91°µÍø

Skip to main content
Illustration of a quantum experiment: atoms in a lattice (inset) with entanglement effects radiating from a central particle on a textured surface.

Working at nanoscale dimensions, billionths of a meter in size, a team of scientists led by ORNL revealed a new way to measure high-speed fluctuations in magnetic materials. Knowledge obtained by these new measurements could be used to advance technologies ranging from traditional computing to the emerging field of quantum computing. 

Hugh O'Neil, director or ORNL's Center for Structural Molecular Biology is sitting in the lab on a stool, hand on desk with glasses on. There are lab related items blurred in the foreground.

Hugh O’Neill’s lifelong fascination with the complexities of the natural world drives his research at ORNL, where he’s using powerful neutron beams to dive deep into the microscopic realm of biological materials and unlock secrets for better production of domestic biofuels and bioproducts.

Procter & Gamble scientists used ORNL’s Summit supercomputer to create a digital model of the corneal epithelium, the primary outer layer of cells covering the human eye, and test that model against a series of cleaning compounds in search of a gentler, more environmentally sustainable formula.

P&G is using simulations on the ORNL Summit supercomputer to study how surfactants in cleaners cause eye irritation. By modeling the corneal epithelium, P&G aims to develop safer, concentrated cleaning products that meet performance and safety standards while supporting sustainability goals.

Two pictures of a rounded triangle shape are shown in mirror image. The left is white with red and purple spots in the middle while the one on the right is purple with a yellow and blue ring in the middle

Scientists designing the world’s first controlled nuclear fusion power plant, ITER, needed to solve the problem of runaway electrons, negatively charged particles in the soup of matter in the plasma within the tokamak, the magnetic bottle intended to contain the massive energy produced. Simulations performed on Summit, the 200-petaflop supercomputer at ORNL, could offer the first step toward a solution.

ORNL researcher Phong Le poses for a photo outside on a walkway bridge over the pond. The photo is framed with brown and green plants

Phong Le is a computational hydrologist at ORNL who is putting his skills in hydrology, numerical modeling, machine learning and high-performance computing to work quantifying water-related risks for humans and the environment. 

Photo is a high aerial view of lake superior through the clouds

Researchers at Stanford University, the European Center for Medium-Range Weather Forecasts, or ECMWF, and ORNL used the lab’s Summit supercomputer to better understand atmospheric gravity waves, which influence significant weather patterns that are difficult to forecast. 

Researcher in a blue coat and glasses, purple gloves and white baseball gat pulls out materials from a metal canister

ORNL researchers created and tested two methods for transforming coal into the scarce mineral graphite, which is used in batteries for electric vehicles. 

3D map of Washington, D.C. that is a weather model of neighborhood during heat waves. The map is red and green indicating which buildings are giving off more heat
Scientists at ORNL have developed a first-ever urban heat wave simulation that takes into account the compounding effects from building infrastructure. The method provides a more accurate picture of the impacts from excessive heat on at-risk
A small sample from the Frontier simulations reveals the evolution of the expanding universe in a region containing a massive cluster of galaxies from billions of years ago to present day (left).

In early November, researchers at the Department of Energy’s Argonne National Laboratory used the fastest supercomputer on the planet to run the largest astrophysical simulation of the universe ever conducted. The achievement was made using the Frontier supercomputer at 91°µÍø. 

Nine men are pictured here standing in front of a window, posing for a group photo with 5 standing and 4 sitting.

A research team led by the University of Maryland has been nominated for the Association for Computing Machinery’s Gordon Bell Prize. The team is being recognized for developing a scalable, distributed training framework called AxoNN, which leverages GPUs to rapidly train large language models.