![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 (2)
- Biology and Environment (44)
- Clean Energy (103)
- Climate and Environmental Systems (4)
- Computational Biology (1)
- Computational Engineering (3)
- Computer Science (7)
- Electricity and Smart Grid (1)
- Fusion and Fission (1)
- Fusion Energy (1)
- Isotopes (3)
- Materials (56)
- Materials for Computing (9)
- Mathematics (1)
- National Security (20)
- Neutron Science (23)
- Nuclear Science and Technology (6)
- Quantum information Science (2)
- Sensors and Controls (1)
- Supercomputing (46)
- Transportation Systems (2)
News Type
News Topics
- (-) Biomedical (28)
- (-) Clean Water (15)
- (-) Cybersecurity (20)
- (-) Environment (79)
- (-) Grid (36)
- (-) Machine Learning (25)
- (-) Molten Salt (7)
- (-) Physics (28)
- (-) Polymers (21)
- (-) Summit (27)
- (-) Transportation (60)
- 3-D Printing/Advanced Manufacturing (74)
- Advanced Reactors (23)
- Artificial Intelligence (45)
- Big Data (24)
- Bioenergy (39)
- Biology (39)
- Biotechnology (10)
- Buildings (33)
- Chemical Sciences (40)
- Climate Change (45)
- Composites (19)
- Computer Science (99)
- Coronavirus (28)
- Critical Materials (23)
- Decarbonization (29)
- Education (3)
- Element Discovery (1)
- Energy Storage (74)
- Exascale Computing (11)
- Fossil Energy (2)
- Frontier (16)
- Fusion (24)
- High-Performance Computing (40)
- Hydropower (6)
- Irradiation (2)
- Isotopes (23)
- ITER (5)
- Materials (92)
- Materials Science (85)
- Mathematics (2)
- Mercury (5)
- Microelectronics (1)
- Microscopy (27)
- Nanotechnology (38)
- National Security (21)
- Net Zero (5)
- Neutron Science (77)
- Nuclear Energy (45)
- Partnerships (30)
- Quantum Computing (14)
- Quantum Science (37)
- Renewable Energy (1)
- Security (12)
- Simulation (15)
- Space Exploration (13)
- Statistics (2)
- Sustainable Energy (75)
- Transformational Challenge Reactor (4)
Media Contacts
![carbon nanospikes carbon nanospikes](/sites/default/files/styles/list_page_thumbnail/public/carbon_nanospikes.jpg?itok=D0GNAvH4)
OAK RIDGE, Tenn., March 1, 2019—ReactWell, LLC, has licensed a novel waste-to-fuel technology from the Department of Energy’s Oak Ridge National Laboratory to improve energy conversion methods for cleaner, more efficient oil and gas, chemical and
![Using neutrons from the TOPAZ beamline, which is optimal for locating hydrogen atoms in materials, ORNL researchers observed a single-crystal neutron diffraction structure of the insoluble carbonate salt formed by absorption of carbon dioxide from the air.](/sites/default/files/styles/list_page_thumbnail/public/2019-02/Carbon_capture_neutrons_0.jpg?h=4137a28c&itok=ZBLNFjNc)
Researchers used neutron scattering at Oak Ridge National Laboratory’s Spallation Neutron Source to investigate the effectiveness of a novel crystallization method to capture carbon dioxide directly from the air.
![As part of a preliminary study, ORNL scientists used critical location data collected from Twitter to map the location of certain power outages across the United States.](/sites/default/files/styles/list_page_thumbnail/public/2019-02/PowerOutageTweets_map_0.png?h=6448fdc1&itok=AUit-O2Y)
Gleaning valuable data from social platforms such as Twitter—particularly to map out critical location information during emergencies— has become more effective and efficient thanks to Oak Ridge National Laboratory.
![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).
![Researchers used machine learning methods on the ORNL Compute and Data Environment for Science, or CADES, to map vegetation communities in the Kougarok Watershed on the Seward Peninsula of Alaska. The colors denote different types of vegetation, such as w Researchers used machine learning methods on the ORNL Compute and Data Environment for Science, or CADES, to map vegetation communities in the Kougarok Watershed on the Seward Peninsula of Alaska. The colors denote different types of vegetation, such as w](/sites/default/files/styles/list_page_thumbnail/public/rs2019_highlight_plot_3d.png?itok=5bROV_ys)
A team of scientists led by Oak Ridge National Laboratory used machine learning methods to generate a high-resolution map of vegetation growing in the remote reaches of the Alaskan tundra.
![At the salt–metal interface, thermodynamic forces drive chromium from the bulk of a nickel alloy, leaving a porous, weakened layer. Impurities in the salt drive further corrosion of the structural material. Credit: Stephen Raiman/Oak Ridge National Labora At the salt–metal interface, thermodynamic forces drive chromium from the bulk of a nickel alloy, leaving a porous, weakened layer. Impurities in the salt drive further corrosion of the structural material. Credit: Stephen Raiman/Oak Ridge National Labora](/sites/default/files/styles/list_page_thumbnail/public/story%20tip%20image%20BW%20only.jpg?itok=Vbc0iTLt)
Oak Ridge National Laboratory scientists analyzed more than 50 years of data showing puzzlingly inconsistent trends about corrosion of structural alloys in molten salts and found one factor mattered most—salt purity.
![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.
![Picture2.png Picture2.png](/sites/default/files/styles/list_page_thumbnail/public/Picture2_1.png?itok=IV4n9XEh)
Oak Ridge National Laboratory scientists studying fuel cells as a potential alternative to internal combustion engines used sophisticated electron microscopy to investigate the benefits of replacing high-cost platinum with a lower cost, carbon-nitrogen-manganese-based catalyst.
![mirrorAsymmetry-NPDGamma_ORNL.jpg mirrorAsymmetry-NPDGamma_ORNL.jpg](/sites/default/files/styles/list_page_thumbnail/public/mirrorAsymmetry-NPDGamma_ORNL.jpg?itok=POtcSu48)
A team of scientists has for the first time measured the elusive weak interaction between protons and neutrons in the nucleus of an atom. They had chosen the simplest nucleus consisting of one neutron and one proton for the study.