17 Undergraduate Research II (Posters)

Thursday, 20 March 2025
1:00 PM - 5:00 PM
Shenandoah ABC

TOWARDS A SYNTHETIC U-STAGE MICROSCOPE-NUMERICAL MODELING OF PLAGIOCLASE OPTICS OBSERVED IN THIN-SECTION

Paper number: 17-4
Program: Theme Sessions
Time: 1:00 PM – 5:00 PM

Authors

Abstract

The optical properties of plagioclase are well characterized. These properties vary as a function of grain orientation, composition, and cooling rate (i.e., degree of Si-Al ordering). It is our belief that these features are underutilized in geological investigations, and coupled with current computational resources, present the possibility for the development of new tools geared towards orientational analyses. This is timely, because current methodologies possess inherent limitations: 1) Universal Stage microscopes are time-intensive to use and are no longer manufactured, thus making procurement/maintenance of an instrument challenging; and 2) Electron Backscatter Diffraction (EBSD), while automated, still requires many hours of beam time to generate relatively small maps, thus constricting sample throughput and making this analytical technique cost prohibitive for many potential users. Thus, we present a foundational first step towards the development of a Synthetic U-Stage Microscope (SUS Microscope). Utilizing published optical properties of plagioclase across six compositions, namely the refractive indices and optical orientations, we construct a numerical model for birefringence and extinction angles for any plutonic plagioclase, both in terms of composition and orientation. From these results, we demonstrate this approach’s accuracy and limitations in several examples. First, we present a recasting of the Michel-Levy Method with comparison to the original. Next, we present results from individual plagioclase grains comparing optical based orientation estimates against EBSD determined orientations, thereby providing empirical estimates of accuracy. Future work will focus on automating the process, such that full thin-section scans can be analyzed, utilizing machine learning models to segment grains, isolate minerals of interest, and perform SUS analysis. Additionally, with strong advances in statistical techniques, such as Markov Chain-Monte Carlo simulations, it will be possible to determine robust orientational uncertainties for each crystal. The development of SUS Microscopy could benefit many fields of study, providing a high-throughput, cost-efficient, and accessible alternative to currently available techniques.

Geological Society of America Abstracts with Programs. Vol. 57, No. 2

doi: 10.1130/abs/2025SE-408813

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