{"title":"双阈值独立门FinFET和SRAM单元的综合优化","authors":"H. Ni, Jianping Hu, Huishan Yang, Haotian Zhu","doi":"10.1155/2018/4512924","DOIUrl":null,"url":null,"abstract":"Independent-Gate (IG) FinFET is a promising device in circuit applications due to its two separated gates, which can be used independently. In this paper, we proposed a comprehensive method to optimize the Dual Threshold (DT) IG FinFET devices by carrying out modulations for the gate electrode work function, oxide thickness, and silicon body thickness. Titanium nitride (TiNx) is used as the tunable work function gate electrode for good performances. The thicknesses of the gate oxide and silicon body are swept by TCAD simulations to obtain the appropriate values. The verification simulation of the optimized transistors shows that the DT IG FinFETs can realize merging parallel and series transistors, respectively, and the current characteristics of the transistors are improved significantly. By extracting the BSIM-IMG model parameters, we can simulate the circuits composed of the proposed DT IG FinFET by using HSPICE with BSIM-IMG model. As practical examples, we optimized two novel 7T SRAM cells using DT IG FinFETs. HSPICE simulation results indicate that the new SRAM cells obtain higher write margin and read static noise margin with lower leakage power consumption than the other implementations.","PeriodicalId":43355,"journal":{"name":"Active and Passive Electronic Components","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2018-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2018/4512924","citationCount":"5","resultStr":"{\"title\":\"Comprehensive Optimization of Dual Threshold Independent-Gate FinFET and SRAM Cells\",\"authors\":\"H. Ni, Jianping Hu, Huishan Yang, Haotian Zhu\",\"doi\":\"10.1155/2018/4512924\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Independent-Gate (IG) FinFET is a promising device in circuit applications due to its two separated gates, which can be used independently. In this paper, we proposed a comprehensive method to optimize the Dual Threshold (DT) IG FinFET devices by carrying out modulations for the gate electrode work function, oxide thickness, and silicon body thickness. Titanium nitride (TiNx) is used as the tunable work function gate electrode for good performances. The thicknesses of the gate oxide and silicon body are swept by TCAD simulations to obtain the appropriate values. The verification simulation of the optimized transistors shows that the DT IG FinFETs can realize merging parallel and series transistors, respectively, and the current characteristics of the transistors are improved significantly. By extracting the BSIM-IMG model parameters, we can simulate the circuits composed of the proposed DT IG FinFET by using HSPICE with BSIM-IMG model. As practical examples, we optimized two novel 7T SRAM cells using DT IG FinFETs. HSPICE simulation results indicate that the new SRAM cells obtain higher write margin and read static noise margin with lower leakage power consumption than the other implementations.\",\"PeriodicalId\":43355,\"journal\":{\"name\":\"Active and Passive Electronic Components\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2018-09-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1155/2018/4512924\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Active and Passive Electronic Components\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1155/2018/4512924\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Active and Passive Electronic Components","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2018/4512924","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Comprehensive Optimization of Dual Threshold Independent-Gate FinFET and SRAM Cells
Independent-Gate (IG) FinFET is a promising device in circuit applications due to its two separated gates, which can be used independently. In this paper, we proposed a comprehensive method to optimize the Dual Threshold (DT) IG FinFET devices by carrying out modulations for the gate electrode work function, oxide thickness, and silicon body thickness. Titanium nitride (TiNx) is used as the tunable work function gate electrode for good performances. The thicknesses of the gate oxide and silicon body are swept by TCAD simulations to obtain the appropriate values. The verification simulation of the optimized transistors shows that the DT IG FinFETs can realize merging parallel and series transistors, respectively, and the current characteristics of the transistors are improved significantly. By extracting the BSIM-IMG model parameters, we can simulate the circuits composed of the proposed DT IG FinFET by using HSPICE with BSIM-IMG model. As practical examples, we optimized two novel 7T SRAM cells using DT IG FinFETs. HSPICE simulation results indicate that the new SRAM cells obtain higher write margin and read static noise margin with lower leakage power consumption than the other implementations.
期刊介绍:
Active and Passive Electronic Components is an international journal devoted to the science and technology of all types of electronic components. The journal publishes experimental and theoretical papers on topics such as transistors, hybrid circuits, integrated circuits, MicroElectroMechanical Systems (MEMS), sensors, high frequency devices and circuits, power devices and circuits, non-volatile memory technologies such as ferroelectric and phase transition memories, and nano electronics devices and circuits.