![Weyl semimetal](/sites/default/files/styles/featured_square_large/public/2024-08/Picture4.jpg?h=b38bf506&itok=nYXXiLDs)
Filter News
Area of Research
News Type
News Topics
- (-) Cybersecurity (2)
- (-) Frontier (13)
- (-) Isotopes (6)
- (-) Machine Learning (9)
- (-) Microscopy (9)
- (-) Quantum Computing (11)
- (-) Security (2)
- (-) Simulation (10)
- (-) Space Exploration (3)
- 3-D Printing/Advanced Manufacturing (7)
- Advanced Reactors (1)
- Artificial Intelligence (22)
- Big Data (13)
- Bioenergy (7)
- Biology (6)
- Biomedical (11)
- Biotechnology (1)
- Buildings (3)
- Chemical Sciences (8)
- Clean Water (3)
- Climate Change (12)
- Composites (2)
- Computer Science (49)
- Coronavirus (7)
- Decarbonization (5)
- Energy Storage (9)
- Environment (20)
- Exascale Computing (12)
- Fossil Energy (1)
- Fusion (3)
- Grid (3)
- High-Performance Computing (20)
- Materials (25)
- Materials Science (28)
- Mathematics (1)
- Nanotechnology (12)
- National Security (3)
- Net Zero (1)
- Neutron Science (40)
- Nuclear Energy (12)
- Partnerships (3)
- Physics (15)
- Polymers (6)
- Quantum Science (10)
- Software (1)
- Summit (21)
- Sustainable Energy (5)
- Transformational Challenge Reactor (2)
- Transportation (9)
Media Contacts
![Larry Allard](/sites/default/files/styles/list_page_thumbnail/public/2022-08/Allard.png?h=748cb951&itok=GvagcEmh)
Larry Allard, a distinguished research staff member at Oak Ridge National Laboratory, has been named a Fellow of the Microanalysis Society.
![Travis Humble. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-08/2022-P07054_2.jpg?h=8f9cfe54&itok=SUY5L40C)
Travis Humble has been named director of the Quantum Science Center headquartered at ORNL. The QSC is a multi-institutional partnership that spans industry, academia and government institutions and is tasked with uncovering the full potential of quantum materials, sensors and algorithms.
![Scattering-type scanning near-field optical microscopy, a nondestructive technique in which the tip of the probe of a microscope scatters pulses of light to generate a picture of a sample, allowed the team to obtain insights into the composition of plant cell walls. Credit: Ali Passian/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-06/Picture1_0.jpg?h=da2f9885&itok=_QN9qoqF)
To optimize biomaterials for reliable, cost-effective paper production, building construction, and biofuel development, researchers often study the structure of plant cells using techniques such as freezing plant samples or placing them in a vacuum.
![Oak Ridge National Laboratory’s Mitch Allmond works with the Facility for Rare Isotope Beams Decay Station initiator, which combined diverse detectors for FRIB’s first experiment. Credit: Robert Grzywacz/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-06/FRIB1.jpg?h=429981e8&itok=sFq0uTlk)
Two decades in the making, a new flagship facility for nuclear physics opened on May 2, and scientists from the Department of Energy’s Oak Ridge National Laboratory have a hand in 10 of its first 34 experiments.
![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.
![Earth Day](/sites/default/files/styles/list_page_thumbnail/public/2022-04/Earth%20image.png?h=8f74817f&itok=5rQ_su9Z)
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.
![Exploring the smallest distance scales with particle colliders often requires detailed calculations of the spectra of outgoing particles (smallest filled green circles). Image Credit: Benjamin Nachman, Berkeley Lab](/sites/default/files/styles/list_page_thumbnail/public/2022-04/Nachman-schematic_0.png?h=ba0ef1c4&itok=11-E7fDz)
Lawrence Berkeley National Laboratory physicists Christian Bauer, Marat Freytsis and Benjamin Nachman have leveraged an IBM Q quantum computer through the Oak Ridge Leadership Computing Facility’s Quantum Computing User Program to capture part of a
![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.
![An ORNL-led team studied the SARS-CoV-2 spike protein in the trimer state, shown here, to pinpoint structural transitions that could be disrupted to destabilize the protein and negate its harmful effects. Credit: Debsindhu Bhowmik/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-01/sars_cov_2_bk.png?h=05c2797f&itok=jQ2D9aTr)
To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.
![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.