Supply Voltage Dependence of Heavy Ion Induced SEEs on 65 nm CMOS Bulk SRAMs
Bibliographic record
Abstract
Soft Error Rates (SER) of hardened and unhardened SRAM cells need to be experimentally characterized to determine their appropriate applications in radiation environments. This characterization is especially important when low supply voltage is preferred. In this paper, we developed an SRAM test chip with four cell arrays including two types of unhardened cells (standard 6T and subthreshold 10T) and two types of hardened cells (Quatro and DICE). This test chip was fabricated in a 65 nm bulk technology and irradiated by heavy ions at different supply voltages. Experimental results show that the SERs of 6T and 10T cells present significant sensitivities to supply voltages when the particle linear energy transfers (LETs) are relatively low. For Quatro and DICE cells, one does not consistently show superior hardening performance over the other. It is also noted that Quatro cells show significant advantage in single event resilience over 10T cells although they consume similar areas. TCAD simulations were carried out to validate the experimental data. In addition, the error amount distributions follow a Poisson distribution very well for each type of cell array.
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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) | 0.002 | 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".