![Debjani Singh](/sites/default/files/styles/featured_square_large/public/2024-08/2024-P12408.jpg?h=8f9cfe54&itok=bP5F6U4Y)
Filter News
Area of Research
- Advanced Manufacturing (4)
- Biology and Environment (19)
- Clean Energy (72)
- Computational Biology (1)
- Computational Engineering (1)
- Computer Science (1)
- Fuel Cycle Science and Technology (1)
- Fusion and Fission (16)
- Fusion Energy (8)
- Isotope Development and Production (1)
- Isotopes (18)
- Materials (33)
- Materials for Computing (7)
- National Security (19)
- Neutron Science (15)
- Nuclear Science and Technology (23)
- Nuclear Systems Modeling, Simulation and Validation (2)
- Quantum information Science (2)
- Supercomputing (22)
- Transportation Systems (2)
News Type
News Topics
- (-) Advanced Reactors (25)
- (-) Biomedical (38)
- (-) Cybersecurity (26)
- (-) Fossil Energy (2)
- (-) Isotopes (34)
- (-) Nuclear Energy (60)
- (-) Partnerships (30)
- (-) Space Exploration (13)
- (-) Transportation (72)
- 3-D Printing/Advanced Manufacturing (87)
- Artificial Intelligence (50)
- Big Data (31)
- Bioenergy (56)
- Biology (61)
- Biotechnology (14)
- Buildings (42)
- Chemical Sciences (49)
- Clean Water (22)
- Climate Change (60)
- Composites (22)
- Computer Science (112)
- Coronavirus (34)
- Critical Materials (25)
- Decarbonization (44)
- Education (3)
- Element Discovery (1)
- Energy Storage (88)
- Environment (116)
- Exascale Computing (14)
- Frontier (19)
- Fusion (31)
- Grid (43)
- High-Performance Computing (49)
- Hydropower (8)
- Irradiation (2)
- ITER (6)
- Machine Learning (30)
- Materials (99)
- Materials Science (97)
- Mathematics (6)
- Mercury (9)
- Microelectronics (1)
- Microscopy (36)
- Molten Salt (7)
- Nanotechnology (44)
- National Security (37)
- Net Zero (7)
- Neutron Science (85)
- Physics (44)
- Polymers (26)
- Quantum Computing (15)
- Quantum Science (39)
- Renewable Energy (1)
- Security (18)
- Simulation (19)
- Statistics (2)
- Summit (29)
- Sustainable Energy (89)
- Transformational Challenge Reactor (4)
Media Contacts
![In ORNL’s Low Activation Materials Development and Analysis Laboratory, Field makes use of a transmission electron microscope to examine a sample made with a focused ion beam. He investigates the defects produced in a FeCrAl alloy bombarded with neutrons in HFIR. Credit: Carlos Jones/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2019-03/2018-P08721%20%28first%29.jpg?h=8f9cfe54&itok=sRzTcetb)
Kevin Field at the Department of Energy’s Oak Ridge National Laboratory synthesizes and scrutinizes materials for nuclear power systems that must perform safely and efficiently over decades of irradiation.
![Illustration of the intricate organization of the PKA structure, wherein different parts of the protein are connected through elaborate hydrogen bonding networks (dashed yellow lines), glued together by the hydrophobic assemblies (light blue and orange volumes)—all working together to build the functional active site. Insert shows protonation of the transferred phosphoryl group (cyan mesh) and its many interactions with water and the active site amino acid residues. Credit: Jill Hemman/ORNL](/sites/default/files/styles/list_page_thumbnail/public/2019-03/19-G00204_MR_graphic_Kovalevsky_proof5_2.png?h=b7fbb1a9&itok=wrZFNX-o)
OAK RIDGE, Tenn., March 20, 2019—Direct observations of the structure and catalytic mechanism of a prototypical kinase enzyme—protein kinase A or PKA—will provide researchers and drug developers with significantly enhanced abilities to understand and treat fatal diseases and neurological disorders such as cancer, diabetes, and cystic fibrosis.
