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Paper No. 7
Presentation Time: 10:30 AM

USING LASER INDUCED BREAKDOWN SPECTROSCOPY (LIBS), SCANNING ELECTRON MICROSCOPY (SEM), AND ACOUSTO-OPTIC TUNABLE FILTER SPECTROSCOPY (AOTF) TO DISTINGUISH BETWEEN BACTERIALLY AND NON-BACTERIALLY INFLUENCED CALCITE AND GYPSUM, FORT STANTON CAVE, NEW MEXICO


CHAVEZ, Arriana1, UCKERT, Kyle2, MCMILLAN, Nancy J.3, CHANOVER, Nancy2 and VOELZ, David G.4, (1)Geological Sciences, New Mexico State University, BOX 30001 MSC 3AB, Las Cruces, NM 88003, (2)Astronomy, New Mexico State University, P. O. Box 30001, MSC 4500, Las Cruces, NM 88003, (3)Geological Sciences, New Mexico State University, Box 30001 MSC 3AB, Las Cruces, NM 88003, (4)Electrical and Computer Engineering, New Mexico State University, Box 30001 MSC 3O, Las Cruces, NM 88003, arrichav@nmsu.edu

The combination of LIBS and AOTF provides a robust method for geochemical analysis in extreme conditions, such as caves or other planets. In this study, samples of cave calcite and cave gypsum collected from Fort Stanton, NM, were analyzed with SEM, LIBS, and AOTF spectroscopy to determine if the presence of bacterial bodies and biomarkers affect the elemental composition and chemical fingerprints of the host rock.

Through atom excitation and photon analysis, LIBS enables quick and easy identification of materials by their elemental compositions and chemical “fingerprints”. AOTF spectroscopy measures light reflected from mineral surfaces using the acousto-optic effect to diffract light using sound waves.

SEM analysis was utilized to classify each sample as either bacterially or non-bacterially influenced. Bacterially influenced samples showed signs of bacterial bodies and/or biomarkers, such as mucus strands. These bodies and biomarkers are abundant in calcite samples from Don Sawyer Memorial Hall. Non-bacterially influenced samples were more crystalline in nature and lacked spherical or rounded components, as seen in selenite needles discovered in Roaring Hill.

Samples analyzed with LIBS were ablated 200 times; one ablation to clean the surface and another to analyze the sample, for 100 shots. Additionally, argon gas flowed inside the sample stage during data acquisition. The argon intensifies the spectra and diminishes the intensity of nitrogen and oxygen from the surrounding air, thus allowing a more accurate analysis of each sample. Samples were then analyzed using AOTF and one spectrum was obtained per sample.

LIBS and AOTF spectra are modeled with Principal Component Analysis (PCA) and Partial Least Squares Regression (PLSR) techniques to distinguish between bacterial and non-bacterial gypsum and calcite.

The results of this study can aid in cave research, geomicrobiology, and advances in portable LIBS and AOTF devices.

Session No. 341

T60. Caves as Deep Time Repositories of Geological, Biological, and Anthropological Information (Posters)
Wednesday, 30 October 2013: 9:00 AM-6:30 PM
Hall D (Colorado Convention Center)
Geological Society of America Abstracts with Programs. Vol. 45, No. 7, p.777
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