Filter News
Area of Research
- (-) Materials (46)
- (-) Supercomputing (46)
- Advanced Manufacturing (5)
- Biological Systems (1)
- Biology and Environment (50)
- Clean Energy (85)
- Computational Biology (1)
- Computer Science (1)
- Electricity and Smart Grid (2)
- Functional Materials for Energy (2)
- Fusion and Fission (7)
- Materials for Computing (4)
- National Security (13)
- Neutron Science (10)
- Nuclear Science and Technology (3)
- Quantum information Science (1)
News Type
News Topics
- (-) 3-D Printing/Advanced Manufacturing (12)
- (-) Big Data (14)
- (-) Bioenergy (9)
- (-) Energy Storage (17)
- (-) Grid (4)
- (-) High-Performance Computing (27)
- (-) Physics (20)
- (-) Transformational Challenge Reactor (3)
- Advanced Reactors (3)
- Artificial Intelligence (25)
- Biology (9)
- Biomedical (9)
- Biotechnology (1)
- Buildings (4)
- Chemical Sciences (14)
- Clean Water (2)
- Climate Change (15)
- Composites (3)
- Computer Science (55)
- Coronavirus (8)
- Critical Materials (1)
- Cybersecurity (4)
- Decarbonization (5)
- Environment (22)
- Exascale Computing (14)
- Frontier (16)
- Fusion (5)
- Irradiation (1)
- Isotopes (8)
- ITER (1)
- Machine Learning (9)
- Materials (46)
- Materials Science (38)
- Mathematics (1)
- Microscopy (16)
- Molten Salt (1)
- Nanotechnology (21)
- National Security (4)
- Net Zero (1)
- Neutron Science (19)
- Nuclear Energy (14)
- Partnerships (4)
- Polymers (7)
- Quantum Computing (12)
- Quantum Science (12)
- Security (3)
- Simulation (12)
- Software (1)
- Space Exploration (3)
- Summit (22)
- Sustainable Energy (8)
- Transportation (9)
Media Contacts
![The AI agent, incorporating a language model-based molecular generator and a graph neural network-based molecular property predictor, processes a set of user-provided molecules (green) and produces/suggests new molecules (red) with desired chemical/physical properties (i.e. excitation energy). Image credit: Pilsun You, Jason Smith/ORNL, U.S. DOE](/sites/default/files/styles/list_page_thumbnail/public/2023-12/image001_0.png?h=16ec4b77&itok=KtCjteSq)
A team of computational scientists at ORNL has generated and released datasets of unprecedented scale that provide the ultraviolet visible spectral properties of over 10 million organic molecules.
![Scientists at Oak Ridge National Laboratory contributed to several chapters of the Fifth National Climate Assessment, providing expertise in complex ecosystem processes, energy systems, human dynamics, computational science and Earth-scale modeling. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-11/EarthSystem_2023NCA5.jpg?h=d1cb525d&itok=r043oHRM)
Scientists at ORNL used their knowledge of complex ecosystem processes, energy systems, human dynamics, computational science and Earth-scale modeling to inform the nation’s latest National Climate Assessment, which draws attention to vulnerabilities and resilience opportunities in every region of the country.
![Researchers used Frontier, the world’s first exascale supercomputer, to simulate a magnesium system of nearly 75,000 atoms and the National Energy Research Computing Center’s Perlmutter supercomputer to simulate a quasicrystal structure, above, in a ytterbium-cadmium alloy. Credit: Vikram Gavini](/sites/default/files/styles/list_page_thumbnail/public/2023-11/Gavini_quasiCrystal_0.png?h=c85002af&itok=6QPdbiZo)
Researchers used the world’s first exascale supercomputer to run one of the largest simulations of an alloy ever and achieve near-quantum accuracy.
![Frontier’s exascale power enables the Energy, Exascale and Earth System Model-Multiscale Modeling Framework — or E3SM-MMF — project to run years’ worth of climate simulations at unprecedented speed and scale. Credit: Mark Taylor/Sandia National Laboratories, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-11/E3SM-MMF.png?h=21f5ce54&itok=UAeMXyqa)
The world’s first exascale supercomputer will help scientists peer into the future of global climate change and open a window into weather patterns that could affect the world a generation from now.
![Hilda Klasky](/sites/default/files/styles/list_page_thumbnail/public/2023-11/Hilda%20Klasky.jpg?h=dbae05b8&itok=CPlpl2-D)
Hilda Klasky, an R&D staff member in the Scalable Biomedical Modeling group at ORNL, has been selected as a senior member of the Association of Computing Machinery, or ACM.
![red and green sphagnum moss](/sites/default/files/styles/list_page_thumbnail/public/2023-10/2022-P05000_0.jpg?h=971886de&itok=7xwMranw)
A type of peat moss has surprised scientists with its climate resilience: Sphagnum divinum is actively speciating in response to hot, dry conditions.
![The sun sets behind the ORNL Visitor Center in this aerial photo from April 2023. Credit: Kase Clapp/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-10/sunset_visitor-center_0.png?h=10d202d3&itok=jLImPT0R)
In fiscal year 2023 — Oct. 1–Sept. 30, 2023 — Oak Ridge National Laboratory was awarded more than $8 million in technology maturation funding through the Department of Energy’s Technology Commercialization Fund, or TCF.
![Photo collage with text that reads " A New era of discovery"](/sites/default/files/styles/list_page_thumbnail/public/2023-10/LRP%20Image_0.png?h=d1cb525d&itok=m-0J8hDE)
ORNL, a bastion of nuclear physics research for the past 80 years, is poised to strengthen its programs and service to the United States over the next decade if national recommendations of the Nuclear Science Advisory Committee, or NSAC, are enacted.
![Conceptual art depicts an atomic nucleus and merging neutron stars, respectively, areas of study in ORNL-led projects called NUCLEI and ENAF within the Scientific Discovery through Advanced Computing, or SciDAC, program. Credit: Adam Malin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-09/atomic-space-graphic-2_1920_72dpi_0.jpg?h=8a33d6d1&itok=caY64a8z)
ORNL is leading two nuclear physics research projects within the Scientific Discovery through Advanced Computing, or SciDAC, program from the Department of Energy Office of Science.
![Steven Hamilton, an R&D scientist in the HPC Methods for Nuclear Applications group at ORNL, leads the ExaSMR project. ExaSMR was developed to run on the Oak Ridge Leadership Computing Facility’s exascale-class supercomputer, Frontier. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-09/2023-P00165_1.jpg?h=c6980913&itok=YE6_qVLk)
The Exascale Small Modular Reactor effort, or ExaSMR, is a software stack developed over seven years under the Department of Energy’s Exascale Computing Project to produce the highest-resolution simulations of nuclear reactor systems to date. Now, ExaSMR has been nominated for a 2023 Gordon Bell Prize by the Association for Computing Machinery and is one of six finalists for the annual award, which honors outstanding achievements in high-performance computing from a variety of scientific domains.