This paper compares different types of resistive defects that may occur inside low-power SRAM cells, focusing on their impact on device operation. Notwithstanding the continuous evolution of SRAM device integration, manufacturing processes continue to be very sensitive to production faults, giving rise to defects that can be modeled as resistances, especially for devices designed to work in low-power modes. This work analyzes this type of resistive defect that may impair the device functionalities in subtle ways, depending on the defect characteristics and values that may not be directly or easily detectable by traditional test methods. We analyze each defect in terms of the possible effects inside the SRAM cell, its impact on power consumption, and provide guidelines for selecting the best test methods.

An Experimental Evaluation of Resistive Defects and Different Testing Solutions in Low-Power Back-Biased SRAM Cells / Mirabella, N.; Grosso, M.; Franchino, G.; Rinaudo, S.; Deretzis, I.; La Magna, A.; Reorda, M. S.. - In: ELECTRONICS. - ISSN 2079-9292. - ELETTRONICO. - 11:2(2022), p. 203. [10.3390/electronics11020203]

An Experimental Evaluation of Resistive Defects and Different Testing Solutions in Low-Power Back-Biased SRAM Cells

Mirabella N.;Grosso M.;Reorda M. S.
2022

Abstract

This paper compares different types of resistive defects that may occur inside low-power SRAM cells, focusing on their impact on device operation. Notwithstanding the continuous evolution of SRAM device integration, manufacturing processes continue to be very sensitive to production faults, giving rise to defects that can be modeled as resistances, especially for devices designed to work in low-power modes. This work analyzes this type of resistive defect that may impair the device functionalities in subtle ways, depending on the defect characteristics and values that may not be directly or easily detectable by traditional test methods. We analyze each defect in terms of the possible effects inside the SRAM cell, its impact on power consumption, and provide guidelines for selecting the best test methods.
2022
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2960559