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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. 

The Center for Bioenergy Innovation, or CBI, at the Department of Energy’s Oak Ridge National Laboratory has promoted Melissa Cregger and Carrie Eckert to serve as chief science officers, advancing the center’s mission of Â鶹ӰÒôs for new domestic biofuels, chemicals and materials.

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. 

Recent advancements at ORNL show that 3D-printed metal molds offer a faster, more cost-effective and flexible approach to producing large composite components for mass-produced vehicles than traditional tooling methods.

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. 

Scientists at ORNL have developed a vacuum-assisted extrusion method that reduces Â鶹ӰÒô 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. 

Jesse Labbé aims to leverage biology, computation and engineering to address societal challenges related to energy, national security and health, while enhancing U.S. competitiveness. Labbé emphasizes the importance of translating groundbreaking research into practical applications that have real-world impact.

The University of Oklahoma and Oak Ridge National Laboratory, the Department of Energy’s largest multi-program science and energy laboratory, have entered a strategic collaboration to establish a cutting-edge additive manufacturing center. 

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. 

 

Scientists at Oak Ridge National Laboratory and the University of Colorado Boulder used a gene-silencing tool and a large library of molecular guides to understand how photosynthetic bacteria adapt to light and temperature changes. They found that even partial suppression of certain genes yielded big benefits in modifying the stress response of wild microbes.