Carter to lead Fusion Energy Division at Oak Ridge National Laboratory
A multi-lab research team led by ORNL's Paul Kent is developing a computer application called QMCPACK to enable precise and reliable predictions of the fundamental properties of materials critical in energy research.
ORNL has been selected to lead an Energy Frontier Research Center, or EFRC, focused on polymer electrolytes for next-generation energy storage devices such as fuel cells and solid-state electric vehicle batteries.
ORNL Corporate Fellow and Center for Nanophase Materials Sciences researcher Bobby Sumpter has been named fellow of two scientific professional societies: the Institute of Physics and the International Association of Advanced Materials.
As climate change leads to larger and more frequent wildfires, researchers at ORNL are using sensors, drones and machine learning to both prevent fires and reduce their damage to the electric grid.
To further the potential benefits of the nation’s hydropower resources, researchers at Oak Ridge National Laboratory have developed and maintain a comprehensive water energy digital platform called HydroSource.
Oak Ridge National Laboratory researchers are developing a first-of-its-kind artificial intelligence device for neutron scattering called Hyperspectral Computed Tomography, or HyperCT.
Burak Ozpineci, a Corporate Fellow and section head for Vehicle and Mobility Systems Research at Oak Ridge National Laboratory, is one of six international recipients of the eighth Nagamori Award.
Steven Arndt, distinguished R&D staff member in the Nuclear Energy and Fuel Cycle Division at ORNL, began a one-year term on June 16 as the 68th President of the American Nuclear Society.
Jagjit Nanda, a distinguished staff scientist, has been elected a fellow of the Materials Research Society. The lifetime appointment recognizes outstanding members whose sustained and distinguished contributions to the advancement of materials research are internationally recognized.
Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions.