Observation of Self-heating Process in STT-MRAM and Its Implication in Device Operations

In this study, we first report the observation of the self- heating process in STT-MRAM using the electrical characterization technique with a temporal resolution better than 500 ps. The results confirm that at room temperature (300 K), the time constants for both heating and cooling during the write operation are smaller than 10 ns and the temperature increase of the Magnetic Tunnel Junction (MTJ) due to the self-heating effect (SHE) exceeds 75 K. Furthermore, the thermal resistance of the MTJ was experimentally extracted for the first time through electrical characterizations, which is crucial for accurately modeling the performance of MRAM.

Authors

Institutions

Publication Details

Published
2025-03-30
DOI
https://doi.org/10.1109/irps48204.2025.10982942
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Observation of Self-heating Process in STT-MRAM and Its Implication in Device Operations

Ming Wang, Shifan Gao, Zhangsheng Lan, Yi Wei et al.
1 links
Advanced machining processes and optimization
article

Observation of Self-heating Process in STT-MRAM and Its Implication in Device Operations

Ming Wang, Shifan Gao, Zhangsheng Lan, Yi Wei, Wenchao Yan, Xiaolei Yang, Yiming Qu, Yuhao Chen, Yi Zhao, Shikun He
article en

Abstract

In this study, we first report the observation of the self- heating process in STT-MRAM using the electrical characterization technique with a temporal resolution better than 500 ps. The results confirm that at room temperature (300 K), the time constants for both heating and cooling during the write operation are smaller than 10 ns and the temperature increase of the Magnetic Tunnel Junction (MTJ) due to the self-heating effect (SHE) exceeds 75 K. Furthermore, the thermal resistance of the MTJ was experimentally extracted for the first time through electrical characterizations, which is crucial for accurately modeling the performance of MRAM.

East China Normal University (CN), Zhejiang University (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 90%
Advanced machining processes and optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.