It would be a challenge for any scientist to match Alexey Serov’s rate of inventions related to green hydrogen fuel. But this researcher at ORNL has 84 patents with at least 35 more under review, so his electrifying pace is unlikely to slow down any time soon.
Four scientists affiliated with ORNL were named Battelle Distinguished Inventors during the lab’s annual Innovation Awards on Dec. 1 in recognition of being granted 14 or more United States patents.
The common sounds in the background of daily life – like a refrigerator’s hum, an air conditioner’s whoosh and a heat pump’s buzz – often go unnoticed. These noises, however, are the heartbeat of a healthy building and integral for comfort and convenience.
A licensing agreement between the Department of Energy’s Oak Ridge National Laboratory and research partner ZEISS will enable industrial X-ray computed tomography, or CT, to perform rapid evaluations of 3D-printed components using ORNL’s machine
Bryan Maldonado, a dynamic systems and controls researcher at ORNL, has been recognized by the 2023 Hispanic Engineer National Achievements Awards Conference, or HENAAC, with the Most Promising Engineer Award.
Scientist-inventors from ORNL will present seven new technologies during the Technology Innovation Showcase on Friday, July 14, from 8 a.m.–4 p.m. at the Joint Institute for Computational Sciences on ORNL’s campus.
Seven scientists at the Department of Energy’s Oak Ridge National Laboratory have been named Battelle Distinguished Inventors, in recognition of their obtaining 14 or more patents during their careers at the lab.
Laboratory Director Thomas Zacharia presented five Director’s Awards during Saturday night's annual Awards Night event hosted by UT-Battelle, which manages ORNL for the Department of Energy.
Materials scientist Denise Antunes da Silva researches ways to reduce concrete’s embodied carbon in the Sustainable Building Materials Laboratory at ORNL, a research space dedicated to studying environmentally friendly building materials. Credit: ORNL, U.S. Dept. of Energy
A new deep-learning framework developed at ORNL is speeding up the process of inspecting additively manufactured metal parts using X-ray computed tomography, or CT, while increasing the accuracy of the results. The reduced costs for time, labor, maintenance and energy are expected to accelerate expansion of additive manufacturing, or 3D printing.