Abstract
AbstractIn situ electron microscopy allows one to monitor dynamical processes at high spatial and temporal resolution. This produces large quantities of data, and hence automated image processing algorithms are needed to extract useful quantitative measures of the observed phenomena. In this work, we outline an image processing workflow for the analysis of evolving interfaces imaged during liquid cell electron microscopy. As examples, we show metal electrodeposition at electrode surfaces; beam-induced nanocrystal formation and dissolution; and beam-induced bubble nucleation, growth, and migration. These experiments are used to demonstrate a fully automated workflow for the extraction of, among other things, interface position, roughness, lateral wavelength, local normal velocity, and the projected area of the evolving phase as functions of time. The relevant algorithms have been implemented in Mathematica and are available online.
Highlights
Detailed understanding of the evolution of interfaces is of both scientific and practical interest in many disciplines
We have developed a general use interface-tracking algorithm based on image analysis needs over several different liquid cell experiments
Had the image not been pre-processed with the TV filter and background subtraction, many false positives would have been identified by the edge detection (Fig. 2i)
Summary
Detailed understanding of the evolution of interfaces is of both scientific and practical interest in many disciplines. Making the best use of the information obtained during liquid cell experiments requires quantitative measurements from each frame in a video sequence as a phenomenon of interest takes place.
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