A team of researchers at Oak Ridge National Laboratory have demonstrated that designed synthetic polymers can serve as a high-performance binding material for next-generation lithium-ion batteries.
Galigekere is principal investigator for the breakthrough work in fast, wireless charging of electric vehicles being performed at the National Transportation Research Center at Oak Ridge National Laboratory.
OAK RIDGE, Tenn., May 7, 2019—The U.S. Department of Energy today announced a contract with Cray Inc. to build the Frontier supercomputer at Oak Ridge National Laboratory, which is anticipated to debut in 2021 as the world’s most powerful computer with a performance of greater than 1.5 exaflops.
Scientists at Oak Ridge National Laboratory have developed a low-cost, printed, flexible sensor that can wrap around power cables to precisely monitor electrical loads from household appliances to support grid operations.
Oak Ridge National Laboratory’s latest Transportation Energy Data Book: Edition 37 reports that the number of vehicles nationwide is growing faster than the population, with sales more than 17 million since 2015, and the average household vehicle travels more than 11,000 miles per year.
Gleaning valuable data from social platforms such as Twitter—particularly to map out critical location information during emergencies— has become more effective and efficient thanks to Oak Ridge National Laboratory.
Oak Ridge National Laboratory scientists have created open source software that scales up analysis of motor designs to run on the fastest computers available, including those accessible to outside users at the Oak Ridge Leadership Computing Facility.
OAK RIDGE, Tenn., Feb. 12, 2019—A team of researchers from the Department of Energy’s Oak Ridge and Los Alamos National Laboratories has partnered with EPB, a Chattanooga utility and telecommunications company, to demonstrate the effectiveness of metro-scale quantum key distribution (QKD).
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 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.