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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.

 

Oak Ridge National Laboratory entrance sign

The Department of Energy’s Office of Science has selected three ORNL research teams to receive funding through DOE’s new Biopreparedness Research Virtual Environment initiative.

ORNL will collaborate with Fairbanks Morse Defense on decarbonization efforts to develop alternative fuel technologies for marine engines. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

ORNL, the Department of Energy’s largest multidisciplinary laboratory, and Fairbanks Morse Defense, a portfolio company of Arcline Investment Management, have entered into a Memorandum of Understanding to collaborate on the development and integration of alternative fuel technologies aimed at reducing the marine engine’s reliance on fossil fuels. 

ORNL seismic researcher Chengping Chai placed seismic sensors on the ground at various distances from an ORNL nuclear reactor to learn whether they could detect its operating state. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Like most scientists, Chengping Chai is not content with the surface of things: He wants to probe beyond to learn what’s really going on. But in his case, he is literally building a map of the world beneath, using seismic and acoustic data that reveal when and where the earth moves.

Neutron scattering experiments at the Spallation Neutron Source revealed how the dynamics between copper and oxygen make a special type of enzyme excel at breaking down biomass. Insights could lead to lowering the cost of biofuel production. Credit: Jill Hemman/ORNL, U.S. Dept. of Energy

Nonfood, plant-based biofuels have potential as a green alternative to fossil fuels, but the enzymes required for production are too inefficient and costly to produce. However, new research is shining a light on enzymes from fungi that could make biofuels economically viable.

ORNL’s award-winning ultraclean condensing high-efficiency natural gas furnace features an affordable add-on technology that can remove more than 99.9% of acidic gases and other emissions. The technology can also be added to other natural gas-driven equipment. Credit: Jill Hemman/ORNL

Natural gas furnaces not only heat your home, they also produce a lot of pollution. Even modern high-efficiency condensing furnaces produce significant amounts of corrosive acidic condensation and unhealthy levels of nitrogen oxides

State and Local Economic Development Award

A partnership of ORNL, the Tennessee Department of Economic and Community Development, the Community Reuse Organization of East Tennessee and TVA that aims to attract nuclear energy-related firms to Oak Ridge has been recognized with a state and local economic development award from the Federal Laboratory Consortium.

New manufacturing process produces better, cheaper cathodes for lithium-ion batteries. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

Researchers at ORNL have developed a new method for producing a key component of lithium-ion batteries. The result is a more affordable battery from a faster, less wasteful process that uses less toxic material.

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.