Display Accessibility Tools

Accessibility Tools

Grayscale

Highlight Links

Change Contrast

Increase Text Size

Increase Letter Spacing

Readability Bar

Dyslexia Friendly Font

Increase Cursor Size

SEM-EDS hardware and software capabilities upgraded

EDS map of a montaged area of a geological thin sectionThis fall, the Energy-dispersive X-ray spectroscopy (EDS) capabilities for both of our SEM systems received hardware and software updates that greatly boost our capabilities for elemental analysis. The new Oxford UltiMax detectors and processing units provide much faster counting and processing of X-rays, leading to rapid collection of high-quality spectra and maps.  Other capability updates include:
  • Live chemical imaging - near-instantaneous X-ray maps for locating elements / regions of interest
  • Large-area montaging for creating detailed X-ray maps at high-resolutions over up to mm-sized areas (such as the rock sample shown here, which includes 12 'tiles' of montaged X-ray map data)
  • Improved reporting and export options for retrieving and analyzing data
  • Offline licenses for AZtec for calculation of QuantMaps or other data processing
These upgrades were made possible through support from Assistant Professor Amanda Ostwald from the MSU Department of Earth and Environmental Sciences and the MSU College of Natural Science.
 
Dr. Ostwald and her team study igneous petrology—or the study of rocks formed by magma and lava—with a specialty in the igneous petrology of other planets. Her current research focus is on the magmatic and volcanic history of the Mars crust, for which she studies our only current Mars samples: meteorites. She leverages many microscopic—especially electron microscopic—techniques to learn more about the chemical and physical conditions of the magmas that contributed to the formation and evolution of Mars.  The new EDS hardware will help collect X-ray maps of entire Mars meteorite sections, so far we have successfully completed runs with over 300 tiles at 250x magnification, producing >60GB of data in a single dataset.