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ORNL researchers are developing a method to print low-cost, high-fidelity, customizable sensors for monitoring power grid equipment. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

A method developed at Oak Ridge National Laboratory to print high-fidelity, passive sensors for energy applications can reduce the cost of monitoring critical power grid assets.

Pella Marion

A new Department of Energy report produced by Oak Ridge National Laboratory details national and international trends in hydropower, including the role waterpower plays in enhancing the flexibility and resilience of the power grid.

Distinguished Inventors

Six scientists at the Department of Energy’s Oak Ridge National Laboratory were named Battelle Distinguished Inventors, in recognition of obtaining 14 or more patents during their careers at the lab.

Hector J. Santos-Villalobos, left, and Oscar A. Martinez

Two staff members at the Department of Energy’s Oak Ridge National Laboratory have received prestigious HENAAC and Luminary Awards from Great Minds in STEM, a nonprofit organization that focuses on promoting STEM careers in underserved 

Researcher Chase Joslin uses Peregrine software to monitor and analyze a component being 3D printed at the Manufacturing Demonstration Facility at ORNL. Credit: Luke Scime/ORNL, U.S. Dept. of Energy.

Oak Ridge National Laboratory researchers have developed artificial intelligence software for powder bed 3D printers that assesses the quality of parts in real time, without the need for expensive characterization equipment.

Andrew Harter, pictured, and fellow ORNL staff members formed Horizon31 to build a set of products and services that provide customized unmanned vehicle control systems. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Horizon31, LLC has exclusively licensed a novel communication system that allows users to reliably operate unmanned vehicles such as drones from anywhere in the world using only an internet connection.

Cars and coronavirus

Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.

Sergei Kalinin

Five researchers at the Department of Energy’s Oak Ridge National Laboratory have been named ORNL Corporate Fellows in recognition of significant career accomplishments and continued leadership in their scientific fields.

Map with focus on sub-saharan Africa

Researchers at Oak Ridge National Laboratory developed a method that uses machine learning to predict seasonal fire risk in Africa, where half of the world’s wildfire-related carbon emissions originate.

Wireless charging – Special delivery for UPS

Researchers at Oak Ridge National Laboratory demonstrated a 20-kilowatt bi-directional wireless charging system on a UPS plug-in hybrid electric delivery truck, advancing the technology to a larger class of vehicles and enabling a new energy storage method for fleet owners and their facilities.