Oak Ridge National Laboratory geospatial scientists who study the movement of people are using advanced machine learning methods to better predict home-to-work commuting patterns.
OAK RIDGE, Tenn., Jan. 31, 2019—A new electron microscopy technique that detects the subtle changes in the weight of proteins at the nanoscale—while keeping the sample intact—could open a new pathway for deeper, more comprehensive studies of the basic building blocks of life.
Jon Poplawsky, a materials scientist at the Department of Energy’s Oak Ridge National Laboratory, develops and links advanced characterization techniques that improve our ability to see and understand atomic-scale features of diverse materials
Scientists at Oak Ridge National Laboratory and Hypres, a digital superconductor company, have tested a novel cryogenic, or low-temperature, memory cell circuit design that may boost memory storage while using less energy in future exascale and quantum computing applications.
Oak Ridge National Laboratory scientists studying fuel cells as a potential alternative to internal combustion engines used sophisticated electron microscopy to investigate the benefits of replacing high-cost platinum with a lower cost, carbon-nitrogen-manganese-based catalyst.
ORNL helps develop hybrid computational strategy for efficient sequencing of massive genome datasets
Computing experts at the Department of Energy’s Oak Ridge National Laboratory collaborated with a team of university researchers and software companies to develop a novel hybrid computational strategy to efficiently discover genetic variants
The Department of Energy’s Oak Ridge National Laboratory has received funding from DOE’s Exascale Computing Project (ECP) to develop applications for future exascale systems that will be 50 to 100 times more powerful than today’s fastest supercomputers.