DETERMINING 3D CHONDRULE SIZES FROM 2D THIN SECTIONS: LOST IN TRANSLATION

Chondrites are a type of primitive meteorite that are characterized by the presence of rounded inclusions, called chondrules, which formed when the Solar nebula condensed. This means chondritic meteorites contain some of the oldest materials in our Solar system. By studying chondrites we can better understand the formation of our universe.

A common way to study chondrules is to examine a thin section of a chondrite with a microscope. Many properties can be identified with thin sections, but any data of chondrule size is biased because one is trying to describe a 3D object using a 2D slice. Our investigation sought to remedy this by translating 2D data into 3D data.

Using Adobe Photoshop, we identified chondrules in elemental X-ray maps of 7 ordinary chondrite thin sections (Northwest Africa (NWA) 7978, 6550, 7981, 4910, 7777, 7917, and 8007). All samples are unequilibrated (petrologic type 3), and therefore not highly metamorphosed. Chondrules were fairly easy to identify, but, in samples of higher petrologic types (e.g. > 3.6), it was hard to distinguish chondrules from matrix. We identified 198-522 chondrules per sample and measured their diameters in ImageJ. Finally, by using Jeffrey Cuzzi and Daniel Olson's program (Cuzzi and Olson 2017), we estimated the number of 3D chondrules per diameter bin based on our 2D measurements.

The results of the program (Cuzzi and Olson 2017) were surprising, as it yielded negative values for many of the diameter bins and overestimated the number of possible chondrules in other bins. It is possible the overestimations and negative values could be avoided by identifying more chondrules with smaller diameters in the thin sections, but the resolution of the X-ray images makes this difficult. For example our samples’ resolutions varied from 7 mu per pixel to 15 mu, and only 0-4 chondrules less than 150 mu in diameter were identified in all seven samples. In future investigations, it would be useful to compare measurements of chondrules derived from 3D CT scans with the estimated sizes from this program (Cuzzi and Olson 2017). It may be possible to determine how the program overestimates and underestimates sizes, and then adjust accordingly in the future.

Cuzzi, J.N., and Olson, D.M., 2017 Recovering 3D particle size distribution from 2D sections: Meteoritics & Planetary Science, v. 52, nr. 3, p. 532-545.