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In this artist’s conception of the process, an automated deposition system places a new material onto a base material (purple beam, right) as the last sample that was made is analyzed and sent to the AI (green beams, brain, left). The AI tells the pulsed laser deposition machine what to do next (data cable, bottom).
Researchers harness AI for autonomous discovery and optimization of materials
Students gather at a poster session
Students acquire skills at Quantum Science Center
Rectangular box being lifted by a red pully system up the left side of the building
Researchers make ‘green’ floor to replace steel

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ORNL, VA and Harvard researchers developed a sparse matrix full of anonymized information on what is thought to be the largest cohort of healthcare data used for this type of research in the U.S. The matrix can be probed with different methods, such as KESER, to gain new insights into human health. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

VA, ORNL and Harvard develop novel method to identify complex medical relationships

A team of researchers has developed a novel, machine learning–based  technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.

ORNL scientists created a new microbial trait mapping process that improves on classical protoplast fusion techniques to identify the genes that trigger desirable genetic traits like improved biomass processing. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy. Reprinted with the permission of Oxford University Press, publisher of Nucleic Acids Research

Retro technique advances modern bacterial engineering for bioenergy

ORNL scientists had a problem mapping the genomes of bacteria to better understand the origins of their physical traits and improve their function for bioenergy production.

QLAN submit - A team from the U.S. Department of Energy’s Oak Ridge National Laboratory, Stanford University and Purdue University developed and demonstrated a novel, fully functional quantum local area network, or QLAN, to enable real-time adjustments to information shared with geographically isolated systems at ORNL using entangled photons passing through optical fiber. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

QIS investments position ORNL to lead the quantum revolution

A rapidly emerging consensus in the scientific community predicts the future will be defined by humanity’s ability to exploit the laws of quantum mechanics.

This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography. Credit: Ada Sedova/ORNL, U.S. Dept. of Energy

Scientists use Summit supercomputer, deep learning to predict protein functions at genome scale

A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.

Burak Ozpineci is a globally recognized leader in power electronics research. He was named an ORNL Corporate Fellow in fall 2021. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Powering a clean, electrified future: Burak Ozpineci

Burak Ozpineci started out at ORNL working on a novel project: introducing silicon carbide into power electronics for more efficient electric vehicles. Twenty years later, the car he drives contains those same components.

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

Key witness helps scientists detect ‘spooky’ quantum entanglement in solid materials

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.

Erdem Asa is leveraging his power electronics expertise to adapt ORNL’s wireless charging technology to unmanned aerial vehicles. Credit: Erdem Asa/ORNL, U.S. Dept. of Energy

Erdem Asa: Taking to the skies with wireless charging

Having co-developed the power electronics behind ORNL’s compact, high-level wireless power technology for automobiles, Erdem Asa is looking to the skies to apply the same breakthrough to aviation.

A traffic-camera view of Shallowford Road, one of the more than 350 intersections in Chattanooga studied by Oak Ridge National Laboratory researchers.

Clearing congestion: ORNL computing researchers help unclog traffic jams

The daily traffic congestion along the streets and interstate lanes of Chattanooga could be headed the way of the horse and buggy with help from ORNL researchers.

Hope Corsair. Credit: Carlos Jones, ORNL/U.S. Dept. of Energy

Hope Corsair: Amplifying the societal impact of new technologies

When Hope Corsair’s new colleagues at Oak Ridge National Laboratory ask her about her area of expertise, she tells them it’s “context.” Her goal as an energy economist is to make sure ORNL’s breakthroughs have the widest possible

Ross Wang is leveraging his expertise in civil engineering, transportation systems, data analytics, and modeling and simulation in a variety of mobility projects at ORNL, including unsnarling traffic on some of the nation’s most congested roadways. Credit: ORNL/U.S. Dept. of Energy

Ross Wang: Driving clean mobility with data analytics

Ross Wang has been intent on resolving traffic jams since he rode a city bus every day through 40 minutes of traffic to get to his elementary school. That daily journey left an impression that would shape his career.