4.4 Article

Performance analysis and yield estimation for a negative capacitance field effect transistor-based eight-transistor static random access memory

Journal

SEMICONDUCTOR SCIENCE AND TECHNOLOGY
Volume 36, Issue 9, Pages -

Publisher

IOP Publishing Ltd
DOI: 10.1088/1361-6641/ac0d99

Keywords

negative capacitance field effect transistor; static random access memory; variation; sensitivity analysis; cell sigma; yield estimation

Funding

  1. National Research Foundation of Korea (NRF) - Korean government [2020M3F3A2A01081672, 2020M3F3A2A01082326, 2020M3F3A2A02082473]
  2. Future Semiconductor Device Technology Development Program - Ministry of Trade, Industry and Energy (MOTIE) [10067746]
  3. Korea Semiconductor Research Consortium (KSRC)
  4. IC Design Education Center (IDEC), Korea
  5. National Research Foundation of Korea [2020M3F3A2A01082326, 2020M3F3A2A01081672] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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The study quantitatively evaluates the read/write performance and yield of an 8-T SRAM using NCFET, comparing it with a conventional 8-T SRAM. The sensitivity of the 8-T SRAM cell to read/write metrics is estimated by quantitatively evaluating the impact of systematic variations, and quantitative yield estimation is done using the 'cell sigma' concept. Finally, the minimum power supply voltage (V (DD)) for yield estimation of the NCFET-based/baseline 8-T SRAM cell is quantitatively estimated.
The read/write performance and yield of a negative capacitance field effect transistor (NCFET)-based eight-transistor (8-T) static random access memory (SRAM) are quantitatively evaluated and then compared with a conventional 8-T SRAM. The performance of the 8-T SRAM cell is analyzed by read/write metrics (i.e. read static noise margin, write-ability current and read 'zero (0)' current). The sensitivity of the 8-T SRAM cell to the read/write metric is estimated by quantitatively evaluating the impact of systematic variation (i.e. channel width, length and threshold voltage variation). Based on variation-aware sensitivity analysis, quantitative yield estimation is done using the 'cell sigma' concept. Finally, the minimum power supply voltage (V (DD)) (which satisfies six cell sigma for yield estimation of a NCFET-based/baseline 8-T SRAM cell) is quantitatively estimated.

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