Evaluation of a Simplified Modeling Approach for SEE Cross-Section Prediction: A Case Study of SEU on 6T SRAM Cells
Author:
Affiliation:
1. IES, UMR-CNRS 5214, University of Montpellier, 34090 Montpellier, France
2. CERN, CH-1211 Genève, Switzerland
Abstract
Funder
European Union’s Horizon 2020 research and innovation program
Publisher
MDPI AG
Link
https://www.mdpi.com/2079-9292/13/10/1954/pdf
Reference35 articles.
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3. An SRAM SEU Cross Section Curve Physics Model;Kobayashi;IEEE Trans. Nucl. Sci.,2022
4. Heavy Ion SEU Cross Section Calculation Based on Proton Experimental Data, and Vice Versa;Wrobel;IEEE Trans. Nucl. Sci.,2014
5. Narasimham, B., Gupta, S., Reed, D., Wang, J.K., Hendrickson, N., and Taufique, H. (2018, January 11–15). Scaling trends and bias dependence of the soft error rate of 16 nm and 7 nm FinFET SRAMs. Proceedings of the 2018 IEEE International Reliability Physics Symposium (IRPS), Burlingame, CA, USA.
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