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Making live-time SEM/EDS phase mapping a reality

C. Heijboer and D. West

Thermo Fisher Scientific, Takkebijsters 1, 4817 BL Breda, The Netherlands

Email: cees.heijboer@thermofisher.com

BY MSSA TECH FORUM

EDS spectral imaging (SI) data sets contain large amounts of complex information. Generating EDS phase maps from this data with traditional techniques is self-limited by the ability of such techniques to simultaneously handle data sets of this magnitude and complexity. The resulting methods are computationally resource-consuming, require long data acquisitions and have the potential to misidentify or overlook minor phases. The application of principal component analysis (PCA) to spectral imaging data sets represents a paradigm shift in data processing techniques; in particular when applied to EDS phase mapping. These methods require no assumptions regarding sample chemistry, work well with low volume or sparse data sets, deal effectively with noisy data and are generally robust enough to eliminate the need for user input. The microanalysis software program, COMPASS, applies PCA to EDS SI data sets in order to automatically reduce the complexity of the data to the handful of dominant components that describe the data. These components are then used to identify and to describe the chemical phases within the data set. When the data reduction algorithms associated with COMPASS are run in the math kernel library of the processor, live time phase mapping becomes a reality. These phase maps are typically generated after a single, 30-second frame. Most samples under study are completely described by chemical phase maps after only 2-3 minutes of data acquisition.

 November 06, 2015
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