A Simulation Approach to Analyze Bridge-Defects in a 6T-SRAM Bit Cell

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A Simulation Approach to Analyze Bridge-Defects in a 6T-SRAM Bit Cell
Title:
A Simulation Approach to Analyze Bridge-Defects in a 6T-SRAM Bit Cell
Journal Title:
2022 6th IEEE Electron Devices Technology Manufacturing Conference (EDTM)
Publication Date:
21 June 2022
Citation:
Ghosh, J., Lim, S. Y., Meftahul, F. Md., Jayavelu, S., & Thean, A. V.Y. (2022). A Simulation Approach to Analyze Bridge-Defects in a 6T-SRAM Bit Cell. 2022 6th IEEE Electron Devices Technology & Manufacturing Conference (EDTM). https://doi.org/10.1109/edtm53872.2022.9798365
Abstract:
The modern semiconductor technology node causes several failure analysis challenges of the current industry-standard tools to locate the physical defects. Here we discuss such defects in a 6T-SRAM cell. We combine bridge-defect modeling with SPICE simulations and machine learning technique for detect predictions across a node pair. We employ supervised learning algorithm trained with the measurable electrical attributes of the circuit to predict defect location. Then, we utilize t-distributed stochastic neighbor embedding (t-SNE) technique to visualize the multi-dimensional data and interpret how several defect clusters behave. Our approach promises to improve the failure analysis in integrated circuits, enhancing the cycle of design to product.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the A*STAR - Accelerated Materials Development for Manufacturing Program (AME Programmatic Fund)
Grant Reference no. : A1898b0043
Description:
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
ISBN:
978-1-6654-2179-9
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