Demonstration of highly scaled FinFET SRAM cells with high-κ/metal gate and investigation of characteristic variability for the 32 nm node and beyond
Bibliographic record
Abstract
Highly scaled FinFET SRAM cells, of area down to 0.128 m2, were fabricated using high-kappa dielectric and a single metal gate to demonstrate cell size scalability and to investigate Vtvariability for the 32 nm node and beyond. A single-sided ion implantation (I/I) scheme was proposed to reduce Vtvariation of Fin-FETs in a SRAM cell, where resist shadowing is a great issue. In the 0.187 m2cell, at Vd= 0.6 V, a static noise margin (SNM) of 95 mV was obtained and stable read/write operations were verified from N-curve measurements. sigmaVtof transistors in 0.187 m2cells was measured with and without channel doping and the result was summarized in the Pelgrom plot. With the 22 nm node design rule, FinFET SRAM cell layouts were compared against planar-FET SRAM cell layouts. An un-doped FinFET SRAM cell was simulated to have significant advantage in read/write margin over a planar-FET SRAM cell, which would have higher sigmaVtmainly caused by heavy doping into the channel region.
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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 | 0.000 |
| 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".