Fully depleted silicon-on-insulator (FDSOI) technology nodes offer better single-event performance compared with comparable bulk technologies. However, upsets are still possible at nanoscale feature sizes and additional hardening techniques need to be explored. Single-event upset (SEU) performance of multiple flip-flop designs using the stacked-transistor hardening technique at a 22-nm FDSOI technology node is presented in this paper. Irradiation results show significant reductions in SEU cross-sections for stacked-transistor-based hardened designs compared to a conventional design. Alpha particle exposures showed zero upsets for all D-Flip-Flop (DFF) designs tested. When exposed to heavy-ions, the stacked-transistor DFF design showed a 17X improvement over a conventional DFF design at an LET value of 47 MeV-cm ² /mg. The stacked-transistor design with the charge-cancelling technique showed upsets when particle LET exceeded 93.8 MeV-cm ² /mg and at a high angle of incidence. The stacked-transistor design with the interleaving technique showed zero upsets for all test conditions.

Total ionizing dose (TID) effects from Co-60 gamma ray and heavy ion irradiation were studied at the 22-nm FD SOI technology node and compared with the testing results from the 28-nm FD SOI technology. Ring oscillators (RO) designed with inverters, NAND2, and NOR2 gates were used to observe the output frequency drift and current draw. Experimental results show a noticeable increased device current draw and decreases in RO frequencies where NOR2 ROs have the most degradation. As well, the functionality of a 256 kb SRAM block and shift-register chains were evaluated during C0-60 irradiation. SRAM functionality deteriorated at 325 krad(Si) of the total dosage, while the FF chains remained functional up to 1 Mrad(Si). Overall, the 22-nm FD SOI results show better resilience to TID effects compared to the 28-nm FD SOI technology node.

Because of the isolation of transistors, fully-depleted silicon-on-insulator (FDSOI) technology nodes have shown better single-event upset (SEU) resilience compared with bulk technology nodes. Additional radiation-hardening-by-design (RHBD) techniques can further improve the SEU performance. In this paper, SEU performance of multiple RHBD flip-flop (FF) designs using the guard-gate circuit at a 22-nm FDSOI technology is presented, including a conventional FF, a guard-gate (GG) FF, a dual-feedback-recovery (DFR) FF, and a GG-Dual-Interconnected Storage Cell (DICE) FF. Irradiation results showed significant reductions in SEU cross-sections for hardened designs compared to the conventional design. Specifically, the conventional GG design demonstrates more than 100X improvement over a conventional FF design, while DFR and GG-DICE designs showed no upsets for all test conditions. Further analysis was carried out to explain the SEU performance differences between the GG and DFR FF designs, and it is noted that proper layout arrangement is critical for achieving ideal SEU mitigation in this FDSOI technology node.

Fully Depleted Silicon on Insulator (FD SOI) technology nodes provide better resistance to single event upsets than comparable bulk technologies, but upsets are still likely to occur at nano-scale feature sizes, and additional hardening techniques should be explored. Three flip-flop designs were implemented using Dual Interlocked Cell (DICE) latches in a 22 m FD SOI technology node. Additional hardening was implemented in the layout of each design by using transistor spacing and interleaving. Comparisons were made between a standard DICE design and two other designs making use of the new Continuous Active (CnRx) Diffusion construct and guard-gate transistor stacking through alpha particle and heavy ion irradiation. Designs making use of the CnRx construct for performance improvements were more likely to experience upsets due to higher collected charges in the increased diffusion regions. Conversely, transistor stacking showed strong soft error rate resilience because of the natural isolation between transistors in the FD SOI technology. Overall, the efficacy of transistor interleaving in flip-flops using DICE latches was found to be extremely robust in the 22 nm FD SOI technology node.

In this brief, we propose a pipeline for machine learning on CMOS Oscillator Networks (OscNet), inspired by human visual system development. By relying solely on forward propagation, OscNet is energy efficient and preserves biological plausibility. Our simulations confirm the effectiveness of the proposed architectures, and experimental results demonstrate that the Hebbian-learning pipeline on OscNet matches traditional machine learning algorithms, underscoring its promise as an energy efficient and high performance new computational paradigm. The repository for OscNet family is:.

Embedded Silicon Germanium (eSiGe) is used in the channel region of PFET devices at the 22-nm FD SOI node. The use of eSiGe results in channel regions becoming strained, which results in better hole mobility and increased performance. However, if the active diffusion regions are too short on each side of a PFET gate, then the effect of channel strain is reduced, and performance is reduced. The Continuous Active Diffusion (CnRx) layout construct suggested by the foundry is a way to help keep channel strain present within a single cell design. In this paper the CnRx construct is implemented in a 22-nm FD SOI test chip and soft error rates of stacked-transistor flip-flops are shown to increase with heavy ion irradiation. The effect of channel strain on PFETs results in higher collected charges from ion strikes, and charges are more easily passed between adjacent transistors through strained channels. However, with careful schematic and layout design, these effects can be mitigated to produce both high performance and radiation tolerant cells using the CnRx construct.