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Media Contacts
![ORNL researchers demonstrated a 3D printed power pole made of bioderived and recycled materials could be easily manufactured, transported and assembled, enabling the quick restoration of power after natural disasters. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-07/PrintedTubeCropped.jpg?h=7e76e9d2&itok=0C7p7pB3)
A team of researchers at Oak Ridge National Laboratory demonstrated the ability to additively manufacture power poles from bioderived and recycled materials, which could more quickly restore electricity after natural disasters.
![ORNL researchers installed and demonstrated their wireless charging technology for the first time on an autonomous vehicle – the Local Motors Olli shuttle bus. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-07/2021-P03084_1.jpg?h=c6980913&itok=zDDq9rRc)
Oak Ridge National Laboratory researchers demonstrated their wireless charging technology on an autonomous electric vehicle for the first time in a project with Local Motors.
![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](/sites/default/files/styles/list_page_thumbnail/public/2021-02/SAW%20sensors%202021-P01084_0.jpg?h=8f9cfe54&itok=H3Fe6A_G)
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](/sites/default/files/styles/list_page_thumbnail/public/2021-03/WMMPA%20Pella%20Marion%20790_Small.jpg?h=f14a4ec1&itok=ItU-Ca6U)
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.
![An X-ray CT image of a 3D-printed metal turbine blade was reconstructed using ORNL’s neural network and advanced algorithms. Credit: Amir Ziabari/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-01/Manufacturing%20-%20Defect%20detection%202_0.jpg?h=259e5a75&itok=CwpLQv6U)
Algorithms developed at Oak Ridge National Laboratory can greatly enhance X-ray computed tomography images of 3D-printed metal parts, resulting in more accurate, faster scans.
![Distinguished Inventors](/sites/default/files/styles/list_page_thumbnail/public/2020-12/inventors.jpg?h=4631f1c1&itok=xhAGY0kv)
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.
![David Kropaczek](/sites/default/files/styles/list_page_thumbnail/public/2020-11/2016-P07859_0.jpg?h=49ab6177&itok=nsklImHq)
David Kropaczek, director of the Consortium for Advanced Simulation of Light Water Reactors, or CASL, at the Department of Energy’s Oak Ridge National Laboratory, has been named a fellow of the American Nuclear Society.
![Fuel pellets sometimes degrade to a sandlike consistency and can disperse into the reactor core if a rod’s cladding bursts. ORNL researchers are studying how often this happens and what impact it has, in order to let reactors operate as long as possible without increasing risk.](/sites/default/files/styles/list_page_thumbnail/public/2020-08/X2001338_FuelFragmentation_GraphicUpdate_Bumpus_jnj-02_0.jpg?h=049a2720&itok=mzNfF2cS)
A developing method to gauge the occurrence of a nuclear reactor anomaly has the potential to save millions of dollars.
![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.](/sites/default/files/styles/list_page_thumbnail/public/2020-08/Peregrine%20Chase%20Joslin_0.jpg?h=51c7b451&itok=4Hc6PNwu)
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.
![Cars and coronavirus](/sites/default/files/styles/list_page_thumbnail/public/2020-08/Transportation-Gauging_pandemic_impact_ORNL_0.jpg?h=4a7d1ed4&itok=Xqx4kknO)
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.