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Media Contacts
![The ORNL researchers’ findings may enable better detection of uranium tetrafluoride hydrate, a little-studied byproduct of the nuclear fuel cycle, and better understanding of how environmental conditions influence the chemical behavior of fuel cycle materials. Credit: Kevin Pastoor/Colorado School of Mines](/sites/default/files/styles/list_page_thumbnail/public/2022-05/UF4%20hydrate.png?h=d318f057&itok=spT-Dg48)
ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.
![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.
![Mars Rover 2020](/sites/default/files/styles/list_page_thumbnail/public/2019-03/Mars_0.jpg?h=c44fcfa1&itok=gSstQOJO)
More than 50 current employees and recent retirees from ORNL received Department of Energy Secretary’s Honor Awards from Secretary Jennifer Granholm in January as part of project teams spanning the national laboratory system. The annual awards recognized 21 teams and three individuals for service and contributions to DOE’s mission and to the benefit of the nation.
![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.
![Miaofang Chi, a scientist in the Center for Nanophase Materials Sciences, received the 2021 Director’s Award for Outstanding Individual Accomplishment in Science and Technology. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-12/2021-P09692_0.jpg?h=9bbd619b&itok=4iANdQKl)
A world-leading researcher in solid electrolytes and sophisticated electron microscopy methods received Oak Ridge National Laboratory’s top science honor today for her work in developing new materials for batteries. The announcement was made during a livestreamed Director’s Awards event hosted by ORNL Director Thomas Zacharia.
![Watermarks, considered the most efficient mechanisms for tracking how complete streaming data processing is, allow new tasks to be processed immediately after prior tasks are completed. Image Credit: Nathan Armistead, ORNL](/sites/default/files/styles/list_page_thumbnail/public/2021-11/Watermarks%5B1%5D.jpg?h=f7cc716d&itok=Er5k0WwK)
A team of collaborators from ORNL, Google Inc., Snowflake Inc. and Ververica GmbH has tested a computing concept that could help speed up real-time processing of data that stream on mobile and other electronic devices.
![INCITE_narrow_logo](/sites/default/files/styles/list_page_thumbnail/public/2021-11/incite_narrow_1.png?h=a08abdbb&itok=2O5LBHgQ)
The U.S. Department of Energy’s Office of Science announced allocations of supercomputer access to 51 high-impact computational science projects for 2022 through its Innovative and Novel Computational Impact on Theory and Experiment, or INCITE, program.
![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.
![An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-06/frame1.png?h=d1cb525d&itok=51pwBWyP)
An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.