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Media Contacts
![Logan Sturm, Alvin M. Weinberg Fellow at ORNL, creates a mashup between additive manufacturing and cybersecurity research. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-05/sturm-lab.jpg?h=1de2f7a8&itok=nYiuVTGx)
How an Alvin M. Weinberg Fellow is increasing security for critical infrastructure components
![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](/sites/default/files/styles/list_page_thumbnail/public/2022-04/2022-G00330_KESER%20Illustration_0.jpg?h=1cb48fc4&itok=c6ZuDdDg)
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.
![Andrew Sutton joined ORNL in 2020 to guide a newly formed team that focuses on chemical process scale-up in advanced manufacturing. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-04/2022-P01204.jpg?h=8f9cfe54&itok=n2ca9jZz)
When Andrew Sutton arrived at ORNL in late 2020, he knew the move would be significant in more ways than just a change in location.
![ORNL research scientist Christa Brelsford explained a mathematical framework she developed in 2018, which showed increased availability of infrastructure didn’t necessarily reduce inequality in its access. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-04/image001.jpg?h=1579b22a&itok=XzIna_Uc)
Unequal access to modern infrastructure is a feature of growing cities, according to a study published this week in the Proceedings of the National Academy of Sciences
![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](/sites/default/files/styles/list_page_thumbnail/public/2022-04/Nucleic%20Cover%20Illustration.jpg?h=4a9d1e17&itok=iw81emAt)
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](/sites/default/files/styles/list_page_thumbnail/public/2022-01/QLAN%20submit_0.jpg?h=cd715a88&itok=JV1MjQHH)
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](/sites/default/files/styles/list_page_thumbnail/public/2022-01/thermosipho_collabfold2_0.jpg?h=3432ff3c&itok=4xhLbjKZ)
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](/sites/default/files/styles/list_page_thumbnail/public/2021-12/2021-P05927.jpg?h=c6980913&itok=INL2tsOt)
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.
![U.S. Secretary of Energy Granholm tours ORNL’s world-class science facilities](/sites/default/files/styles/list_page_thumbnail/public/2021-11/2021-P09409.jpg?h=036a71b7&itok=C8b0_-Vk)
Energy Secretary Jennifer Granholm visited ORNL on Nov. 22 for a two-hour tour, meeting top scientists and engineers as they highlighted projects and world-leading capabilities that address some of the country’s most complex research and technical challenges.
![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](/sites/default/files/styles/list_page_thumbnail/public/2021-11/Quantum%20Illustration%20V3_0.png?h=2e111cc1&itok=Bth5wkD4)
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.