![Weyl semimetal](/sites/default/files/styles/featured_square_large/public/2024-08/Picture4.jpg?h=b38bf506&itok=nYXXiLDs)
Filter News
Area of Research
- Advanced Manufacturing (4)
- Biology and Environment (13)
- Clean Energy (25)
- Computational Engineering (1)
- Computer Science (4)
- Electricity and Smart Grid (2)
- Functional Materials for Energy (1)
- Fusion and Fission (1)
- Materials (14)
- Materials for Computing (1)
- National Security (12)
- Neutron Science (4)
- Supercomputing (14)
News Topics
- (-) Composites (29)
- (-) Machine Learning (48)
- (-) Microelectronics (4)
- 3-D Printing/Advanced Manufacturing (125)
- Advanced Reactors (34)
- Artificial Intelligence (95)
- Big Data (58)
- Bioenergy (92)
- Biology (100)
- Biomedical (59)
- Biotechnology (23)
- Buildings (59)
- Chemical Sciences (69)
- Clean Water (30)
- Climate Change (103)
- Computer Science (194)
- Coronavirus (46)
- Critical Materials (29)
- Cybersecurity (35)
- Decarbonization (81)
- Education (4)
- Element Discovery (1)
- Emergency (2)
- Energy Storage (111)
- Environment (198)
- Exascale Computing (39)
- Fossil Energy (6)
- Frontier (44)
- Fusion (55)
- Grid (65)
- High-Performance Computing (88)
- Hydropower (11)
- Irradiation (3)
- Isotopes (54)
- ITER (7)
- Materials (145)
- Materials Science (144)
- Mathematics (9)
- Mercury (12)
- Microscopy (51)
- Molten Salt (8)
- Nanotechnology (60)
- National Security (68)
- Net Zero (14)
- Neutron Science (133)
- Nuclear Energy (110)
- Partnerships (49)
- Physics (63)
- Polymers (33)
- Quantum Computing (35)
- Quantum Science (70)
- Renewable Energy (2)
- Security (24)
- Simulation (49)
- Software (1)
- Space Exploration (25)
- Statistics (3)
- Summit (59)
- Sustainable Energy (129)
- Transformational Challenge Reactor (7)
- Transportation (97)
Media Contacts
![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.
![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.
![A new process developed by Oak Ridge National Laboratory leverages deep learning techniques to study cell movements in a simulated environment, guided by simple physics rules similar to video-game play. Credit: MSKCC and UTK](/sites/default/files/styles/list_page_thumbnail/public/2022-01/Observed%20data%20AI%20story%20tip.jpg?h=8e5dac0a&itok=wrAOsfIs)
Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity.
![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.
![Ten scientists from the Department of Energy’s Oak Ridge National Laboratory are among the world’s most highly cited researchers. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-11/2008-P01679_0.jpg?h=6acbff97&itok=ewBiiftq)
Ten scientists from the Department of Energy’s Oak Ridge National Laboratory are among the world’s most highly cited researchers, according to a bibliometric analysis conducted by the scientific publication analytics firm Clarivate.
![Oak Ridge National Laboratory scientist Tomonori Saito shows a 3D-printed sandcastle at the DOE Manufacturing Demonstration Facility at ORNL. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-11/2019-P16307.jpg?h=036a71b7&itok=_ikjcodd)
Researchers at ORNL designed a novel polymer to bind and strengthen silica sand for binder jet additive manufacturing, a 3D-printing method used by industries for prototyping and part production.
![ORNL researchers produced self-healable and highly adhesive elastomers, proving they self-repair in ambient conditions and underwater. This project garnered a 2021 R&D 100 Award. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-10/Unbreakable-bond-copy.jpg?h=cd715a88&itok=cQeEYNZn)
Research teams from the Department of Energy’s Oak Ridge National Laboratory and their technologies have received seven 2021 R&D 100 Awards, plus special recognition for a COVID-19-related project.
![A 3D printed thermal protection shield, produced by ORNL researchers for NASA, is part of a cargo spacecraft bound for the International Space Station. The shield was printed at the Department of Energy’s Manufacturing Demonstration Facility at ORNL. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-07/Sanded5.jpg?h=dce12e0c&itok=_8wzeG94)
A research team at Oak Ridge National Laboratory have 3D printed a thermal protection shield, or TPS, for a capsule that will launch with the Cygnus cargo spacecraft as part of the supply mission to the International Space Station.
![ORNL, in collaboration with Cincinnati, Inc., used the Big Area Additive Manufacturing machine to 3D print a mold made of recycled thermoplastic composite and syntactic foam, demonstrating the potential for multimaterials in large-scale applications. Credit: ORNL/U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-05/MM%20Mold_7_0.jpg?h=151f6e80&itok=DGoZAbvk)
Oak Ridge National Laboratory researchers, in collaboration with Cincinnati Inc., demonstrated the potential for using multimaterials and recycled composites in large-scale applications by 3D printing a mold that replicated a single facet of a
![Oak Ridge National Laboratory’s MENNDL AI software system can design thousands of neural networks in a matter of hours. One example uses a driving simulator to evaluate a network’s ability to perceive objects under various lighting conditions. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-04/CARLA%20MENNDL%20sim001_1.png?h=e2caa22a&itok=tvE9seMo)
The Department of Energy’s Oak Ridge National Laboratory has licensed its award-winning artificial intelligence software system, the Multinode Evolutionary Neural Networks for Deep Learning, to General Motors for use in vehicle technology and design.