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Media Contacts
ORNL and Department of Energy officials dedicated the launch of two clean energy research initiatives that focus on the recycling and recovery of advanced manufacturing materials and on connected and
Scientists at Oak Ridge National Laboratory used new techniques to create a composite that increases the electrical current capacity of copper wires, providing a new material that can be scaled for use in ultra-efficient, power-dense electric vehicle traction motors.
Scientists at ORNL and the University of Nebraska have developed an easier way to generate electrons for nanoscale imaging and sensing, providing a useful new tool for material science, bioimaging and fundamental quantum research.
The Department of Energy announced awards for 10 projects with private industry that will allow for collaboration with DOE national laboratories in accelerating fusion energy development.
Oak Ridge National Laboratory scientists have discovered a cost-effective way to significantly improve the mechanical performance of common polymer nanocomposite materials.
The inside of future nuclear fusion energy reactors will be among the harshest environments ever produced on Earth. What’s strong enough to protect the inside of a fusion reactor from plasma-produced heat fluxes akin to space shuttles reentering Earth’s atmosphere?
An all-in-one experimental platform developed at Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences accelerates research on promising materials for future technologies.
Combining expertise in physics, applied math and computing, Oak Ridge National Laboratory scientists are expanding the possibilities for simulating electromagnetic fields that underpin phenomena in materials design and telecommunications.
Real-time measurements captured by researchers at ORNL provide missing insight into chemical separations to recover cobalt, a critical raw material used to make batteries and magnets for modern technologies.
Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.