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Figure 2 : Comparison between grayscale cross sections of (a) nano-icicles covered with oil on anti-frosting surface [ 19 ] and red cabbage; and (b) emulsion of microscale water droplets and oil [ 20 ] and a slice of Swiss cheese with large holes.

of the object and capturing an image of the exposed cross section. By “slicing-and-viewing” through the entire object of interest, a set of images of sequential cross sections of the object may be collected. T ese data can be processed using a variety of image processing programs to yield a 3D reconstruction of the original object that can be used to explore the internal geometry and quantify important charac- teristics such as secondary phase distribution within a parent phase (for example, nanoparticles in a composite or drops in an emulsion) or porosity (for example, within shells, rocks, or novel 3D electrodes for batteries).

In a manner analogous to these research procedures, we show that 2D images of sequential cross sections of several foods can be quickly reconstructed into a volumetric data set, shared, and interactively explored online using simple and fast image processing. We describe the entire process and present the results of destructive tomography of red cabbage and Swiss cheese. We selected these two common food items because their cross-sectional morphology resembles, albeit at a much larger size, objects that we have previously encountered in our research. For example, the grayscale cross sections of the red cabbage resemble those of nano-icicles covered by oil on anti-frosting coatings [ 19 ] (see Figure 2a ). Similarly, a grayscale image of holes in Swiss cheese resembles that of water microdroplets and oil emulsion [ 20 ] (see Figure 2b ). The rich morphology of the red cabbage also resembles geometry of biological cells interacting with nanomaterials imaged using FIB-SEM [ 21 ]. Consequently, the proposed activity can be not only used to introduce students to tomography, but can also be a hands-on component of a broader outreach program covering a variety of topics. In the last part of this article, we describe our experience with implementation of this activity in a local middle school.

Materials and Methods Red cabbage . We selected a red cabbage about 10 cm in diameter as our first sample because of its rich internal


composition and high contrast between the lighter and darker colors. In order to repeatedly cut thin slices with uniform thickness we employed a mandolin slicer shown with cabbage slices in Figure 3a . Aſt er each cut we placed the cabbage in a marked position in front of a white background set by a sheet of paper and captured a digital image of the cross section. T e collected images were pre-processed using ImageJ, Microsoſt Windows Paint, or Adobe Photoshop. Specifi cally, besides adjusting contrast and brightness, the out-of-focus areas outside of the cross section were removed (otherwise the cabbage attains a half-cylinder shape aſt er reconstruction). T e images in Figure 3b show examples of four

“cleaned-up” cabbage sections, in original color and aſt er binarization followed by color inversion (watch Video 1 online in the digital edition of this issue at this web address: ). At this stage of processing of a typical FIB-SEM data set, the grayscale images would be imported into 3D analysis soſt ware. T e sequential slices would be aligned with respect to each other, segmented into individual phases (for example, using thresh- olding to produce binary images such as those in Figure 3b ), and reconstructed in three dimensions. While conceptually straightforward, full execution of this image processing methodology can be cumbersome and is beyond scope of a K–12 outreach activity. Aſt er evaluating several alternatives, we found that ImageJ as well as Wolfram Mathematica can be used relatively easily to conduct a simplifi ed image processing procedure. Since ImageJ is commonly used by microsco- pists, the image processing steps in this soſt ware will not be reiterated here. In turn, Mathematica is commonly available to university students and is being used increasingly in K–12 grades, but it is not commonly used by microscopists. We found that just a few lines of code in this soſt ware are needed to make an interactive and easy-to-explore 3D reconstruction of the original object from the collected images. T e sample code for processing the images can be downloaded from Reference [ 22 ]. Examples of two progressive cuts in the x - y plane into a red cabbage reconstructed using this code along the z -axis are shown in Figure 3c . Along with the 3D reconstruction, these few lines of code produce sliders that a viewer can drag to progressively “clip-away” sections of the object along the z -axis as well as the x -axis (see Figure 3d and watch Video 2 online in the digital edition of this issue at this web address: ). T e results can be saved as a Mathematica Demonstration or in Computational Document Format (CDF) and shared via any website (for example, see Reference [ 22 ]). Pre-sliced cheese . Next, in order to improve the safety of the procedure, we looked for samples that can be “pre-sliced” • 2017 September

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