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ORNL's Communications team works with news media seeking information about the laboratory. Media may use the resources listed below or send questions to news@ornl.gov.

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Larry York is sitting in front of a computer screen showing an image of plant phenotyping

The Advanced Plant Phenotyping Laboratory at ORNL utilizes robotics, multi-modal imaging, and AI to enhance understanding of plant genetics and interactions with microbes. It aims to connect genes to traits for advancements in bioenergy, agriculture, and climate resilience. Senior scientist Larry York highlights the lab's capabilities and the insights from a new digital underground imaging system to improve biomass feedstocks for bioenergy and carbon storage.

This is a simulated image of the project to build a new network that artificial intelligence and machine learning to steer experiments and analyze data faster and more accurately. will enable

To bridge the gap between experimental facilities and supercomputers, experts from SLAC National Accelerator Laboratory are teaming up with other DOE national laboratories to build a new data streaming pipeline. The pipeline will allow researchers to send their data to the nation’s leading computing centers for analysis in real time even as their experiments are taking place. 

FAMU, FSU, FAMU-FSU College of Engineering, and Oak Ridge National Laboratory (ORNL) leadership

Oak Ridge National Laboratory has launched its Neutron Nexus pilot program with Florida Agricultural & Mechanical University and Florida State University through the FAMU-FSU College of Engineering. The first program of its kind nationwide, it’s aimed at broadening and diversifying the scientific user community with outreach to universities and colleges. 

Illustration of a hydrogen atom.

Scientists at ORNL used neutrons to end a decades-long debate about an enzyme cancer uses.

This illustration demonstrates how atomic configurations with an equiatomic concentration of niobium (Nb), tantalum (Ta) and vanadium (V) can become disordered. The AI model helps researchers identify potential atomic configurations that can be used as shielding for housing fusion applications in a nuclear reactor. Credit: Massimiliano Lupo Pasini/ORNL, U.S. Dept. of Energy

A study led by the Department of Energy’s Oak Ridge National Laboratory details how artificial intelligence researchers created an AI model to help identify new alloys used as shielding for housing fusion applications components in a nuclear reactor. The findings mark a major step towards improving nuclear fusion facilities.

ORNL's Spallation Neutron Source, the nation’s leading source of pulsed neutron beams for research, was recently restarted after nine months of upgrade work. Credit: ORNL, U.S. Dept. of Energy

ORNL's Spallation Neutron Source, the nation’s leading source of pulsed neutron beams for research, was recently restarted after nine months of upgrade work. 

Takeshi Egami stands at his workstation at ORNL’s Spallation Neutron Source where he used novel experimental methods to propose the density wave theory. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Distinguished materials scientist Takeshi Egami has spent his career revealing the complex atomic structure of metallic glass and other liquids — sometimes sharing theories with initially resistant minds in the scientific community. 

Matthew Loyd

ORNL’s Matthew Loyd will receive a Department of Energy Office of Science Early Career Research award. 

Robert Saethre has worked to create a LEGO model of the ring injection region of the SNS’ pulsed accelerator that features the new Proton Power Upgrade magnets and vacuum chambers.

Using LEGO® bricks, Robert Saethre has worked to create a model of the ring injection region of the SNS pulsed accelerator that features the new Proton Power Upgrade magnets and vacuum chambers. 

From left, Sedrick Bouknight and Matthias Maiterth of ORNL’s Analytics and AI Methods at Scale group demonstrate the VR capabilities of the Frontier digital twin project's ExaDIGIT framework. Using VR allows Frontier's operators to exam the system's telemetry in a more interactive and intuitive way.

As high-tech companies ramp up construction of massive data centers to meet the business boom in artificial intelligence, one component is becoming an increasingly rare commodity: electricity. Since its formation in 2004, the OLCF has fielded five generations of world-class supercomputing systems that have produced a nearly 2,000 times reduction in energy usage per floating point operation per second, or flops. With decades of experience in making HPC more energy efficient, the OLCF may serve as a resource for best “bang for the buck” practices in a suddenly burgeoning industry.