Inside the Laboratory: The Meteorite Center at the Sharjah Academy of Astronomy, Space Sciences, and Technology
This feature showcases how the Sharjah Academy of Astronomy, Space Sciences, and Technology (SAASST) employs techniques such as X-ray fluorescence (XRF), X-ray diffraction (XRD), scanning electron microscopy coupled with energy-dispersive spectroscopy (SEM-EDS), and Raman spectroscopy to determine the mineral makeup of meteorites.
“Inside the Laboratory” is a collaborative series with LCGC and Spectroscopy, profiling analytical scientists and their research groups worldwide. The series highlights current chromatographic and spectroscopic research, and explains why these efforts matter for analytical chemistry and related industries. Here, we explore how SAASST (United Arab Emirates) uses XRF, XRD, SEM-EDS, and Raman spectroscopy to elucidate the mineral composition of meteorites.
What is the Meteorite Center at SAASST?
The Meteorite Center at SAASST analyzes the mineral composition of meteorite samples collected by scientists. Established in 2017, it is the Gulf region’s first institution dedicated exclusively to meteorite study and space-science research. Beyond research, the Center aims to advance astronomy and space science education across the UAE and the broader Arab world.
SAASST comprises multiple buildings with distinct purposes. In addition to the research center, it features a planetarium, an astronomy exhibition, an observatory, and a Cosmic Park. These facilities are open to students, educators, researchers, and families who visit for research and educational experiences.
What are SAASST’s main objectives?
SAASST pursues three primary goals. First, it analyzes meteors and meteorites using the UAE Meteor Monitoring Network. Second, it conducts meteorite searches to collect samples for analysis. Third, it aims to develop a Space Situational Awareness (SSA) program in the UAE to foster growth in this scientific field within the country.
Key achievements of SAASST researchers
A notable achievement is the use of machine learning (ML) algorithms to optimize a drone-based meteorite collection system (DMS). The team has developed several neural network architectures to handle the data produced by their instruments, with convolutional neural networks (CNNs) playing a prominent role in visual data and computer-vision tasks.
These advanced models were developed in the Space Artificial Intelligence Laboratory (SAIL). They help distinguish earthly rocks from meteorites by training on SAASST’s meteorite collection and on regional rocks from the Sharjah area.
Significance of SAASST’s Meteorite Center
The Meteorite Center stands out as a key hub for meteorite research and planetary science in the Gulf. Its diverse collections, sophisticated lab capabilities, and active involvement in meteor monitoring and public outreach connect research, education, and community interest in space science.
Of particular importance is the Center’s meteorite collection, which includes everything from large iron meteorites to rare lunar and Martian specimens, tektites, and impactites. This enables researchers, geologists, and students to study extraterrestrial materials that are rarely available locally. Through careful cataloging and digital archiving, the Center is building a resource that could underpin long-term international research collaborations.
By integrating meteorite analysis, monitoring, workshops, and seminars—along with collaborations with global experts—the Center helps position the UAE on the map of planetary science and inspires a new generation of scientists interested in space, geology, and the origins of the solar system.
More information about the Meteorite Center at SAASST can be found here: https://saasst.ae/index.php
References
- SAASST, Meteorite Center. SAASST.ae. Available at: https://www.saasst.ae/index.php/space-sciences/meteorite-center (accessed 2025-12-05).
- SAASST, DMS – Drone Meteorite System. SAASST.ae. https://saasst.ae/index.php/hm/dms (accessed 2025-12-05).
- SAASST, Space Artificial Intelligence Laboratory. SAASST.ae. https://saasst.ae/index.php/space-sciences/space-artificial-intelligence (accessed 2025-12-08).
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