GSA Annual Meeting in Phoenix, Arizona, USA - 2019

Paper No. 100-13
Presentation Time: 9:00 AM-6:30 PM


SNYDER, Jonah1, LAMBERT, Trevor2, CHAPPELL, J. Caleb3 and KREKELER, Mark P.S.3, (1)Geology & Environmental Earth Sciences, Miami University, 501 E. High St., Oxford, OH 45056, (2)Department of Geology & Environmental Earth Sciences, Miami University - Hamilton, 1601 University Blvd., Hamilton, OH 45011, (3)Geology and Environmental Earth Science, Miami University, 118 Shideler hall, 250 S. Patterson Ave, Oxford, OH 45056

Finding and best utilizing mineral resources that can support alternative energy sources such as photovoltaic cells is critical for the U.S. to move toward a more efficient and distributed power system. Quartzite can be an economically viable source of silicon for solar cells, and the purity of the silicon being used is correlated to the efficiency of the solar cell. The purer the silicon is, the more efficient the cell will be. Sorting quartzite that is mined or searching for high purity quartzite as a resource can be expedited by the use of reflective spectroscopy and/ or hyperspectral remote sensing. Samples of the Ordovician Eureka quartzite from east central Idaho were examined using an ASD Fieldspec 4 spectroradiometer using a contact probe. This enables an estimation of a correlation between what was measured on the device and the known purity of the samples of quartzite. Samples used included a range of highest purity to more iron oxide-rich samples. Multiple spectra were obtained in a controlled lab environment for each sample under both dry and wet conditions. Significant variation of the spectra of samples was observed suggesting that it is possible to classify high silica rock from less pure materials. This is largely a function of the iron oxide features in the upper visible and the near infrared portions of the spectrum combined with hydroxyl features. Surface texture and water saturation impact spectra but minimally for sorting and classification purposes. Spectral properties correlate reasonably well with known chemical composition determined by inductively coupled plasma – optical emission spectroscopy and bulk mineralogy by scanning electron microscopy and powder X-ray diffraction. The end of goal of this testing, to see if one could use hyperspectral sensing to look at large areas and determine the silicon content to know if it would be worthwhile mining, is supported. The technique is also suitable for production sorting.