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ORNL researcher Louise Evans is working to ensure safeguards approaches and verification technologies are integrated early in the design process of advanced reactor technologies. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy
Decades of nuclear expertise guides global nonproliferation innovation
To turn carbon dioxide, or CO2, into methanol, or CH3OH, copper (shown in yellow) on a hydride-substituted support speeds reactions mediated by hydrides and catalyzed by hydrogen atoms (shown in black) from surface-adsorbed formate, HCOO*. Credit: Yang He/ORNL, U.S. Dept. of Energy
Ion swap improves CO2-defeating catalyst
Caption: The Na-CO2 battery developed at ORNL, consisting of two electrodes in a saltwater solution, pulls atmospheric carbon dioxide into its electrochemical reaction, and releases only valuable biproducts. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy
Carbon-capture batteries store renewable energy

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Oak Ridge National Laboratory researchers used an invertible neural network, a type of artificial intelligence that mimics the human brain, to select the most suitable materials for desired properties, such as flexibility or heat resistance, with high chemical accuracy. The study could lead to more customizable materials design for industry.

ORNL neural network study harnesses made-to-order design to pair properties to materials

A study led by researchers at ORNL could help make materials design as customizable as point-and-click.

Earth Day

ORNL brings big science to address the climate challenge

Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time. 

Dongarra in 2019 with Oak Ridge National Laboratory's Summit supercomputer

Dongarra named Turing Award recipient for advances in high-performance computing, AI

A force within the supercomputing community, Jack Dongarra developed software packages that became standard in the industry, allowing high-performance computers to become increasingly more powerful in recent decades.

ORNL’s Joseph Lukens runs experiments in an optics lab. Credit: Jason Richards/ORNL, U.S. Dept. of Energy

Giant leap toward quantum internet realized with Bell state analyzer

Scientists’ increasing mastery of quantum mechanics is heralding a new age of innovation. Technologies that harness the power of nature’s most minute scale show enormous potential across the scientific spectrum

Mars Rover 2020

Secretary’s Honor Awards recognize dozens of ORNL employees

More than 50 current employees and recent retirees from ORNL received Department of Energy Secretary’s Honor Awards from Secretary Jennifer Granholm in January as part of project teams spanning the national laboratory system. The annual awards recognized 21 teams and three individuals for service and contributions to DOE’s mission and to the benefit of the nation.

QLAN submit - A team from the U.S. Department of Energy’s Oak Ridge National Laboratory, Stanford University and Purdue University developed and demonstrated a novel, fully functional quantum local area network, or QLAN, to enable real-time adjustments to information shared with geographically isolated systems at ORNL using entangled photons passing through optical fiber. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

QIS investments position ORNL to lead the quantum revolution

A rapidly emerging consensus in the scientific community predicts the future will be defined by humanity’s ability to exploit the laws of quantum mechanics.

The Energy Exascale Earth System Model project reliably simulates aspects of earth system variability and projects decadal changes that will critically impact the U.S. energy sector in the future. A new version of the model delivers twice the performance of its predecessor. Credit: E3SM, Dept. of Energy

Updated exascale system for Earth simulations delivers twice the speed

A new version of the Energy Exascale Earth System Model, or E3SM, is two times faster than an earlier version released in 2018.

This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography. Credit: Ada Sedova/ORNL, U.S. Dept. of Energy

Scientists use Summit supercomputer, deep learning to predict protein functions at genome scale

A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.