Skip to main content
Merlin Theodore, advanced fibers manufacturing group leader and Tuskegee University alumna, will guide Oak Ridge National Laboratory’s collaboration with the university, through which students and researchers work together to advance the development of bioderived materials. Credit: ORNL, U.S. Dept. of Energy

ORNL and Tuskegee University have formed a partnership to develop new biodegradable materials for use in buildings, transportation and biomedical applications.

Ten scientists from the Department of Energy’s Oak Ridge National Laboratory are among the world’s most highly cited researchers. Credit: ORNL, U.S. Dept. of Energy

Ten scientists from the Department of Energy’s Oak Ridge National Laboratory are among the world’s most highly cited researchers, according to a bibliometric analysis conducted by the scientific publication analytics firm Clarivate.

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.

ORNL’s Christine Walker, a technical consultant and researcher in the Integrated Building Performance Group, works with the nation’s federally owned buildings through the Federal Energy Management Program, helping to reduce their carbon footprint and improve their energy performance. Credit: ORNL/U.S. Dept. of Energy

She may not wear a white coat or carry a stethoscope, but Christine Walker of ORNL spends her days diagnosing the energy health of buildings and figuring out how to improve their efficiency to achieve cost savings and reduce their carbon footprint.

AIST Conference

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 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

From left to right are Beth Armstrong, Govindarajan Muralidharan and Andrew Payzant.

ASM International recently elected three researchers from ORNL as 2021 fellows. Selected were Beth Armstrong and Govindarajan Muralidharan, both from ORNL’s Material Sciences and Technology Division, and Andrew Payzant from the Neutron Scattering Division.

From top to bottom respectively, alloys were made without nanoprecipitates or with coarse or fine nanoprecipitates to assess effects of their sizes and spacings on mechanical behavior. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy

Scientists at ORNL and the University of Tennessee, Knoxville, have found a way to simultaneously increase the strength and ductility of an alloy by introducing tiny precipitates into its matrix and tuning their size and spacing.

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.