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Phase retrieval using through-focus images in Lorentz transmission electron microscopy.
Takahiro Tamura1, Yukinori Nakane1, Hiroshi Nakajima2
1Department of Material and Life Science, Graduate School of Engineering, Osaka University, Suita, Osaka 565-0871, Japan.
Microscopy (Oxford, England)
|March 29, 2018
Summary
We developed a new phase retrieval method using through-focus images in Lorentz transmission electron microscopy (LTEM) to observe magnetic domain structures. This conjugate gradient maximum likelihood (CG-MAL) approach offers improved convergence for magnetic bubble analysis.
Area of Science:
- Materials Science
- Physics
- Electron Microscopy
Background:
- Lorentz transmission electron microscopy (LTEM) is crucial for visualizing magnetic domain structures.
- Accurate phase retrieval is essential for reconstructing high-resolution images from LTEM data.
- Existing iterative phase retrieval methods can face challenges with convergence and accuracy.
Purpose of the Study:
- To introduce and evaluate a novel phase retrieval method, conjugate gradient maximum likelihood (CG-MAL), for LTEM.
- To assess the effectiveness of CG-MAL using simulated and experimental through-focus images of magnetic bubbles.
- To demonstrate the method's capability in reconstructing magnetic domain structures.
Main Methods:
- Phase retrieval using the maximum likelihood method combined with the conjugate gradient method (CG-MAL).
- Utilizing a series of through-focus images of magnetic bubbles with defocus values ranging from -3 mm to 3 mm.
- Validation through both simulated data and experimental LTEM images.
Main Results:
- Successful reconstruction of magnetic domain structures for magnetic bubbles from both simulated and experimental data.
- Demonstrated superior convergence behavior of the CG-MAL method compared to other iterative phase retrieval techniques.
- The method effectively processed images across a wide defocus range (-3 mm to 3 mm).
Conclusions:
- The CG-MAL method provides an effective and robust approach for phase retrieval in LTEM.
- This technique significantly improves the observation of magnetic domain structures, particularly for magnetic bubbles.
- CG-MAL shows broad applicability for analyzing diverse magnetic domain structures using highly defocused through-focus images.
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