Standby magnetic immunity calculator for STT-MRAM
Source abstract
Abstract
This work investigates the impact of external magnetic fields, field orientation, temperature, and exposure time on the standby magnetic immunity (SMI) of spin-transfer torque magnetoresistive random-access memory. Wafer-level measurements were performed using a 3D vector magnet, ensuring uniform magnetic fields on unpackaged and unshielded wafers. The analytical model, used to predict the SMI safety field for long-term exposure, has been validated against hardware data and micromagnetic simulations. Furthermore, we introduce a machine-learning-based SMI calculator that provides a fast, automated estimation of the safety field for complex mission profiles. This approach bridges physics-based modeling and data-driven prediction, providing a practical tool for estimating the SMI of MRAM for automotive and other safety-critical environments.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Magnetic Field Sensors Techniques · Magnetic properties of thin films · Magnetic Properties and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
GlobalFoundries 1 , Wilschdorfer Landstraße 101, 01109 Dresden,
GlobalFoundries 2 , 400 Stone Break Rd Extension, Malta, New York 12020,
References (27)
Show source-provided references
1. 2024 · 1
2. 2019 · 2
3. 2019 · 2
4. 2019 · 1
5. 2021 · 1
6. AIP Adv. · 2016 · 6 · 07501410.1063/1.4959593 ↗
7. 2020 · 1
8. 2018 · 1
9. IEEE Trans. Magn. · 2020 · 56 · 340041110.1109/tmag.2020.3028045 ↗
10. 2020 · 222
11. IEEE Electron Devices Mag. · 2024 · 2 · 5210.1109/med.2024.3442086 ↗
12. IEEE Trans. Magn. · 2025 · 61 · 340120610.1109/tmag.2025.3558542 ↗
13. 2018 · 349
14. See https://www.everspin.com/ for Everspin Technologies.
15. Nat. Electron. · 2021 · 4 · 39210.1038/s41928-021-00593-x ↗
16. Appl. Phys. Lett. · 2019 · 114 · 17240510.1063/1.5094482 ↗
17. AIP Adv. · 2023 · 13 · 02523210.1063/9.0000521 ↗
18. Phys. Rev. B · 2007 · 75 · 17443010.1103/physrevb.75.174430 ↗
19. Phys. Rev. Appl. · 2018 · 9 · 06402710.1103/physrevapplied.9.064027 ↗
20. Technology cad and machine learning: A new paradigm for semiconductor technology development
21. TCAD-enabled machine learning—An efficient framework to build highly accurate and reliable models for semiconductor technology development and fabrication10.1109/tsm.2023.3240033 ↗
22. J. Magn. Magn Mater. · 2013 · 345 · 2910.1016/j.jmmm.2013.05.051 ↗
23. IEEE Trans. Elect. Dev. · 2024 · 71 · 188610.1109/TED.2024.3354695 ↗
24. J. Appl. Phys. · 2013 · 114 · 22390110.1063/1.4839895 ↗
25. 2020 · 1
26. 2020 · 1
27. IEEE Elect. Dev. Lett. · 2025 · 46 · 19110.1109/LED.2024.3513954 ↗