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Friday, October 11 • 09:40 - 10:00
Data Fusion and Multivariate Analysis: A Tool for the Identification of Clay Minerals During in-situ Planetary Exploration

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Clay minerals present an opportunity to satisfy NASA’s primary objective of determining whether life ever arose on Mars and are recognized as high-priority targets for future missions. Clay minerals form by chemical interactions between liquid water and rock and are thus key markers of environments that may have been warm, wet, and habitable in the past. Further, clays have a demonstrated capacity to preserve chemical and morphological fossil and have even been implicated in the abiogenesis of life on Earth.
However, the exact identification of clay minerals by conventional analytical methods is complicated and often inaccurate. Analytical issues are associated with the ultrafine grain size, the compositional variability, and the structural disorders that are common amongst clay minerals. It is therefore necessary to develop a rapid analysis technique for clay properties so that upcoming exploration rovers can be reliably guided towards high-priority clay-bearing targets.
We investigate a technique known as data fusion, in which the information collected from two spectroscopic techniques, namely, laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy (RS), will be combined into a single data-set. This methodology is founded on the basic premise that aggregating information from multiple sources offers more relevant knowledge about a sample and yields more specific, refined inferences (classifications with less error and predictions with less uncertainty) than an individual source acting alone. LIBS and RS are well-suited for this task as they provide complimentary information: LIBS records the elemental composition while RS reveals molecular structures. We hypothesize that exploiting the synergistic nature of LIBS and RLS through data fusion techniques will enable definitive mineral phase identification and produce clay mineral classification models with lower uncertainty, higher reliability, and improved interpretability because the uncertain identity of a target that arises from the molecular features may be clarified by the chemical profile, and vice versa.


Erin Gibbons

PhD Student, McGill University
Erin is a PhD student of Earth and Planetary Science at McGill University. She is working as a student science collaborator with NASA's current exploration rover, Curiosity, and hopes to collaborate on upcoming missions. Her research is dedicated to improving the operativity of laser-based... Read More →

Friday October 11, 2019 09:40 - 10:00 EDT
Room CR1 ICAO - 999 Boulevard Robert-Bourassa, Montréal, QC H3C 5H10