Polyphase wireless power transfer system achieves 270-kilowatt charge, s...
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.
Doug Kothe has been named associate laboratory director for the Computing and Computational Sciences Directorate at ORNL, effective June 6.
To optimize biomaterials for reliable, cost-effective paper production, building construction, and biofuel development, researchers often study the structure of plant cells using techniques such as freezing plant samples or placing them in a vacuum.
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.
The Frontier supercomputer at the Department of Energy’s Oak Ridge National Laboratory earned the top ranking today as the world’s fastest on the 59th TOP500 list, with 1.1 exaflops of performance. The system is the first to achieve an unprecedented level of computing performance known as exascale, a threshold of a quintillion calculations per second.
ORNL scientists will present new technologies available for licensing during the annual Technology Innovation Showcase. The event is 9 a.m. to 3 p.m. Thursday, June 16, at the Manufacturing Demonstration Facility at ORNL’s Hardin Valley campus.
Jennifer Morrell-Falvey’s interest in visualizing the science behind natural processes was what drew her to ORNL in what she expected to be a short stint some 18 years ago.
Researchers at ORNL are teaching microscopes to drive discoveries with an intuitive algorithm, developed at the lab’s Center for Nanophase Materials Sciences, that could guide breakthroughs in new materials for energy technologies, sensing and computing.
Miaofang Chi, a scientist at ORNL, has been elected a Fellow of the Microscopy Society of America.
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.