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ORNL researchers are establishing a digital thread of data, algorithms and workflows to produce a continuously updated model of earth systems.

Digital twins are exactly what they sound like: virtual models of physical reality that continuously update to reflect changes in the real world.

 

LandScan Global depicts population distribution estimates across the planet. The darker orange and red colors above indicate higher population density. Credit: ORNL, U.S. Dept. of Energy

It’s a simple premise: To truly improve the health, safety, and security of human beings, you must first understand where those individuals are.

ORNL, VA and Harvard researchers developed a sparse matrix full of anonymized information on what is thought to be the largest cohort of healthcare data used for this type of research in the U.S. The matrix can be probed with different methods, such as KESER, to gain new insights into human health. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

A team of researchers has developed a novel, machine learning–based  technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.

A 3D printed thermal protection shield, produced by ORNL researchers for NASA, is part of a cargo spacecraft bound for the International Space Station. The shield was printed at the Department of Energy’s Manufacturing Demonstration Facility at ORNL. Credit: ORNL, U.S. Dept. of Energy

A research team at Oak Ridge National Laboratory have 3D printed a thermal protection shield, or TPS, for a capsule that will launch with the Cygnus cargo spacecraft as part of the supply mission to the International Space Station.

ORNL researchers combined additive manufacturing with conventional compression molding to produce high-performance thermoplastic composites, demonstrating the potential for the use of large-scale multimaterial preforms to create molded composites. Credit: ORNL/U.S. Dept. of Energy

Oak Ridge National Laboratory researchers combined additive manufacturing with conventional compression molding to produce high-performance thermoplastic composites reinforced with short carbon fibers.

A 3D printed turbine blade demonstrates the use of the new class of nickel-based superalloys that can withstand extreme heat environments without cracking or losing strength. Credit: ORNL/U.S. Dept. of Energy

Oak Ridge National Laboratory researchers have demonstrated that a new class of superalloys made of cobalt and nickel remains crack-free and defect-resistant in extreme heat, making them conducive for use in metal-based 3D printing applications.

Six ORNL scientists have been elected as fellows to the American Association for the Advancement of Science, or AAAS. Credit: ORNL, U.S. Dept. of Energy

Six ORNL scientists have been elected as fellows to the American Association for the Advancement of Science, or AAAS.

The CrossVis application includes a parallel coordinates plot (left), a tiled image view (right) and other interactive data views. Credit: Chad Steed/Oak Ridge National Laboratory, U.S. Dept. of Energy

From materials science and earth system modeling to quantum information science and cybersecurity, experts in many fields run simulations and conduct experiments to collect the abundance of data necessary for scientific progress.

Recent research involving Oak Ridge National Laboratory’s Spallation Neutron Source demonstrates crystal-like heat conduction in a solid-liquid hybrid, AgCrSe2.

Research by an international team led by Duke University and the Department of Energy’s Oak Ridge National Laboratory scientists could speed the way to safer rechargeable batteries for consumer electronics such as laptops and cellphones.

A new computational approach by ORNL can more quickly scan large-scale satellite images, such as these of Puerto Rico, for more accurate mapping of complex infrastructure like buildings. Credit: Maxar Technologies and Dalton Lunga/Oak Ridge National Laboratory, U.S. Dept. of Energy

A novel approach developed by scientists at ORNL can scan massive datasets of large-scale satellite images to more accurately map infrastructure – such as buildings and roads – in hours versus days.