![Neutron scattering allowed direct observation of how aurein induces lateral segregation in the bacteria membranes, which creates instability in the membrane structure. This instability causes the membranes to fail, making harmful bacteria less effective.](/sites/default/files/styles/list_page_thumbnail/public/2019-03/Neutrons-FightingSuperbugs_0.jpg?h=e4b73f5a&itok=ebOQD-Mr)
As the rise of antibiotic-resistant bacteria known as superbugs threatens public health, Oak Ridge National Laboratory’s Shuo Qian and Veerendra Sharma from the Bhaba Atomic Research Centre in India are using neutron scattering to study how an antibacterial peptide interacts with and fights harmful bacteria.
![ORNL nuclear engineer Chris Petrie](/sites/default/files/styles/list_page_thumbnail/public/2019-03/Nuclear-Follow_your_senses_ORNL_2.jpg?h=7d719b4a&itok=xTiBlfq8)
Oak Ridge National Laboratory is using ultrasonic additive manufacturing to embed highly accurate fiber optic sensors in heat- and radiation-resistant materials, allowing for real-time monitoring that could lead to greater insights and safer reactors.
![Transportation Energy Data Book Edition 37](/sites/default/files/styles/list_page_thumbnail/public/2019-03/Transportation-Logging_the_miles_ORNL_0.jpg?h=ade3edc7&itok=wGiEijHl)
Oak Ridge National Laboratory’s latest Transportation Energy Data Book: Edition 37 reports that the number of vehicles nationwide is growing faster than the population, with sales more than 17 million since 2015, and the average household vehicle travels more than 11,000 miles per year.
![(From left) ORNL Associate Laboratory Director for Computing and Computational Sciences Jeff Nichols; ORNL Health Data Sciences Institute Director Gina Tourassi; DOE Deputy Under Secretary for Science Thomas Cubbage; ORNL Task Lead for Biostatistics Blair Christian; and ORNL Research Scientist Ioana Danciu were invited to the White House to showcase an ORNL-developed digital tool aimed at better matching cancer patients with clinical trials.](/sites/default/files/styles/list_page_thumbnail/public/2019-03/TourassiWH%5B1%5D.png?h=26b5064d&itok=HUC2iYmE)
OAK RIDGE, Tenn., March 4, 2019—A team of researchers from the Department of Energy’s Oak Ridge National Laboratory Health Data Sciences Institute have harnessed the power of artificial intelligence to better match cancer patients with clinical trials.
![An ORNL-developed graphite foam, which could be used in plasma-facing components in fusion reactors, performed well during testing at the Wendlestein 7-X stellarator in Germany.](/sites/default/files/styles/list_page_thumbnail/public/2019-02/W7-XPlasmaExposure_0.jpg?h=d5d04e3b&itok=uKiauhdF)
Scientists have tested a novel heat-shielding graphite foam, originally created at Oak Ridge National Laboratory, at Germany’s Wendelstein 7-X stellarator with promising results for use in plasma-facing components of fusion reactors.
![Laminations such as these are compiled to form the core of modern electric vehicle motors. ORNL has developed a software toolkit to speed the development of new motor designs and to improve the accuracy of their real-world performance.](/sites/default/files/styles/list_page_thumbnail/public/2019-02/Motors_OeRSTED_0.jpg?h=af53702d&itok=mT24R4WI)
Oak Ridge National Laboratory scientists have created open source software that scales up analysis of motor designs to run on the fastest computers available, including those accessible to outside users at the Oak Ridge Leadership Computing Facility.
OAK RIDGE, Tenn., Feb. 12, 2019—A team of researchers from the Department of Energy’s Oak Ridge and Los Alamos National Laboratories has partnered with EPB, a Chattanooga utility and telecommunications company, to demonstrate the effectiveness of metro-scale quantum key distribution (QKD).
![ORNL scientists used commuting behavior data from East Tennessee to demonstrate how machine learning models can easily accept new data, quickly re-train themselves and update predictions about commuting patterns. Credit: April Morton/Oak Ridge National La ORNL scientists used commuting behavior data from East Tennessee to demonstrate how machine learning models can easily accept new data, quickly re-train themselves and update predictions about commuting patterns. Credit: April Morton/Oak Ridge National La](/sites/default/files/styles/list_page_thumbnail/public/study_area_one_dest_2.jpg?itok=2cWFkQvW)
Oak Ridge National Laboratory geospatial scientists who study the movement of people are using advanced machine learning methods to better predict home-to-work commuting patterns.