![White car (Porsche Taycan) with the hood popped is inside the building with an american flag on the wall.](/sites/default/files/styles/featured_square_large/public/2024-06/2024-P09317.jpg?h=8f9cfe54&itok=m6sQhZRq)
Filter News
Area of Research
News Type
News Topics
- (-) 3-D Printing/Advanced Manufacturing (9)
- (-) Artificial Intelligence (18)
- (-) Big Data (6)
- (-) Cybersecurity (1)
- (-) Energy Storage (7)
- (-) Exascale Computing (6)
- (-) High-Performance Computing (10)
- (-) Materials Science (13)
- (-) Microscopy (3)
- (-) Nanotechnology (1)
- (-) Polymers (3)
- (-) Security (2)
- (-) Space Exploration (3)
- (-) Transportation (6)
- Advanced Reactors (3)
- Bioenergy (8)
- Biology (10)
- Biomedical (3)
- Biotechnology (4)
- Buildings (10)
- Chemical Sciences (7)
- Clean Water (3)
- Climate Change (14)
- Composites (4)
- Computer Science (16)
- Critical Materials (1)
- Decarbonization (14)
- Education (1)
- Emergency (1)
- Environment (15)
- Fossil Energy (2)
- Frontier (6)
- Fusion (6)
- Grid (4)
- Isotopes (8)
- ITER (1)
- Machine Learning (7)
- Materials (9)
- Mathematics (2)
- National Security (10)
- Net Zero (3)
- Neutron Science (7)
- Nuclear Energy (6)
- Partnerships (8)
- Physics (4)
- Quantum Computing (8)
- Quantum Science (12)
- Simulation (11)
- Summit (4)
- Sustainable Energy (12)
Media Contacts
![ORNL researchers achieved the highest wireless power transfer level for a light-duty passenger vehicle when the team demonstrated a 100-kW wireless power transfer to an EV using ORNL’s patented polyphase electromagnetic coupling coil. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-03/2024-P00658%20%281%29.jpg?h=c6980913&itok=2gqTSOqI)
A team of researchers at ORNL demonstrated that a light-duty passenger electric vehicle can be wirelessly charged at 100-kW with 96% efficiency using polyphase electromagnetic coupling coils with rotating magnetic fields.
![Sean Oesch](/sites/default/files/styles/list_page_thumbnail/public/2024-03/Picture1.jpg?h=b6c94d59&itok=HaSGWHLY)
While government regulations are slowly coming, a group of cybersecurity professionals are sharing best practices to protect large language models powering these tools. Sean Oesch, a leader in emerging cyber technologies, recently contributed to the OWASP AI Security and Privacy Guide to inform global AI security standards and regulations.
![AI-driven attention mechanisms aid in streamlining cancer pathology reporting.](/sites/default/files/styles/list_page_thumbnail/public/2024-03/attention%20mechanism%20%282%29.jpg?h=3a7a7cb1&itok=_OJowEl4)
In partnership with the National Cancer Institute, researchers from the Department of Energy’s Oak Ridge National Laboratory’s Modeling Outcomes for Surveillance using Scalable Artificial Intelligence are building on their groundbreaking work to
![Instantaneous solution quantities shown for a static Mach 1.4 solution on a mesh consisting of 33 billion elements using 33,880 GPUs, or 90% of Frontier. From left to right, contours show the mass fractions of the hydroxyl radical and H2O, the temperature in Kelvin, and the local Mach number. Credit: Gabriel Nastac/NASA](/sites/default/files/styles/list_page_thumbnail/public/2024-02/static_fine.png?h=f3b6c815&itok=4rgMEnKZ)
Since 2019, a team of NASA scientists and their partners have been using NASA’s FUN3D software on supercomputers located at the Department of Energy’s Oak Ridge Leadership Computing Facility to conduct computational fluid dynamics simulations of a human-scale Mars lander. The team’s ongoing research project is a first step in determining how to safely land a vehicle with humans onboard onto the surface of Mars.
![New system combines human, artificial intelligence to improve experimentation](/sites/default/files/styles/list_page_thumbnail/public/2024-02/Screenshot%202024-02-14%20at%2011.37.46%20AM%20%281%29.png?h=e621a1e2&itok=N3lsBqrh)
To capitalize on AI and researcher strengths, scientists developed a human-AI collaboration recommender system for improved experimentation performance.
![A multidirectorate group from ORNL attended AGU23 and came away inspired for the year ahead in geospatial, earth and climate science](/sites/default/files/styles/list_page_thumbnail/public/2024-02/MicrosoftTeams-image%20%2815%29%20%281%29.png?h=a5eb5da0&itok=gY269KaC)
ORNL scientists and researchers attended the annual American Geophysical Union meeting and came away inspired for the year ahead in geospatial, earth and climate science.
![Chelsea Chen, polymer physicist at ORNL, stands in front of an eight-channel potentiostat and temperature chamber used for battery and electrochemical testing. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-02/2023-P19202.jpg?h=c6980913&itok=Q-GNSOOO)
Chelsea Chen, a polymer physicist at ORNL, is studying ion transport in solid electrolytes that could help electric vehicle battery charges last longer.
![: ORNL climate modeling expertise contributed to an AI-backed model that assesses global emissions of ammonia from croplands now and in a warmer future, while identifying mitigation strategies. This map highlights croplands around the world. Credit: U.S. Geological Survey](/sites/default/files/styles/list_page_thumbnail/public/2024-02/global_croplands_usgs_globe-4g_1.png?h=4016a495&itok=rb8eHyvK)
ORNL climate modeling expertise contributed to a project that assessed global emissions of ammonia from croplands now and in a warmer future, while also identifying solutions tuned to local growing conditions.
![Using a better modeling framework, with data collected from Mississippi Delta marshes, scientists are able to improve the predictions of methane and other greenhouse gas emissions. Credit: Matthew Berens/ORNL, U.S Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-01/picture1_0.jpg?itok=uQVJerN0)
Scientists at the Department of Energy’s Oak Ridge National Laboratory are using a new modeling framework in conjunction with data collected from marshes in the Mississippi Delta to improve predictions of climate-warming methane and nitrous oxide.
![Conversion of an atomic structure into a graph, where atoms are treating as nodes and interatomic bonds as edges. Credit: Massimiliano “Max” Lupo Pasini/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-01/hydra_gnn_diagram.png?h=2deb2cea&itok=4OvY68cs)
Researchers at the Department of Energy’s Oak Ridge and Lawrence Berkeley National Laboratories are evolving graph neural networks to scale on the nation’s most powerful computational resources, a necessary step in tackling today’s data-centric