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Media Contacts
![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.
![Using the ASGarD mathematical framework, scientists can model and visualize the electric fields, shown as arrows, circling around magnetic fields that are colorized to represent field magnitude of a fusion plasma. Credit: David Green/ORNL](/sites/default/files/styles/list_page_thumbnail/public/2020-08/Max1_t5e-1_EB_0.png?h=35bae166&itok=iRtx2TVM)
Combining expertise in physics, applied math and computing, Oak Ridge National Laboratory scientists are expanding the possibilities for simulating electromagnetic fields that underpin phenomena in materials design and telecommunications.
![Researchers at Oak Ridge National Laboratory shed new light on elusive chemical processes at the liquid-liquid interface during solvent extraction of cobalt (dark blue). Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-08/6_final.png?h=d1cb525d&itok=KQte9kSh)
Real-time measurements captured by researchers at ORNL provide missing insight into chemical separations to recover cobalt, a critical raw material used to make batteries and magnets for modern 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.
![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.
![Drone shot above SPRUCE enclosure](/sites/default/files/styles/list_page_thumbnail/public/2020-07/P20_Drone_YUN00190_0.jpg?h=fe23bcc2&itok=PwOXZq1F)
Scientists at Oak Ridge National Laboratory have demonstrated a direct relationship between climate warming and carbon loss in a peatland ecosystem.
![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
![Burak Ozpineci](/sites/default/files/styles/list_page_thumbnail/public/2020-07/2016-P07072_0.jpg?h=a31ffb6c&itok=dsHTBEvN)
Burak Ozpineci of the Electrical and Electronics Systems Research Division at Oak Ridge National Laboratory has won the 2020 IEEE Power Electronics Society Vehicle and Transportation Systems Achievement Award.
![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.