G-mode magnetic force microscopy: Separating magnetic and electrostatic interactions using big data analytics

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Abstract

In this work, we develop a full information capture approach for Magnetic Force Microscopy (MFM), referred to as generalized mode (G-Mode) MFM. G-Mode MFM acquires and stores the full data stream from the photodetector, captured at sampling rates approaching the intrinsic photodiode limit. The data can be subsequently compressed, denoised, and analyzed, without information loss. Here, G-Mode MFM is implemented and compared to the traditional heterodyne-based MFM on model systems, including domain structures in ferromagnetic Yttrium Iron Garnet and the electronically and magnetically inhomogeneous high entropy alloy, CoFeMnNiSn. We investigate the use of information theory to mine the G-Mode MFM data and demonstrate its usefulness for extracting information which may be hidden in traditional MFM modes, including signatures of nonlinearities and mode-coupling phenomena. Finally, we demonstrate detection and separation of magnetic and electrostatic tip-sample interactions from a single G-Mode image, by analyzing the entire frequency response of the cantilever. G-Mode MFM is immediately implementable on any atomic force microscopy platform and as such is expected to be a useful technique for probing spatiotemporal cantilever dynamics and mapping material properties, as well as their mutual interactions.

Original languageEnglish
Article number193103
JournalApplied Physics Letters
Volume108
Issue number19
DOIs
StatePublished - May 9 2016

Funding

This research (for L.C., A.B., S.V.K., S.J.) was conducted at the Center for Nanophase Materials Sciences, which is a DOE Office of Science User Facility. P.K.L. would like to acknowledge the DOE, Office of Fossil Energy, National Energy Technology Laboratory (DE-FE-0008855, DE-FE-0024054, and DE-FE-0011194). P.K.L. appreciates the support of the U.S. Army Research Office Project (W911NF-13-1-0438) and the support for the National Science Foundation (CMMI-1100080).

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