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}