Non-monotonic probability of thermal reversal in thin-film biaxial nanomagnets with small energy barriers
Source abstract
Abstract
The goal of this paper is to investigate the short time-scale, thermally-induced probability of magnetization reversal for an biaxial nanomagnet that is characterized with a biaxial magnetic anisotropy. For the first time, we clearly show that for a given energy barrier of the nanomagnet, the magnetization reversal probability of an biaxial nanomagnet exhibits a non-monotonic dependence on its saturation magnetization. Specifically, there are two reasons for this non-monotonic behavior in rectangular thin-film nanomagnets that have a large perpendicular magnetic anisotropy. First, a large perpendicular anisotropy lowers the precessional period of the magnetization making it more likely to precess across the x^=0 plane if the magnetization energy exceeds the energy barrier. Second, the thermal-field torque at a particular energy increases as the magnitude of the perpendicular anisotropy increases during the magnetization precession. This non-monotonic behavior is most noticeable when analyzing the magnetization reversals on time-scales up to several tens of ns. In light of the several proposals of spintronic devices that require data retention on time-scales up to 10’s of ns, understanding the probability of magnetization reversal on the short time-scales is important. As such, the results presented in this paper will be helpful in quantifying the reliability and noise sensitivity of spintronic devices in which thermal noise is inevitably present.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Magnetic properties of thin films · Magnetic Properties and Applications · Characterization and Applications of Magnetic Nanoparticles
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Georgia Institute of Technology 1 Electrical and Computer Engineering, , Atlanta, Georgia 30318, USA
New York University 2 Electrical and Computer Engineering, , Brooklyn, New York 11201, USA
Funding
Semiconductor Research Corporation
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Show source-provided references
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