Analysis of parameter variation impact on the single event response in sub-100nm CMOS storage cells
Kauppila, Amy Vaughn
Current deep sub-micron technologies are particularly susceptible to single events. The challenge derives from a conglomeration of effects that affect circuits’ radiation response. For instance, decreasing device size has led to decreased storage charge and increased operating speeds. Decreased storage charge contributes to single event sensitivity since the charge deposited by the ionized particle is now more on par with the storage node charge. The increased operating speeds increase circuit sensitivity since they are now comparable to the speed of a single event transient. Single events are expected to dominate other reliability concerns in deep sub-micrometer devices due to decreased transistor currents and nodal capacitances. Thus, it is vital to understand and quantify the impact of contributing mechanisms. In addition to the challenges presented by radiation, transistor and chip design also faces a challenge from the variations that are inherent to the manufacturing process. During chip fabrication, extreme measures are taken to ensure precision. However, variations in lithography, random dopant fluctuations, gate depletion, surface state charge, and line-edge roughness cause changes in individual transistor behavior and therefore, changes in the behavior-describing transistor parameters. The non-standard behavior then affects circuit performance and therefore impacts single event response. It is anticipated that process variations will substantially increase with shrinking device sizes. Consequently, the potential impact of process variations on SE circuit response is significant. In order to accurately predict the single-event response of any circuit, it is necessary to identify and quantify the impact of the specific process variations. This work correlates the shifts in radiation response to specific device and process-parameter variations by quantifying the impact of process variability on the range of single-event upset (SEU) critical charge. Monte-Carlo simulations are leveraged to assess the impact of process variations on SEU response. This dissertation analyzes the impact of process variations on the single-event upset response of sub-100nm CMOS memory storage circuits.