Oak Ridge National Laboratory scientists are evaluating paths for licensing remotely operated microreactors, which could provide clean energy sources to hard-to-reach communities, such as isolated areas in Alaska.
Kevin Field at the Department of Energy’s Oak Ridge National Laboratory synthesizes and scrutinizes materials for nuclear power systems that must perform safely and efficiently over decades of irradiation.
As the rise of antibiotic-resistant bacteria known as superbugs threatens public health, Oak Ridge National Laboratory’s Shuo Qian and Veerendra Sharma from the Bhaba Atomic Research Centre in India are using neutron scattering to study how an antibacterial peptide interacts with and fights harmful bacteria.
Oak Ridge National Laboratory is using ultrasonic additive manufacturing to embed highly accurate fiber optic sensors in heat- and radiation-resistant materials, allowing for real-time monitoring that could lead to greater insights and safer reactors.
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.
Vera Bocharova at the Department of Energy’s Oak Ridge National Laboratory investigates the structure and dynamics of soft materials—polymer nanocomposites, polymer electrolytes and biological macromolecules—to advance materials and technologies for energy, medicine and other applications.
Scientists have tested a novel heat-shielding graphite foam, originally created at Oak Ridge National Laboratory, at Germany’s Wendelstein 7-X stellarator with promising results for use in plasma-facing components of fusion reactors.
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 National Laboratory geospatial scientists who study the movement of people are using advanced machine learning methods to better predict home-to-work commuting patterns.
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