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: This schematic of tokamak core-pedestal-boundary regions show what will be simulated by an ORNL project applying machine learning to plasma physics modeling. Credit: Giacomin et al., J. Comput. Phys., 463, (2022) 111294, https://doi.org/10.1016/j.jcp.2022.11294

ORNL will lead three new DOE-funded projects designed to bring fusion energy to the grid on a rapid timescale.

ORNL researcher Sreenivasa Jaldanki was recently elevated to IEEE senior member. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Sreenivasa Jaldanki, a researcher in the Grid Systems Modeling and Controls group at the Department of Energy’s Oak Ridge National Laboratory, was recently elevated to senior membership in the Institute of Electrical and Electronics Engineers, or IEEE.

Attendees of SMC23 pose for their annual group photo in downtown Knoxville, TN.

ORNL hosted its annual Smoky Mountains Computational Sciences and Engineering Conference in person for the first time since the COVID-19 pandemic.

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The Oak Ridge Leadership Computing Facility, a Department of Energy Office of Science user facility at ORNL, is pleased to announce a new allocation program for computing time on the IBM AC922 Summit supercomputer.

Chathuddasie Amarasinghe explains her research poster, “Using Microfluidic Mother Machine Devices to Study the Correlated Dynamics of Ribosomes and Chromosomes in Escherichia Coli.” Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Speakers, scientific workshops, speed networking, a student poster showcase and more energized the Annual User Meeting of the Department of Energy’s Center for Nanophase Materials Sciences, or CNMS, Aug. 7-10, near Market Square in downtown Knoxville, Tennessee.

The DEMAND single crystal diffractometer at the High Flux Isotope Reactor, or HFIR, is the latest neutron instrument at the Department of Energy’s Oak Ridge National Laboratory to be equipped with machine learning-assisted software, called ReTIA. Credit: Jeremy Rumsey/ORNL, U.S. Dept. of Energy

Neutron experiments can take days to complete, requiring researchers to work long shifts to monitor progress and make necessary adjustments. But thanks to advances in artificial intelligence and machine learning, experiments can now be done remotely and in half the time.

Madhavi Martin portrait image

Madhavi Martin brings a physicist’s tools and perspective to biological and environmental research at the Department of Energy’s Oak Ridge National Laboratory, supporting advances in bioenergy, soil carbon storage and environmental monitoring, and even helping solve a murder mystery.

Diagram of faults affecting a conventional power system.

Researchers at the Department of Energy’s Oak Ridge National Laboratory are leading the way in understanding the effects of electrical faults in the modern U.S. power grid.

Cody Lloyd stands in front of images of historical nuclear field testing. The green and red dots are the machine learning algorithm recognizing features in the image. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Cody Lloyd became a nuclear engineer because of his interest in the Manhattan Project, the United States’ mission to advance nuclear science to end World War II. As a research associate in nuclear forensics at ORNL, Lloyd now teaches computers to interpret data from imagery of nuclear weapons tests from the 1950s and early 1960s, bringing his childhood fascination into his career

Jonathan Harter, a technical professional in ORNL’s Engineering Science and Technology Directorate, uses a robot and other automated methods to disassemble electric vehicle batteries for recycling or reuse in the electric grid. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

After being stabilized in an ambulance as he struggled to breathe, Jonathan Harter hit a low point. It was 2020, he was very sick with COVID-19, and his job as a lab technician at ORNL was ending along with his research funding.