Statistical simulation of self-heating induced variability and reliability with application to Nanosheet-FETs based SRAM

• Autores: Wangyong Chen, Linlin Cai, Kunliang Wang, Xing Zhang, Xiaoyan Liu, Gang Du
• Localización: Microelectronics reliability, ISSN 0026-2714, Nº. 98, 2019, págs. 63-68
• Idioma: inglés
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• Resumen

  • We propose a new methodology to analyze self-heating induced variability and reliability in digital circuits during random operation. The arbitrary power waveform (APW) self-heating model is used for the self-heating evaluation with the input sequences generated by the power waveform generator (PWG). Based on the proposed method, the variability and HCI as well as BTI degradation correlated with self-heating effect (SHE) in Nanosheet-FETs based SRAM are investigated. It reveals that reducing the bit-line capacitance (CBL) and the minimum differential voltage between bit lines (ΔVBLBMIN) can suppress SHE and the temperature variation during operation of SRAM. The results also show that it is essential to take the self-heating variation into account for circuit design and reliability prediction.