Updated software improves slicing for large-format 3D printing
Zheng Gai, a senior staff scientist at ORNL’s Center for Nanophase Materials Sciences, has been selected as editor-in-chief of the Spin Crossover and Spintronics section of Magnetochemistry.
Anne Campbell, an R&D associate in ORNL’s Materials Science and Technology Division since 2016, has been selected as an associate editor of the Journal of Nuclear Materials.
The Department of Energy’s Center for Bioenergy Innovation, led by Oak Ridge National Laboratory, recently added three new members to its board of directors: Deborah Crawford of the University of Tennessee, Knoxville; Susan Hubbard of ORNL; and Maureen McCann of the National Renewable Energy Laboratory.
Merlin Theodore is one of eight new board members announced by President Biden; she will join the 25-member board for a six-year term.
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.
Three researchers at ORNL have been named ORNL Corporate Fellows in recognition of significant career accomplishments and continued leadership in their scientific fields.
Although blockchain is best known for securing digital currency payments, researchers at the Department of Energy’s Oak Ridge National Laboratory are using it to track a different kind of exchange: It’s the first time blockchain has ever been used to validate communication among devices on the electric grid.
Eight ORNL scientists are among the world’s most highly cited researchers, according to a bibliometric analysis conducted by the scientific publication analytics firm Clarivate.
Marc-Antoni Racing has licensed a collection of patented energy storage technologies developed at ORNL. The technologies focus on components that enable fast-charging, energy-dense batteries for electric and hybrid vehicles and grid storage.
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.