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A former intern for ORNL was selected to represent Tennessee presenting his research at the National Junior Science and Humanities Symposium. Langalibalele “Langa” Lunga, a senior at Farragut High School in Knoxville, Tennessee, interned with ORNL working on deep learning for fast scanning microscopy, a technique for capturing microscopic images more rapidly than traditional methods.

Scientists have developed a new machine learning approach that accurately predicted critical and difficult-to-compute properties of molten salts, materials with diverse nuclear energy applications.

Van Graves, an engineering manager at ORNL, is celebrating 40 years of dedicated service leading a diverse range of prominent engineering projects at ORNL and internationally.

Researchers at ORNL have developed a tool that gives builders a quick way to measure, correct and certify level foundations. FLAT, or the Flat and Level Analysis Tool, examines a 360-degree laser scan of a construction site using ORNL-developed segmentation algorithms and machine learning to locate uneven areas on a concrete slab.

ORNL’s Biological Monitoring and Abatement Program, or BMAP, is marking 40 years of helping steward the DOE’s 33,476 acres of land on which some of the nation’s most powerful science and technology missions are carried out.

As the focus on energy resiliency and competitiveness increases, the development of advanced materials for next-generation, commercial fusion reactors is gaining attention. A recent paper examines a promising candidate for these reactors: ultra-high-temperature ceramics, or UHTCs.

Using the Frontier supercomputer, a team of researchers from the Massachusetts Institute of Technology conducted large-scale calculations to chart the isospin density of a neutron star across a range of conditions. Their work provides new insights into how pressure and density interact within neutron stars, offering important predictions about their inner workings.

UT-Battelle has contributed up to $475,000 for the purchase and installation of advanced manufacturing equipment to support a program at Tennessee’s Oak Ridge High School that gives students direct experience with the AI- and robotics-assisted workplace of the future.

The Heartbeat Detector, developed at ORNL and licensed by Geovox Security Inc., detects hidden individuals in vehicles by measuring suspension vibrations. Now using a compact black box and cloud software, the system is more affordable and easier to use, while remaining the industry standard worldwide.
