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Media Contacts
![Howard Wilson and Gary Staebler](/sites/default/files/styles/list_page_thumbnail/public/2023-12/Wilson-Staebler_0.png?h=ca9e32dd&itok=fLUb03Ia)
Two fusion energy leaders have joined ORNL in the Fusion and Fission Energy and Science Directorate, or FFESD.
![QSC Director Travis Humble, who gave a lunchtime talk on transitioning good ideas to device development, learns about one of the many quantum research efforts featured at the poster session. Credit: Alonda Hines/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-12/2023-P16851.jpg?h=036a71b7&itok=7MltSEYq)
On Nov. 1, about 250 employees at Oak Ridge National Laboratory gathered in person and online for Quantum on the Quad, an event designed to collect input for a quantum roadmap currently in development. This document will guide the laboratory's efforts in quantum science and technology, including strategies for expanding its expertise to all facets of the field.
![INFUSE logo](/sites/default/files/styles/list_page_thumbnail/public/2023-12/infuse_logo-011_0_0.jpeg?h=855b71fd&itok=vmDC02PO)
ORNL is leading three research collaborations with fusion industry partners through the Innovation Network for FUSion Energy, or INFUSE, program that will focus on resolving technical challenges and developing innovative solutions to make practical fusion energy a reality.
![ORNL researchers are establishing a digital thread of data, algorithms and workflows to produce a continuously updated model of earth systems.](/sites/default/files/styles/list_page_thumbnail/public/2023-11/MicrosoftTeams-image%20%2823%29_0.png?h=c6980913&itok=cK99Pg3y)
Digital twins are exactly what they sound like: virtual models of physical reality that continuously update to reflect changes in the real world.
![text](/sites/default/files/styles/list_page_thumbnail/public/2023-10/2023-P01771.jpg?h=c6980913&itok=5iFiGWPl)
Waiting for answers surrounding a healthcare condition can be as stressful as the condition itself. Maria Mahbub, a research collaborator at Oak Ridge National Laboratory, is developing technology that could help providers and patients get answers sooner.
![Sarah Walters portrait](/sites/default/files/styles/list_page_thumbnail/public/2023-10/CSJ_0837%20-%20R.jpg?h=a64773ff&itok=TGiNzHPR)
Walters is working with a team of geographers, linguists, economists, data scientists and software engineers to apply cultural knowledge and patterns to open-source data in an effort to document and report patterns of human movement through previously unstudied spaces.
![: 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](/sites/default/files/styles/list_page_thumbnail/public/2023-10/Fusion%20tokamak%20simulator.png?h=e1e3aba4&itok=kiVnri5A)
ORNL will lead three new DOE-funded projects designed to bring fusion energy to the grid on a rapid timescale.
![Attendees of SMC23 pose for their annual group photo in downtown Knoxville, TN.](/sites/default/files/styles/list_page_thumbnail/public/2023-09/2023-P12048.jpg?h=b18108c1&itok=nPUCBfNi)
ORNL hosted its annual Smoky Mountains Computational Sciences and Engineering Conference in person for the first time since the COVID-19 pandemic.
![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](/sites/default/files/styles/list_page_thumbnail/public/2023-09/DEMAND%20thumbnail%20image_0.jpg?h=c673cd1c&itok=5YAVwaP6)
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.
![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](/sites/default/files/styles/list_page_thumbnail/public/2023-08/2023-P05797_0.jpg?h=4a7d1ed4&itok=S8h_wvJX)
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