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Media Contacts
![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.
![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](/sites/default/files/styles/list_page_thumbnail/public/2020-08/2018-P09718_0.jpg?h=dd220a27&itok=n2MR7GK5)
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.
![ORNL’s Lab-on-a-crystal uses machine learning to correlate materials’ mechanical, optical and electrical responses to dynamic environments. Credit: Ilia Ivanov/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-08/lab_on_crystal2_0.png?h=bc215d7c&itok=5Zsjkf9e)
An all-in-one experimental platform developed at Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences accelerates research on promising materials for future technologies.
![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.
![The Reactive Additive Manufacturing, or RAM, machine for large-scale thermoset printing supports two technologies licensed by MVP and developed in collaboration with ORNL. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy.](/sites/default/files/styles/list_page_thumbnail/public/2020-07/2019-P13390%20%282%29_0.jpg?h=036a71b7&itok=plG71UED)
ORNL has licensed two additive manufacturing-related technologies that aim to streamline and ramp up production processes to Knoxville-based Magnum Venus Products, Inc., a global manufacturer of fluid movement and product solutions for industrial applications in composites and adhesives.
![Analyses of lung fluid cells from COVID-19 patients conducted on the nation’s fastest supercomputer point to gene expression patterns that may explain the runaway symptoms produced by the body’s response to SARS-CoV-2. Credit: Jason B. Smith/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-07/cells%20200%5B1%5D.png?h=b95f6d72&itok=V2OxqL5l)
A team led by Dan Jacobson of Oak Ridge National Laboratory used the Summit supercomputer at ORNL to analyze genes from cells in the lung fluid of nine COVID-19 patients compared with 40 control patients.
![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/styles/list_page_thumbnail/public/2020-07/THF_high_res.gif?h=5a472534&itok=5peedFnF)
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.
![Selenium atoms, represented by orange, implant in a monolayer of blue tungsten and yellow sulfur to form a Janus layer. In the background, electron microscopy confirms atomic positions. Credit: Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-06/Cover%20Art%20nn-2019-10196k_8_0.jpg?h=97102f31&itok=F-JpEvZ2)
An ORNL team used a simple process to implant atoms precisely into the top layers of ultra-thin crystals, yielding two-sided structures with different chemical compositions.