Enhancement in Retention Time of 3TDRAM Using Double Gate Finfet Technology at Nanometer Regime.
Bibliographic record
Abstract
Leakage current, power and area is the key challenges for VLSI designer during implementation of low power devices. In an integrated circuit number of transistors double in small silicon area every two years. There are certain limitations of cmos technology in nanometer regime out of which leakage current, leakage power, average current and average power is an important issues. In this paper, Retention time improvement in three transistor dynamic random access memory using double gate Finfet technology is proposed. Double gate finfet technology in 3TDRAM overcomes the issues related to cmos technology and it does not required additional circuitry. Proposed 3T DRAM is investigated with cmos and finfet technology at 90nm technology using cadence tool. Analysis of 3TDRAM using cmos and double gate finfet technology is carried out by variation in supply voltage and capacitance values. In double gate finfet technology leakage parameters are minimized and retention time(Th) is more improved as compared to cmos technology is observed.
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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) | 0.002 | 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".