Four ORNL teams and one researcher were recognized for excellence in technology transfer and technology transfer innovation.
Anne Campbell, a researcher at ORNL, recently won the Young Leaders Professional Development Award from the Minerals, Metals & Materials Society, or TMS, and has been chosen as the first recipient of the Young Leaders International Scholar Program award from TMS and the Korean Institute of Metals and Materials, or KIM.
Dean Pierce of ORNL and a research team led by ORNL’s Alex Plotkowski were honored by DOE’s Vehicle Technologies Office for development of novel high-performance alloys that can withstand extreme environments.
Four firms doing business with the Department of Energy’s Oak Ridge National Laboratory received ORNL Small Business Awards during an awards ceremony on June 29.
A new report published by ORNL assessed how advanced manufacturing and materials, such as 3D printing and novel component coatings, could offer solutions to modernize the existing fleet and design new approaches to hydropower.
A partnership of ORNL, the Tennessee Department of Economic and Community Development, the Community Reuse Organization of East Tennessee and TVA that aims to attract nuclear energy-related firms to Oak Ridge has been recognized with a state and local economic development award from the Federal Laboratory Consortium.
Researchers at Oak Ridge National Laboratory have identified a key need for future hydropower innovations – full-scale testing – to better inform developers and operators before making major investments.
To further the potential benefits of the nation’s hydropower resources, researchers at Oak Ridge National Laboratory have developed and maintain a comprehensive water energy digital platform called HydroSource.
Although more than 92,000 dams populate the country, the vast majority — about 89,000 — do not generate electricity through hydropower.
An Oak Ridge National Laboratory team developed a novel technique using sensors to monitor seismic and acoustic activity and machine learning to differentiate operational activities at facilities from “noise” in the recorded data.