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Media Contacts
![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.
![Six ORNL scientists have been elected as fellows to the American Association for the Advancement of Science, or AAAS. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-11/AAASfellows.jpg?h=d761c044&itok=opKRkA17)
Six ORNL scientists have been elected as fellows to the American Association for the Advancement of Science, or AAAS.
![Scientists synthesized graphene nanoribbons (yellow) on a titanium dioxide substrate (blue). The lighter ends show magnetic states. Inset: The ends have up and down spin, ideal for creating qubits. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-10/STM_Science_image_0.jpg?h=83401e72&itok=3oR6W30s)
An international multi-institution team of scientists has synthesized graphene nanoribbons – ultrathin strips of carbon atoms – on a titanium dioxide surface using an atomically precise method that removes a barrier for custom-designed carbon
![ORNL researchers and energy storage startup Sparkz have developed a cobalt-free cathode material for use in lithium-ion batteries Credit: Ilias Belharouak/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-10/cobalt-sparkz_0.jpg?h=cd715a88&itok=vTU2FKUY)
Four research teams from the Department of Energy’s Oak Ridge National Laboratory and their technologies have received 2020 R&D 100 Awards.
![ORNL researchers developed a quantum, or squeezed, light approach for atomic force microscopy that enables measurement of signals otherwise buried by noise. Credit: Raphael Pooser/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-09/cantilever_cell_lower_perspective_composite3a%20copy.jpg?h=cdc5ebd8&itok=MDv06yLW)
Researchers at ORNL used quantum optics to advance state-of-the-art microscopy and illuminate a path to detecting material properties with greater sensitivity than is possible with traditional tools.
![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.
![Sergei Kalinin](/sites/default/files/styles/list_page_thumbnail/public/2020-07/2019-P00126_0.png?h=5969a3b5&itok=66cucDCt)
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.
![An organic solvent and water separate and form nanoclusters on the hydrophobic and hydrophilic sections of plant material, driving the efficient deconstruction of biomass. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy](/sites/default/files/2020-07/THF_high_res.gif)
Scientists at ORNL used neutron scattering and supercomputing to better understand how an organic solvent and water work together to break down plant biomass, creating a pathway to significantly improve the production of renewable
![Map with focus on sub-saharan Africa](/sites/default/files/styles/list_page_thumbnail/public/2020-07/firms3-Africa-NASA_0.jpg?h=27f1d52b&itok=G8uUS5cH)
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.