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.
Researchers at Oak Ridge National Laboratory and Momentum Technologies have piloted an industrial-scale process for recycling valuable materials in the millions of tons of e-waste generated annually in the United States.
Researchers at Oak Ridge National Laboratory are using state-of-the-art methods to shed light on chemical separations needed to recover rare-earth elements and secure critical materials for clean energy technologies.
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.
A new Department of Energy report produced by Oak Ridge National Laboratory identifies several supply chain must-haves in maintaining the pivotal role hydropower will play in decarbonizing the nation’s grid.
Several electrolyte and thin-film coating technologies, developed at Oak Ridge National Laboratory, have been licensed by BTRY, a battery technology company based in Virginia, to make batteries with increased energy density, at lower cost, and with an improved safety profile in crashes.
Oak Ridge National Laboratory researchers demonstrated an electron microscopy technique for imaging lithium in energy storage materials, such as lithium ion batteries, at the atomic scale.
University of Pennsylvania researchers called on computational systems biology expertise at Oak Ridge National Laboratory to analyze large datasets of single-cell RNA sequencing from skin samples afflicted with atopic dermatitis.
Researchers at Oak Ridge National Laboratory are using a novel approach in determining environmental impacts to aquatic species near hydropower facilities, potentially leading to smarter facility designs that can support electrical grid reliability.
Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity.