Filter News
Area of Research
News Topics
- (-) Buildings (18)
- (-) Molten Salt (1)
- (-) Physics (28)
- 3-D Printing/Advanced Manufacturing (37)
- Advanced Reactors (8)
- Artificial Intelligence (46)
- Big Data (22)
- Bioenergy (50)
- Biology (58)
- Biomedical (28)
- Biotechnology (11)
- Chemical Sciences (22)
- Clean Water (14)
- Climate Change (48)
- Composites (6)
- Computer Science (82)
- Coronavirus (17)
- Critical Materials (2)
- Cybersecurity (14)
- Decarbonization (45)
- Education (1)
- Emergency (2)
- Energy Storage (28)
- Environment (101)
- Exascale Computing (25)
- Fossil Energy (4)
- Frontier (24)
- Fusion (30)
- Grid (23)
- High-Performance Computing (43)
- Hydropower (5)
- Isotopes (27)
- ITER (2)
- Machine Learning (22)
- Materials (41)
- Materials Science (44)
- Mathematics (6)
- Mercury (7)
- Microelectronics (2)
- Microscopy (20)
- Nanotechnology (16)
- National Security (35)
- Net Zero (8)
- Neutron Science (47)
- Nuclear Energy (54)
- Partnerships (16)
- Polymers (8)
- Quantum Computing (20)
- Quantum Science (30)
- Renewable Energy (1)
- Security (11)
- Simulation (30)
- Software (1)
- Space Exploration (12)
- Summit (30)
- Sustainable Energy (43)
- Transformational Challenge Reactor (3)
- Transportation (27)
Media Contacts
Researchers used quantum simulations to obtain new insights into the nature of neutrinos — the mysterious subatomic particles that abound throughout the universe — and their role in the deaths of massive stars.
In May, the Department of Energy’s Oak Ridge and Brookhaven national laboratories co-hosted the 15th annual International Particle Accelerator Conference, or IPAC, at the Music City Center in Nashville, Tennessee.
When scientists pushed the world’s fastest supercomputer to its limits, they found those limits stretched beyond even their biggest expectations. In the latest milestone, a team of engineers and scientists used Frontier to simulate a system of nearly half a trillion atoms — the largest system ever modeled and more than 400 times the size of the closest competition.
Helping hundreds of manufacturing industries and water-power facilities across the U.S. increase energy efficiency requires a balance of teaching and training, blended with scientific guidance and technical expertise. It’s a formula for success that ORNL researchers have been providing to DOE’s Better Plants Program for more than a decade.
Cheekatamarla is a researcher in the Multifunctional Equipment Integration group with previous experience in product deployment. He is researching alternative energy sources such as hydrogen for cookstoves and his research supports the decarbonization of building technologies.
Shift Thermal, a member of Innovation Crossroads’ first cohort of fellows, is commercializing advanced ice thermal energy storage for HVAC, shifting the cooling process to be more sustainable, cost-effective and resilient. Shift Thermal wants to enable a lower-cost, more-efficient thermal energy storage method to provide long-duration resilient cooling when the electric grid is down.
Three ORNL intellectual property projects with industry partners have advanced in DOE's Office of Technology Transitions Making Advanced Technology Commercialization Harmonized, or Lab MATCH, prize, which encourages entrepreneurs to find actionable pathways that bring lab-developed intellectual property to market.
Students with a focus on building science will spend 10 weeks this summer interning at ORNL, the National Renewable Energy Laboratory and Pacific Northwest Laboratory as winners of the DOE’s Office of Energy Efficiency and Renewable Energy’s Building Technologies Office sixth annual JUMP into STEM finals competition.
A modeling analysis led by ORNL gives the first detailed look at how geothermal energy can relieve the electric power system and reduce carbon emissions if widely implemented across the United States within the next few decades.
The 2023 top science achievements from HFIR and SNS feature a broad range of materials research published in high impact journals such as Nature and Advanced Materials.