Filter News
Area of Research
- (-) Supercomputing (10)
- Advanced Manufacturing (1)
- Biology and Environment (16)
- Biology and Soft Matter (1)
- Clean Energy (14)
- Computational Biology (1)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Isotopes (1)
- Materials (20)
- Materials for Computing (1)
- National Security (10)
- Neutron Science (1)
News Topics
- (-) Biomedical (4)
- (-) Chemical Sciences (2)
- (-) Cybersecurity (1)
- (-) Machine Learning (5)
- (-) Microscopy (2)
- Artificial Intelligence (7)
- Big Data (3)
- Bioenergy (2)
- Biology (5)
- Buildings (3)
- Climate Change (4)
- Computer Science (10)
- Coronavirus (3)
- Critical Materials (1)
- Decarbonization (2)
- Energy Storage (3)
- Environment (3)
- Exascale Computing (6)
- Frontier (7)
- Grid (2)
- High-Performance Computing (8)
- Materials (8)
- Materials Science (5)
- Nanotechnology (3)
- National Security (3)
- Neutron Science (1)
- Partnerships (1)
- Physics (1)
- Quantum Computing (7)
- Quantum Science (4)
- Security (2)
- Simulation (5)
- Space Exploration (1)
- Summit (7)
- Sustainable Energy (2)
Media Contacts
![Michelle Kidder received the lab’s Director’s Award for Outstanding Individual Accomplishment in Science and Technology for her decades-long work mentoring students, teachers and early-career staff. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-11/2018-P04785_0.png?h=7a8a8cdf&itok=hysTNqXX)
Laboratory Director Thomas Zacharia presented five Director’s Awards during Saturday night's annual Awards Night event hosted by UT-Battelle, which manages ORNL for the Department of Energy.
![ORNL’s RapidCure improves lithium-ion electrode production by producing electrodes faster, reducing the energy necessary for manufacturing and eliminating the need for a solvent recycling unit. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-08/RapidCure_0.jpg?h=def3cf70&itok=BFENW6Cu)
Researchers at the Department of Energy’s Oak Ridge National Laboratory and their technologies have received seven 2022 R&D 100 Awards, plus special recognition for a battery-related green technology product.
![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.
![Frontier has arrived, and ORNL is preparing for science on Day One. Credit: Carlos Jones/ORNL, Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-05/Frontier%20endcap.jpg?h=c6980913&itok=5i5DUzQz)
The Frontier supercomputer at the Department of Energy’s Oak Ridge National Laboratory earned the top ranking today as the world’s fastest on the 59th TOP500 list, with 1.1 exaflops of performance. The system is the first to achieve an unprecedented level of computing performance known as exascale, a threshold of a quintillion calculations per second.
![MDF Exterior](/sites/default/files/styles/list_page_thumbnail/public/2022-06/2021-p07609.jpg?h=be3e4b3a&itok=YfKK7Wy2)
ORNL scientists will present new technologies available for licensing during the annual Technology Innovation Showcase. The event is 9 a.m. to 3 p.m. Thursday, June 16, at the Manufacturing Demonstration Facility at ORNL’s Hardin Valley campus.
![A smart approach to microscopy and imaging developed at Oak Ridge National Laboratory could drive discoveries in materials for future technologies. Credit: Adam Malin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-05/PFC%20Surface%20v3%20300dpi_1.jpg?h=9c3ba2fc&itok=s8arZbEt)
Researchers at ORNL are teaching microscopes to drive discoveries with an intuitive algorithm, developed at the lab’s Center for Nanophase Materials Sciences, that could guide breakthroughs in new materials for energy technologies, sensing and computing.
![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.
![Genetic analysis revealed connections between inflammatory activity and development of atomic dermatitis, according to researchers from the UPenn School of Medicine, the Perelman School of Medicine, and Oak Ridge National Laboratory. Credit: Kang Ko/UPenn](/sites/default/files/styles/list_page_thumbnail/public/2022-02/Graves-AD_0.jpg?h=46d8a70d&itok=77AW7Swv)
University of Pennsylvania researchers called on computational systems biology expertise at Oak Ridge National Laboratory to analyze large datasets of single-cell RNA sequencing from skin samples afflicted with atopic dermatitis.
![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.