Device Aware Diagnosis for Unique Defects in STT-MRAMs

Ahmed Aouichi, Sicong Yuan, Moritz Fieback, Siddharth Rao, Woojin Kim, Erik Jan Marinissen, Sebastien Couet, Mottaqiallah Taouil, Said Hamdioui

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review


Spin-Transfer Torque Magnetic RAMs (STT-MRAMs) are on their way to commercialization. However, obtaining high-quality test and diagnosis solutions for STT-MRAMs is challenging due to the existence of unique defects in Magnetic Tunneling Junctions (MTJs). Recently, the Device-Aware Test (DA-Test) method has been put forward as an effective approach mainly for detecting unique defecting STT-MRAMs. In this study, we propose a further advancement based on the DA-Test framework, introducing the Device-Aware Diagnosis (DA-Diagnosis) method. This method comprises two steps: a) defining distinctive features of each unique defect by characterization and physical analysis of defective MTJs, and b) utilizing march algorithms to extract distinctive features. The effectiveness of the proposed approach is validated in an industrial setting with real devices and data measurement.

Original languageEnglish
Title of host publicationProceedings of the 2023 IEEE 32nd Asian Test Symposium, ATS 2023
Number of pages6
ISBN (Electronic)9798350303100
Publication statusPublished - 2023
Event32nd IEEE Asian Test Symposium, ATS 2023 - Beijing, China
Duration: 14 Oct 202317 Oct 2023

Publication series

NameProceedings of the Asian Test Symposium
ISSN (Print)1081-7735


Conference32nd IEEE Asian Test Symposium, ATS 2023


  • device-aware method
  • diagnosis
  • test
  • unique defect


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