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The impact of process induced variation on the response of SOI Fin FET to heavy ion irradiation is studied through 3-D TCAD simulation for the first time. When Fin FET biased at OFF state configuration(Vgs D0, Vds DVdd/ is struck by a heavy ion, the drain collects ionizing charges under the electric field and a current pulse(single event transient, SET) is consequently formed. The results reveal that with the presence of line-edge roughness(LER), which is one of the major variation sources in nano-scale Fin FETs, the device-to-device variation in terms of SET is observed. In this study, three types of LER are considered: type A has symmetric fin edges, type B has irrelevant fin edges and type C has parallel fin edges. The results show that type A devices have the largest SET variation while type C devices have the smallest variation. Further, the impact of the two main LER parameters,correlation length and root mean square amplitude, on SET variation is discussed as well. The results indicate that variation may be a concern in radiation effects with the down scaling of feature size.
The impact of process induced variation on the response of SOI Fin FET to heavy ion irradiation is studied through 3-D TCAD simulation for the first time. When Fin FET biased at OFF state configuration (Vgs D0, Vds DVdd / is struck by a heavy ion, the drain collects ionizing charges under the electric field and a current pulse (single event transient, SET) is due formed. The results reveal that with the presence of line-edge roughness (LER), which is one of the major variation sources in this study, three types of LER are considered: type A has symmetrical fin edges, type B has irrelevant fin edges and type C has parallel The results show that type A device have the largest SET variation while type C devices have the smallest variation. Further, the impact of the two main LER parameters, correlation length and root mean square amplitude, on SET variation is discussed as well The results i ndicate that variation may be a concern in radiation effects with the down scaling of feature size.