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Summer Widner, Stephanie Timbs, James Gaugler and James Avenell of ORNL are part of a team that processes thorium-228, a byproduct of actinium-227. As new uses for thorium are realized, particularly in medicine, the lab expects the demand for the radioisotope to grow.

As a medical isotope, thorium-228 has a lot of potential — and Oak Ridge National Laboratory produces a lot.

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As the United States transitions to clean energy, the country has an ambitious goal: cut carbon dioxide emissions in half by the year 2030, if not before. One of the solutions to help meet this challenge is found at ORNL as part of the Better Plants Program.

A new tool that simulates the energy profile of every building in America will give homeowners, utilities and companies a quick way to determine energy use and cost-effective retrofits that can reduce energy and carbon emissions.

A new tool that simulates the energy profile of every building in America will give homeowners, utilities and companies a quick way to determine energy use and cost-effective retrofits that can reduce energy and carbon emissions.

ORNL’s particle entanglement machine is a precursor to the device that researchers at the University of Oklahoma are building, which will produce entangled quantum particles for quantum sensing to detect underground pipeline leaks. Credit: ORNL, U.S. Dept. of Energy

To minimize potential damage from underground oil and gas leaks, Oak Ridge National Laboratory is co-developing a quantum sensing system to detect pipeline leaks more quickly.

Initially, Kevin Gaddis’s adapted HPIC will be used only for the fourth of six separations in  actinium-225 processing, but he hopes it will later be used for other separations — and other isotopes. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

An Oak Ridge National Laboratory researcher has invented a version of an isotope-separating device that can withstand extreme environments, including radiation and chemical solvents.

Researchers built optical tools called zero-mode waveguides, illustrated here, used to observe proteins that are implicated in human heart function. Credit: David S. White/University of Wisconsin-Madison

Researchers working with Oak Ridge National Laboratory developed a new method to observe how proteins, at the single-molecule level, bind with other molecules and more accurately pinpoint certain molecular behavior in complex

ORNL’s Jason DeGraw, a mechanical engineer and indoor air quality expert, uses numerical equations powered by high-performance computing to analyze and solve problems related to the dispersion patterns of biological pathogens as well as chemical irritants in buildings. Credit: ORNL, U.S. Dept. of Energy

Long before COVID-19’s rapid transmission led to a worldwide pandemic, Oak Ridge National Laboratory’s Jason DeGraw was performing computer modeling to better understand the impact of virus-laden droplets on indoor air quality

Researchers studying secondary metabolites in the fungus Aspergillus flavus, pictured, found unique mixes of metabolites corresponding to genetically distinct populations. The finding suggests local environmental conditions play a key role in secondary metabolite production, influencing the discovery of drugs and other useful compounds. Credit: Tomás Allen Rush/ORNL, U.S. Dept. of Energy.

Scientists at ORNL and the University of Wisconsin–Madison have discovered that genetically distinct populations within the same species of fungi can produce unique mixes of secondary metabolites, which are organic compounds with applications in

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.