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Al-enabled Lorentz microscopy for quantitative imaging of nanoscale magnetic spin textures

Physics

Al-enabled Lorentz microscopy for quantitative imaging of nanoscale magnetic spin textures

A. R. C. Mccray, T. Zhou, et al.

Discover the groundbreaking SIPRAD method by Arthur R. C. McCray and colleagues, revolutionizing quantitative phase reconstruction in nanoscale magnetic imaging. This AI-driven approach excels in accuracy and noise robustness, providing real-time insights into magnetic spin textures with unprecedented clarity.

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Playback language: English
Abstract
Quantitative characterization of in situ Lorentz transmission electron microscopy (LTEM) data for nanoscale magnetic spin textures is challenging. This paper presents an AI-enabled phase-retrieval method integrating a generative deep image prior with an LTEM image formation forward model. Using a single out-of-focus image, this approach (SIPRAD) achieves higher accuracy and noise robustness than existing methods, isolating sample heterogeneities from magnetic contrast. SIPRAD enables quantitative phase reconstruction of in situ data and potentially near real-time quantitative magnetic imaging.
Publisher
npj Computational Materials
Published On
May 27, 2024
Authors
Arthur R. C. McCray, Tao Zhou, Saugat Kandel, Amanda Petford-Long, Mathew J. Cherukara, Charudatta Phatak
Tags
Lorentz transmission electron microscopy
SIPRAD
quantitative phase reconstruction
nanoscale magnetic imaging
AI-enabled methods
image formation
magnetic contrast

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