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The DEMAND single crystal diffractometer at the High Flux Isotope Reactor, or HFIR, is the latest neutron instrument at the Department of Energy’s Oak Ridge National Laboratory to be equipped with machine learning-assisted software, called ReTIA. Credit: Jeremy Rumsey/ORNL, U.S. Dept. of Energy

Neutron experiments can take days to complete, requiring researchers to work long shifts to monitor progress and make necessary adjustments. But thanks to advances in artificial intelligence and machine learning, experiments can now be done remotely and in half the time.

The ORNL researchers’ findings may enable better detection of uranium tetrafluoride hydrate, a little-studied byproduct of the nuclear fuel cycle, and better understanding of how environmental conditions influence the chemical behavior of fuel cycle materials. Credit: Kevin Pastoor/Colorado School of Mines

ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.

Earth Day

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

ORNL researchers worked with partners at the Colorado School of Mines and Baylor University to develop a new process optimization and control method for a closed-circuit reverse osmosis desalination system. The work is intended to support fully automated, decentralized water treatment plants. Credit: Andrew Sproles/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory scientists worked with the Colorado School of Mines and Baylor University to develop and test control methods for autonomous water treatment plants that use less energy and generate less waste.

Bruce Warmack is using his physics and electrical engineering expertise to analyze advanced sensors for the power grid on a new testbed he developed at the Distributed Energy Communications and Controls Laboratory at ORNL. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Bruce Warmack has been fascinated by science since his mother finally let him have a chemistry set at the age of nine. He’d been pestering her for one since he was six.

A material’s spins, depicted as red spheres, are probed by scattered neutrons. Applying an entanglement witness, such as the QFI calculation pictured, causes the neutrons to form a kind of quantum gauge. This gauge allows the researchers to distinguish between classical and quantum spin fluctuations. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

A team led by the U.S. Department of Energy’s Oak Ridge National Laboratory demonstrated the viability of a “quantum entanglement witness” capable of proving the presence of entanglement between magnetic particles, or spins, in a quantum material.

As part of the Next-Generation Ecosystem Experiments Arctic project, scientists are gathering and incorporating new data about the Alaskan tundra into global models that predict the future of our planet. Credit: ORNL/U.S. Dept. of Energy

Improved data, models and analyses from ORNL scientists and many other researchers in the latest global climate assessment report provide new levels of certainty about what the future holds for the planet 

The REVISE-II modeling tool developed at ORNL supports decision-making for electric vehicle charging infrastructure development along interstate highways in support of intercity travel. Credit: Jason Richards/ORNL, U.S. Dept. of Energy

Researchers at Oak Ridge National Laboratory have developed a nationwide modeling tool to help infrastructure planners decide where and when to locate electric vehicle charging stations along interstate highways. The goal is to encourage the adoption of EVs for cross-country travel.

An algorithm developed and field-tested by ORNL researchers uses machine learning to maintain homeowners’ preferred temperatures year-round while minimizing energy costs. Credit: ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory researchers designed and field-tested an algorithm that could help homeowners maintain comfortable temperatures year-round while minimizing utility costs.

An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy

An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.