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Quantitative Scanning Transmission Electron Microscopy for Materials Science: Imaging, Diffraction, Spectroscopy, and Tomography AITranslate

lawrence berkeley national laboratory
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Publisher: Elsevier
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Abstract AITranslate

Scanning transmission electron microscopy (STEM) is one of the most powerful characterization tools in materials science research. Due to instrumentation developments such as highly coherent electron sources, aberration correctors, and direct electron detectors, STEM experiments can examine the structure and properties of materials at length scales of functional devices and materials down to single atoms. STEM encompasses a wide array of flexible operating modes, including imaging, diffraction, spectroscopy, and 3D tomography experiments. This review outlines many common STEM experimental methods with a focus on quantitative data analysis and simulation methods, especially those enabled by open source software. The hope is to introduce both classic and new experimental methods to materials scientists and summarize recent progress in STEM characterization. The review also discusses the strengths and weaknesses of the various STEM methodologies and briefly considers promising future directions for quantitative STEM research.

KeyWords AITranslate

scanning transmission electron microscopy materials science quantitative analysis simulation imaging diffraction spectroscopy tomography
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Basic Information:

DOI:https://doi.org/10.1146/annurev-matsci-080921-092646

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Citation Information:

Scanning transmission electron microscopy (STEM) is one of the most powerful characterization tools in materials science research. Due to instrumentation developments such as highly coherent electron sources, aberration correctors, and direct electron detectors, STEM experiments can examine the structure and properties of materials at length scales of functional devices and materials down to single atoms. STEM encompasses a wide array of flexible operating modes, including imaging, diffraction, spectroscopy, and 3D tomography experiments. This review outlines many common STEM experimental methods with a focus on quantitative data analysis and simulation methods, especially those enabled by open source software. The hope is to introduce both classic and new experimental methods to materials scientists and summarize recent progress in STEM characterization. The review also discusses the strengths and weaknesses of the various STEM methodologies and briefly considers promising future directions for quantitative STEM research.

quote

GB/T 7714-2015 [1] Colin Ophus. Annual Review of Materials Research, 2023(53). DOI:10.1146/annurev-matsci-080921-092646.
MLA [1] Colin Ophus. Annual Review of Materials Research, no. 53, 2023, https://doi.org/10.1146/annurev-matsci-080921-092646.
APA [1] Colin Ophus. (2023). Annual Review of Materials Research(53). https://doi.org/10.1146/annurev-matsci-080921-092646
IEEE [1] Colin Ophus, Annual Review of Materials Research, no. 53, 2023, doi: 10.1146/annurev-matsci-080921-092646. keywords: {scanning transmission electron microscopy;materials science;quantitative analysis;simulation;imaging;diffraction;spectroscopy;tomography}