FORC+ analysis of perpendicular magnetic tunnel junctions

Abugri, Joseph B.; Visscher, P. B.; Gupta, Subhadra; Chen, P. J.; Shull, Robert D.

doi:10.1063/1.5031786

Cited by 10 publications

(6 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Above -5 kOe the positive density is clearly on the right and it is not noise.] We have observed this also in an MTJ (magnetic tunnel junction) stack 16 , and refer to it as "holdout bias"a few unreversed grains, too small to affect the hysteresis loop (but perhaps visible in the lower right inset in Fig. 2), refuse to switch until about -5 kOe, and change (bias) the field at which the film switches back because they provide nuclei for the back-switching.…”

Section: Switching Mechanism: Forc and Mfmmentioning

confidence: 84%

MFM and first order reversal curve (FORC) study of switching mechanism in Co25Pd75 films

Abugri

Clark

Visscher

et al. 2019

Journal of Applied Physics

Self Cite

View full text Add to dashboard Cite

Recent research on CoPd alloys with perpendicular magnetic anisotropy (PMA) has suggested that they might be useful as the pinning layer in CoFeB/MgO-based perpendicular magnetic tunnel junctions (pMTJ's) for various spintronic applications such as spin-torque transfer random access memory (STT-RAM). We have previously studied the effect of seed layer and composition on the structure (by XRD, SEM, AFM and TEM) and performance (coercivity) of these CoPd films. These films do not switch coherently, so the coercivity is determined by the details of the switching mechanism, which was not studied in our previous paper. In the present paper, we show that information can be obtained about the switching mechanism from magnetic force microscopy (MFM) together with first order reversal curves (FORC), despite the fact that MFM can only be used at zero field. We find that these films switch by a mechanism of domain nucleation and dendritic growth into a labyrinthine structure, after which the unreversed domains gradually shrink to small dots and then disappear.

show abstract

Section: Switching Mechanism: Forc and Mfmmentioning

confidence: 84%

MFM and first order reversal curve (FORC) study of switching mechanism in Co25Pd75 films

Abugri

Clark

Visscher

et al. 2019

Journal of Applied Physics

Self Cite

View full text Add to dashboard Cite

show abstract

“…xFORC software 37 performs a non-weighted second order polynomial regression for each data point. xFORC is freely available as an executable file which requires LabVIEW run-time engine installed. FORC+ 38 estimates the mixed derivative of the magnetization using finite differences without the use of smoothing in order to obtain the sharp structures in the FORC distribution. Instead FORC+ display the raw data in such a color scheme that the noise appears grey from a distance for the human eye.…”

Section: Tools For Forc Processingmentioning

confidence: 99%

doFORC tool for calculating first-order reversal curve diagrams of noisy scattered data

Cimpoesu

Dumitru

Stancu

2019

Journal of Applied Physics

View full text Add to dashboard Cite

First-order reversal curves (FORC) diagram method is one of the most successful characterization techniques used to characterize complex hysteretic phenomena not only in magnetism, but also in other areas of science like in ferroelectricity, geology, archeology, light-induced and pressure hysteresis in spin-transition materials, etc. Because the definition of the FORC diagram involves a second-order derivative, the main problem in their numerical calculation is that the derivative of a function for which only discrete noise-contaminated data values are available magnifies the noise that is inevitably present in measurements. In this paper we present doFORC tool for calculating FORC diagrams of noise scattered data. It can provide both a smooth approximation of the measured magnetization and all its partial derivatives. doFORC is a free, portable application working on various operating systems, with an easy to use graphical interface, with four regression methods implemented to obtain a smooth approximation of the data which may then be differentiated to obtain approximations for derivatives. In order to perform the diagnostics and goodness of fit doFORC computes residuals to characterize the difference between observed and predicted values, generalized cross-validation to measure the predictive performance, two information criteria to quantify the information that is lost by using an approximate model, and three degrees of freedom to compare different amounts of smoothing being performed by different smoothing methods. Based on these doFORC can perform automatic smoothing parameter selection.

show abstract

“…The FORC+ program has also been used for analysis of more complicated structures such as magnetic tunneling junctions (MTJs) 11 , in which the characteristic fingerprints of individual layers (such as the dipole tail) can be identified in the FORC distribution of a complex structure containing such a layer.…”

Section: Examplesmentioning

confidence: 99%

Avoiding the zero-coercivity anomaly in first order reversal curves: FORC+

Visscher

2019

AIP Advances

Self Cite

View full text Add to dashboard Cite

In conventional FORC (First Order Reversal Curve) analysis of a magnetic system, reversible and low-coercivity irreversible materials are treated as being qualitatively different: the FORC distribution shows low-coercivity materials but completely hides reversible (zero-coercivity) ones. This distinction is artificial -as the coercivity approaches zero, the physical properties of an irreversible material change smoothly into those of a reversible material. We have developed a method (called FORC+, implemented in free software at http://MagVis.org) for displaying the reversible properties of a system (a reversible switching-field distribution, R-SFD) together with the irreversible ones (the usual FORC distribution), so that there is no sudden discontinuity in the display when the coercivity becomes zero. We will define a "FORC+ dataset" to include the usual FORC distribution, the R-SFD, the saturation magnetization, and what we will call the "lost hysteron distribution" (LHD) such that no information is lost -the original FORC curves can be exactly recovered from the FORC+ dataset. We also give some examples of the application of FORC+ to real data -it uses a novel complementary-color display that minimizes the need for smoothing. In systems which switch suddenly (thus having sharp structures in the FORC distribution) direct display of un-smoothed raw data allows visualization of sharp structures that would be washed out in a conventional smoothed FORC display. This is an expanded version of paper GG-05, MMM-Intermag 2019, with a discrete derivation of the FORC distribution (Eq. 1) and an additional example (Fig. 7).

show abstract

FORC+ analysis of perpendicular magnetic tunnel junctions

Cited by 10 publications

References 12 publications

MFM and first order reversal curve (FORC) study of switching mechanism in Co25Pd75 films

MFM and first order reversal curve (FORC) study of switching mechanism in Co25Pd75 films

doFORC tool for calculating first-order reversal curve diagrams of noisy scattered data

Avoiding the zero-coercivity anomaly in first order reversal curves: FORC+

Contact Info

Product

Resources

About