Impact of CnRx Structure on Soft Error Rates of Flip-Flop Designs at 22-nm FD SOI Node
Bibliographic record
Abstract
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 article, the CnRx construct is implemented in a 22-nm FD SOI test chip and soft error rates (SER) of stacked-transistor flip-flops (FFs) 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".