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Illustration of the GRETA detector, a spherical array of metal cylinders. The detector is divided into two halves to show the inside of the machine. Both halves are attached to metal harnesses, displayed against a black and green cyber-themed background.

Analyzing massive datasets from nuclear physics experiments can take hours or days to process, but researchers are working to radically reduce that time to mere seconds using special software being developed at the Department of Energy’s Lawrence Berkeley and Oak Ridge national laboratories.  

Illustration of a glowing black box emitting digital particles that form into a 3D model of an electrical grid infrastructure, set against a background of binary code and data visualizations.

Researchers at Oak Ridge National Laboratory have developed a modeling method that uses machine learning to accurately simulate electric grid behavior while protecting proprietary equipment details. The approach overcomes a key barrier to accurate grid modeling, helping utilities plan for future demand and prevent blackouts. 

 

Research scientist Daniel Jacobson is standing with his arms crossed with a dark black backdrop

Daniel Jacobson, distinguished research scientist in the Biosciences Division at ORNL, has been elected a Fellow of the American Institute for Medical and Biological Engineering, or AIMBE, for his achievements in computational biology. 

Researcher is sitting in bio lab surrounded with plants

Dave Weston studies how microorganisms influence plant health and stress tolerance, using the Advanced Plant Phenotyping Laboratory to accelerate research on plant-microbe interactions and develop resilient crops for advanced fuels, chemicals and 

Three egg-shaped orbs of varying opacity are shown on a dark blue background, increasing transparency revealing they are filled with smaller round balls of red and blue. Arrows indicate counterclockwise rotation of the orbs, and green squiggles imply motion of the smaller balls.

Using the Frontier supercomputer at ORNL, researchers have developed a new technique that predicts nuclear properties in record detail. The study revealed how the structure of a nucleus relates to the force that holds it together. This understanding could advance efforts in quantum physics and across a variety of sectors, from to energy production to national security.

Six images fanned out across the right side of the page with the first page showcasing the report cover. To the right hand side is a green oak leaf.

A workshop led by scientists at ORNL sketched a road map toward a longtime goal: development of autonomous, or self-driving, next-generation research laboratories. 

Computer rendering of the FRIB Decay Station initiator, featuring cylindrical components, vacuum chambers, and a greenish glow, used to measure the decays of exotic isotopes at FRIB.

Scientists at ORNL are using advanced germanium detectors to explore fundamental questions in nuclear physics, such as the nature of neutrinos and the matter-antimatter imbalance. The ongoing LEGEND project, an international collaboration, aims to discover neutrinoless double beta decay, which could significantly advance the understanding of the universe.

ORNL researcher Melissa Cregger is standing outside smiling for a photo. Woman is wearing blue and white polka dot shirt with a purple cardigan.

Melissa Cregger of the Department of Energy’s Oak Ridge National Laboratory has received the Presidential Early Career Award for Science and Engineers, or PECASE, the highest honor bestowed by the U.S. government on outstanding early-career scientists and engineers. 

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.

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.