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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.

Strengthening the competitiveness of the U.S. transportation industry depends on developing domestic EV batteries that combine rapid charging with long-range performance — two goals that often conflict. Researchers at ORNL have addressed this challenge by redesigning a key battery component, enabling fast, 10-minute charging while improving energy density and reducing reliance on copper.

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.

Researchers at ORNL have developed an innovative new technique using carbon nanofibers to enhance binding in carbon fiber and other fiber-reinforced polymer composites – an advance likely to improve structural materials for automobiles, airplanes and other applications that require lightweight and strong materials.

Members of the Quantum Science Center, or QSC, gathered at an all-hands meeting in Baton Rouge, Louisiana, in mid-May to reflect on the remarkable accomplishments from the past five years and to prepare for what members hope to be the next five years of the center.

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.

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.

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.

Paul is exploring the next frontier: bridging quantum computing with neutron science. His research aims to integrate quantum algorithms with neutron scattering experiments, opening new possibilities for understanding materials at an atomic level.

The fifth annual Quantum Science Center, or QSC, Summer School at Purdue University, held Apr. 21 through Apr. 25, 2025, welcomed its largest group of students to date. Experts from industry, academia and national laboratories gathered at the Purdue Quantum Science and Engineering Institute to share their research in multiple areas of quantum science.