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A 3D printing nozzle wrapped in insulation extrudes black composite material into a small square mold on a green and white flat surface in a lab setting. Inset shows a close-up of a pressure gauge connected to brass valves and tubing.

Scientists at ORNL have developed a vacuum-assisted extrusion method that reduces internal porosity by up to 75% in large-scale 3D-printed polymer parts. This new technique addresses the critical issue of porosity in large-scale prints but also paves the way for stronger composites. 

Image of the Frontier supercomputer in black with Frontier spelled out across the cabinets in front.

Research teams at the Department of Energy’s Oak Ridge National Laboratory received computing resource awards to train and test AI foundation models for science. A total of six ORNL projects were awarded allocations from the National Artificial Intelligence Research Resource, or NAIRR, pilot and the Innovative and Novel Computational Impact on Theory and Experiment, or INCITE, program to train their AI models.

Illustration of a glowing black box emitting digital particles that form into a 3D model of an electrical grid infrastructure, set against a background of binary code and data visualizations.

Researchers at Oak Ridge National Laboratory have developed a modeling method that uses machine learning to accurately simulate electric grid behavior while protecting proprietary equipment details. The approach overcomes a key barrier to accurate grid modeling, helping utilities plan for future demand and prevent blackouts. 

 

Green and blue background of a graphic image that says Honors and Awards

Mariam Kiran, a quantum research scientist at the Department of Energy’s Oak Ridge National Laboratory, was recently honored as a finalist at the British Council’s Study U.K. Alumni Awards 2025, which celebrate the achievements of U.K. alumni worldwide.

Illustration of a virtual meeting on a laptop screen featuring diverse cartoon avatars of people in a grid layout. In the center, a logo reads “Winter Classic Invitational Student Cluster Competition.” The background consists of digital blue circuitry and data flow patterns, suggesting a technology or computing theme.

ORNL researchers helped introduce college students to quantum computing for the first time during the 2025 Winter Classic Invitational, providing hands-on access to real quantum hardware and training future high-performance computing users through a unique challenge that bridged classical and quantum technologies.

INCITE

The Innovative and Novel Computational Impact on Theory and Experiment, or INCITE, program has announced the 2026 Call for Proposals, inviting researchers to apply for access to some of the world’s most powerful high-performance computing systems. 

Research scientist Daniel Jacobson is standing with his arms crossed with a dark black backdrop

Daniel Jacobson, distinguished research scientist in the Biosciences Division at ORNL, has been elected a Fellow of the American Institute for Medical and Biological Engineering, or AIMBE, for his achievements in computational biology. 

Four researchers are standing next to a research rector that is glowing blue

A team from ORNL, joined by university students, recently traveled to the Ohio State University Research Reactor to conduct a novel experiment on nuclear thermal rocket fuel coatings — one that could help propel NASA’s astronauts to Mars faster and more efficiently. 

Researcher is sitting in bio lab surrounded with plants

Dave Weston studies how microorganisms influence plant health and stress tolerance, using the Advanced Plant Phenotyping Laboratory to accelerate research on plant-microbe interactions and develop resilient crops for advanced fuels, chemicals and 

Wall of black computer chords with blue wiring

Researchers from ORNL have developed a new application to increase efficiency in memory systems for high performance computing. Rather than allow data to bog down traditional memory systems in supercomputers and impact performance, the team from ORNL, along with researchers from the University of Tennessee, Knoxville, created a framework to manage data more efficiently with memory systems that employ more complex structures.