Computational methods for materials characterization by electron tomography

• Electron tomography (ET) allows 3D analysis of materials at nanometre and atomic scale.
• Computing is of paramount importance for the processing and the analysis of ET data.
• Different 2D views acquired from the sample are combined to yield the 3D volume.
• The 3D volume is interpreted in terms of morphological and quantitative information.
• The computational methods and emerging developments in ET are comprehensively reviewed.

Electron tomography (ET) is a powerful imaging technique that enables thorough three-dimensional (3D) analysis of materials at the nanometre and even atomic level. The recent technical advances have established ET as an invaluable tool to carry out detailed 3D morphological studies and derive quantitative structural information. Originally from life sciences, ET was rapidly adapted to this field and has already provided new and unique insights into a variety of materials. The principles of ET are based on the acquisition of a series of images from the sample at different views, which are subsequently processed and combined to yield the 3D volume or tomogram. Thereafter, the tomogram is subjected to 3D visualization and post-processing for proper interpretation. Computation is of utmost importance throughout the process and the development of advanced specific methods is proving to be essential to fully take advantage of ET in materials science. This article aims to comprehensively review the computational methods involved in these ET studies, from image acquisition to tomogram interpretation, with special focus on the emerging methods.

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