2015 GSA Annual Meeting in Baltimore, Maryland, USA (1-4 November 2015)

Paper No. 23-12
Presentation Time: 11:20 AM


ODOM III, William E., Earth, Atmospheric, and Planetary Sciences, Purdue University, 550 Stadium Mall Dr., West Lafayette, IN 47907 and GRANGER, Darryl E., Earth Atmospheric and Planetary Sciences, Purdue University, 550 Stadium Mall Dr., West Lafayette, IN 47907, odomw@purdue.edu

Cosmogenic nuclides are widely utilized in Quaternary geology to date surface exposure, estimate erosion and soil formation rates, and date sediment burial. All of these applications hinge on accurately knowing local production rates and how they vary with elevation, geomagnetic field strength, and time. Production rates are typically calibrated on pristine surfaces of known age, such as glacial moraines and young volcanic flows, but good calibration sites are notoriously difficult to find. Moreover, it remains debated whether production rate scaling should be specific for each nuclide. For example, it has been predicted that 26Al scales differently than 10Be with elevation.

Another way to calibrate cosmogenic nuclide production rates is to use artificial targets exposed in specific locations for a known period of time. If the artificial target is sufficiently large and sufficiently free of contamination, production rates can be measured in a sample which has been exposed over only a few years. Here we show that photovoltaic silicon (used in solar cells) is an ideal target for calibrating production of 26Al. Solar cells have been distributed for decades all over the globe, and they are manufactured to extremely high purity so there should be no intrinsic 26Al prior to exposure.

The measurement of 26Al has been dramatically improved by the recent implementation of a gas-filled-magnet at PRIME Lab, which allows a tenfold increase in accelerator mass spectrometer (AMS) beam currents. Measurement of 26Al is now possible in solar panels exposed for only a few years at mountain elevations. We will present both theoretical calculations and preliminary data from solar panels as a proof of concept.